Provided by: plink1.9_1.90~b6.6-181012-1_amd64 bug


       PLINK - whole genome SNP analysis


       PLINK   v1.90b6.6  64-bit  (12  Oct  2018)    (C)
       2005-2018 Shaun Purcell, Christopher Chang   GNU General Public License v3

       In the command line flag definitions that follow,

              * [square brackets] denote a required parameter, where the text between the

              brackets describes its nature.

              * <angle brackets> denote an optional modifier (or if '|' is present, a set

       of mutually exclusive optional modifiers).
              Use the EXACT text in the

              definition, e.g. '--dummy acgt'.

              * There's one exception to the angle brackets/exact text rule: when an angle

              bracket term ends with '=[value]', '[value]' designates a variable parameter.

              * {curly braces} denote an optional parameter, where the text between the

              braces describes its nature.

              * An ellipsis (...) indicates that you may enter multiple parameters of the

              specified type.

              plink [input flag(s)...] {command flag(s)...} {other flag(s)...} plink --help {flag

       Most PLINK runs require exactly one main input fileset.  The following flags are available
       for defining its form and location:

       --bfile {prefix} : Specify .bed + .bim + .fam prefix (default 'plink').

       --bed [filename] : Specify full name of .bed file.

       --bim [filename] : Specify full name of .bim file.

       --fam [filename] : Specify full name of .fam file.

              :    With    --file/--tfile/--lfile/--vcf/--bcf/--data/--23file,    don't    delete
              autogenerated binary fileset at end of run.

       --file {prefix}
              : Specify .ped + .map filename prefix (default 'plink').

       --ped [filename] : Specify full name of .ped file.

       --map [filename] : Specify full name of .map file.

              : .fam/.ped file does not contain column 1 (family ID).

              : .fam/.ped file does not contain columns 3-4 (parents).

              : .fam/.ped file does not contain column 5 (sex).

              : .fam/.ped file does not contain column 6 (phenotype).

       --tfile {prefix} : Specify .tped + .tfam filename prefix (default 'plink').

       --tped [fname]
              : Specify full name of .tped file.

       --tfam [fname]
              : Specify full name of .tfam file.

       --lfile {prefix} : Specify .lgen + .map + .fam (long-format fileset) prefix.

       --lgen [fname]
              : Specify full name of .lgen file.

       --reference [fn] : Specify default allele file accompanying .lgen input.

              :  When  used  with  --lfile/--lgen  +  --reference,  specifies that the .lgen file
              contains reference allele counts.

       --vcf [filename] : Specify full name of .vcf or .vcf.gz file.

       --bcf [filename] : Specify full name of BCF2 file.

       --data {prefix}
              : Specify Oxford .gen + .sample prefix (default 'plink').

       --gen [filename] : Specify full name of .gen or .gen.gz file.

       --bgen [f] <snpid-chr> : Specify full name of .bgen file.

       --sample [fname] : Specify full name of .sample file.

       --23file [fname] {FID} {IID} {sex} {pheno} {pat. ID} {mat. ID} :

              Specify 23andMe input file.

       --grm-gz {prfx}
              : Specify .grm.gz + (GCTA rel. matrix) prefix.

       --grm-bin {prfx} : Specify .grm.bin + .grm.N.bin + (GCTA triangular
              binary relationship matrix) filename prefix.

       --dummy [sample ct] [SNP ct] {missing geno freq} {missing pheno freq}

              <acgt | 1234 | 12> <scalar-pheno>

              This generates a fake input dataset with the specified number of samples and  SNPs.
              By  default, the missing genotype and phenotype frequencies are zero, and genotypes
              are As and Bs (change the  latter  with  'acgt'/'1234'/'12').   The  'scalar-pheno'
              modifier  causes a normally distributed scalar phenotype to be generated instead of
              a binary one.

       --simulate [simulation parameter file] <tags | haps> <acgt | 1234 | 12>

       --simulate-qt [simulation parameter file] <tags | haps> <acgt | 1234 | 12>

       --simulate generates a fake input dataset with disease-associated SNPs,

              while --simulate-qt generates a dataset with quantitative trait loci.

       Output files have names of the form 'plink.{extension}' by default.  You  can  change  the
       'plink' prefix with

       --out [prefix]
              : Specify prefix for output files.

       Most runs also require at least one of the following commands:


       Create a new binary fileset.
              Unlike the automatic text-to-binary

              converters  (which  only  heed  chromosome  filters),  this supports all of PLINK's
              filtering flags.



       Variants of --make-bed which only write a new .bim or .fam file.
              Can be

              used with only .bim/.fam  input.   USE  THESE  CAUTIOUSLY.   It  is  very  easy  to
              desynchronize your binary genotype data and your .bim/.fam indexes if you use these
              commands improperly.  If you have any doubt, stick with --make-bed.

       --recode [output format] <01 | 12> <tab | tabx | spacex | bgz | gen-gz>

              <include-alt> <omit-nonmale-y>

       Create a new text fileset with all filters applied.
              The following output

              formats are supported: * '23': 23andMe 4-column format.  This can only be used on a

              sample's  data  (--keep  may  be handy), and does not support multicharacter allele

              * 'A': Sample-major additive (0/1/2) coding, suitable for loading from R.

              If you need uncounted alleles to be named in the header line, add the 'include-alt'

              * 'AD': Sample-major additive (0/1/2) + dominant (het=1/hom=0) coding.

              Also supports 'include-alt'.

              *  'A-transpose':  Variant-major 0/1/2.  * 'beagle': Unphased per-autosome .dat and
              .map files, readable by early

              BEAGLE versions.

              * 'beagle-nomap': Single .beagle.dat file.  * 'bimbam': Regular BIMBAM  format.   *
              'bimbam-1chr': BIMBAM format, with a two-column .pos.txt file.  Does not

              support multiple chromosomes.

              * 'fastphase': Per-chromosome fastPHASE files, with

              .chr-[chr #].recode.phase.inp filename extensions.

       * 'fastphase-1chr': Single .recode.phase.inp file.
              Does not support

              multiple chromosomes.

              * 'HV': Per-chromosome Haploview files, with .chr-[chr #][.ped + .info]

              filename extensions.

       * 'HV-1chr': Single Haploview .ped + .info file pair.
              Does not support

              multiple chromosomes.

              *  'lgen':  PLINK  1  long-format  (.lgen + .fam + .map), loadable with --lfile.  *
              'lgen-ref': .lgen + .fam + .map + .ref, loadable with --lfile +


       * 'list': Single genotype-based list, up to 4 lines per variant.
              To omit

              nonmale genotypes on the Y chromosome, add the 'omit-nonmale-y' modifier.

              * 'rlist': .rlist + .fam + .map fileset, where the .rlist file is a

              genotype-based list which omits the most common genotype for  each  variant.   Also
              supports 'omit-nonmale-y'.

       * 'oxford': Oxford-format .gen + .sample.
              With the 'gen-gz' modifier, the

              .gen file is gzipped.

              *   'ped':   PLINK   1  sample-major  (.ped  +  .map),  loadable  with  --file.   *
              'compound-genotypes': Same as 'ped', except that the space between each

              pair of same-variant allele codes is removed.

              * 'structure': Structure-format.  * 'transpose': PLINK  1  variant-major  (.tped  +
              .tfam), loadable with


       * 'vcf', 'vcf-fid', 'vcf-iid': VCFv4.2.
              'vcf-fid' and 'vcf-iid' cause

              family  IDs  or within-family IDs respectively to be used for the sample IDs in the
              last header row, while 'vcf' merges both IDs and puts an underscore  between  them.
              If  the  'bgz'  modifier is added, the VCF file is block-gzipped.  The A2 allele is
              saved as the reference and normally flagged as not based on a real reference genome
              (INFO:PR).   When  it is important for reference alleles to be correct, you'll also
              want to include --a2-allele and --real-ref-alleles in your command.

              In addition, * The '12' modifier causes A1 (usually minor) alleles to be  coded  as

              and A2 alleles to be coded as '2', while '01' maps A1 -> 0 and A2 -> 1.

              * The 'tab' modifier makes the output mostly tab-delimited instead of

       mostly space-delimited.
              'tabx' and 'spacex' force all tabs and all

              spaces, respectively.

       --flip-scan <verbose>

              (alias: --flipscan) LD-based scan for case/control strand inconsistency.


              If  a --covar file is loaded, --make-bed/--make-just-fam and --recode automatically
              generate an updated version (with all filters applied).  However,  if  you  do  not
              wish  to  simultaneously generate a new genotype file, you can use --write-covar to
              just produce a pruned covariate file.

       --write-cluster <omit-unassigned>

              If clusters are specified with --within/--family, this generates a new cluster file
              (with  all  filters  applied).   The  'omit-unassigned' modifier causes unclustered
              samples to be omitted from the file; otherwise their cluster is 'NA'.



              If sets have been defined, --write-set dumps 'END'-terminated set membership  lists
              to  {output prefix}.set, while --set-table writes a variant-by-set membership table
              to {output prefix}.set.table.

       --merge [.ped filename] [.map filename]

       --merge [text fileset prefix]

       --bmerge [.bed filename] [.bim filename] [.fam filename]

       --bmerge [binary fileset prefix]

              Merge the given fileset with the initially loaded fileset, writing  the  result  to
              {output  prefix}.bed  +  .bim + .fam.  (It is no longer necessary to simultaneously
              specify --make-bed.)

       --merge-list [filename]

              Merge all filesets named in the text file with the reference fileset,  if  one  was
              specified.   (However,  this  can also be used *without* a reference; in that case,
              the newly created fileset is then treated as the  reference  by  most  other  PLINK
              operations.)   The  text  file is interpreted as follows: * If a line contains only
              one name, it is assumed to be the prefix for a

              binary fileset.

              * If a line contains exactly two names, they are assumed to be the full

              filenames for a text fileset (.ped first, then .map).

              * If a line contains exactly three names, they are assumed to be the full

              filenames for a binary fileset (.bed, then .bim, then .fam).



       --write-snplist writes a .snplist file listing the names of all variants

              which  pass  the  filters  and  inclusion  thresholds   you've   specified,   while
              --list-23-indels  writes  the  subset  with  23andMe-style  indel calls (D/I allele

       --list-duplicate-vars <require-same-ref> <ids-only> <suppress-first>

       --list-duplicate-vars writes a .dupvar file describing all groups of

              variants with matching positions and allele codes.   *  By  default,  A1/A2  allele
              assignments are ignored; use 'require-same-ref'

              to override this.

       * Normally, the report contains position and allele codes.
              To remove them

              (and produce a file directly usable with e.g. --extract/--exclude), use 'ids-only'.
              Note that this command will fail in 'ids-only' mode if any of the reported IDs  are
              not unique.

              * 'suppress-first' causes the first variant ID in each group to be omitted

              from the report.

       --freq <counts | case-control> <gz>

       --freqx <gz>

       --freq generates a basic allele frequency (or count, if the 'counts'

       modifier is present) report.
              This can be combined with --within/--family

              to  produce  a  cluster-stratified  allele  frequency/count  report instead, or the
              'case-control' modifier to report case and control allele  frequencies  separately.
              --freqx  generates  a  more  detailed  genotype count report, designed for use with

       --missing <gz>

       Generate sample- and variant-based missing data reports.
              If clusters are

       defined, the variant-based report is cluster-stratified.
              'gz' causes the

              output files to be gzipped.


              Check for association between missing calls and flanking haplotypes.

       --hardy <midp> <gz>

       Generate a Hardy-Weinberg exact test p-value report.
              (This does NOT

       simultaneously filter on the p-value any more; use --hwe for that.)

              the 'midp' modifier, the test applies the mid-p adjustment described in  Graffelman
              J, Moreno V (2013) The mid p-value in exact tests for Hardy-Weinberg Equilibrium.

       --mendel <summaries-only>

       Generate a Mendel error report.
              The 'summaries-only' modifier causes the

              .mendel file (listing every single error) to be skipped.

       --het <small-sample> <gz>


       Estimate inbreeding coefficients.
              --het reports method-of-moments

              estimates,  while  --ibc  calculates  all three values described in Yang J, Lee SH,
              Goddard ME and Visscher PM (2011)  GCTA:  A  Tool  for  Genome-wide  Complex  Trait
              Analysis.   (That  paper  also  describes  the  relationship  matrix computation we
              reimplement.)  * These functions require decent MAF estimates.  If there  are  very

              samples  in  your  immediate  fileset,  --read-freq  is practically mandatory since
              imputed MAFs are wildly inaccurate in that case.

              * They also assume the marker set is in  approximate  linkage  equilibrium.   *  By
              default, --het omits the n/(n-1) multiplier in Nei's expected

       homozygosity formula.
              The 'small-sample' modifier causes it to be

              included,  while  forcing  --het to use MAFs imputed from founders in the immediate

       --check-sex {female max F} {male min F}

       --check-sex ycount {female max F} {male min F} {female max Y obs}
              {male min Y obs}

       --check-sex y-only {female max Y obs} {male min Y obs}

       --impute-sex {female max F} {male min F}

       --impute-sex ycount {female max F} {male min F} {female max Y obs}
              {male min Y obs}

       --impute-sex y-only {female max Y obs} {male min Y obs}

       --check-sex normally compares sex assignments in the input dataset with

              those imputed from X chromosome inbreeding coefficients.  * Make sure  that  the  X
              chromosome pseudo-autosomal region has been split

              off (with e.g. --split-x) before using this.

              * You also need decent MAF estimates (so, with very few samples in your

              immediate  fileset,  use --read-freq), and your marker set should be in approximate
              linkage equilibrium.

              * By default, F estimates smaller than 0.2 yield female calls, and values

       larger than 0.8 yield male calls.
              If you pass numeric parameter(s) to

       --check-sex, the first two control these thresholds.

              There are now two modes which consider Y chromosome  data.   *  In  'ycount'  mode,
              gender is still imputed from the X chromosome, but

              female  calls  are  downgraded  to  ambiguous  whenever  more  than  0 nonmissing Y
              genotypes are present, and male calls are downgraded when fewer than 0 are present.
              (Note  that  these  are counts, not rates.)  These thresholds are controllable with
              --check-sex ycount's optional 3rd and 4th numeric parameters.

              * In 'y-only' mode, gender is imputed from nonmissing Y genotype counts.

              The male minimum threshold defaults to 1 instead of zero in this case.

       --impute-sex changes sex assignments to the imputed values, and is

       otherwise identical to --check-sex.
              It must be used with


       --fst <case-control>

              (alias: --Fst) Estimate Wright's Fst for each autosomal diploid variant  using  the
              method  introduced  in Weir BS, Cockerham CC (1984) Estimating F-statistics for the
              analysis of population  structure,  given  a  set  of  subpopulations  defined  via
              --within.  Raw and weighted global means are also reported.  * If you're interested
              in the global means, it is usually best to perform

              this calculation on a marker set in approximate linkage equilibrium.

              * If you have only two subpopulations, you can represent them with

              case/control status and use the 'case-control' modifier.

       --indep [window size]<kb> [step size (variant ct)] [VIF threshold]

       --indep-pairwise [window size]<kb> [step size (variant ct)] [r^2 threshold]

       --indep-pairphase [window size]<kb> [step size (variant ct)] [r^2 threshold]

       Generate a list of markers in approximate linkage equilibrium.
              With the

              'kb' modifier, the window size is in  kilobase  instead  of  variant  count  units.
              (Pre-'kb'   space   is   optional,   i.e.  '--indep-pairwise  500  kb  5  0.5'  and
              '--indep-pairwise 500kb 5 0.5' have the same effect.)  Note that you need to  rerun
              PLINK  using  --extract  or --exclude on the file to apply the
              list to another computation.

       --r <square | square0 | triangle | inter-chr> <gz | bin | bin4> <spaces>

              <in-phase> <d | dprime | dprime-signed> <with-freqs> <yes-really>

       --r2 <square | square0 | triangle | inter-chr> <gz | bin | bin4> <spaces>

              <in-phase> <d | dprime | dprime-signed> <with-freqs> <yes-really>

       LD statistic reports.
              --r yields raw inter-variant correlations, while

       --r2 reports their squares.
              You can request results for all pairs in

              matrix format (if you specify 'bin' or one of the shape modifiers),  all  pairs  in
              table  format  ('inter-chr'), or a limited window in table format (default).  * The
              'gz' modifier causes the output text file to be gzipped.  * 'bin' causes the output
              matrix to be written in double-precision binary

       format, while 'bin4' specifics single-precision binary.
              The matrix is

              square if no shape is explicitly specified.

              *  By  default,  text  matrices  are  tab-delimited;  'spaces'  switches  this.   *
              'in-phase' adds a column with in-phase allele pairs to table-formatted

              (This cannot be used with very long allele codes.)

              * 'dprime' adds the absolute value of Lewontin's D-prime statistic to

              table-formatted reports, and forces both r/r^2 and  D-prime  to  be  based  on  the
              maximum  likelihood  solution to the cubic equation discussed in Gaunt T, Rodriguez
              S, Day I (2007) Cubic exact solutions for  the  estimation  of  pairwise  haplotype
              frequencies.  'dprime-signed' keeps the sign, while 'd' skips division by D_{max}.

              *  'with-freqs' adds MAF columns to table-formatted reports.  * Since the resulting
              file can easily be huge, you're required to add the

              'yes-really' modifier when requesting  an  unfiltered,  non-distributed  all  pairs
              computation on more than 400k variants.

              * These computations can be subdivided with --parallel (even when the

              'square' modifier is active).

       --ld [variant ID] [variant ID] <hwe-midp>

              This  displays  haplotype  frequencies,  r^2, and D' for a single pair of variants.
              When there are multiple biologically possible solutions to the haplotype  frequency
              cubic  equation, all are displayed (instead of just the maximum likelihood solution
              identified by --r/--r2), along with HWE exact test statistics.

       --show-tags [filename]

       --show-tags all

              * If a file is specified, list all variants which tag at least one variant

       named in the file.
              (This will normally be a superset of the original

              list, since a variant is considered to tag itself here.)

              * If 'all' mode is specified, for each variant, each *other* variant which

              tags it is reported.

       --blocks <no-pheno-req> <no-small-max-span>

              Estimate haplotype blocks, via Haploview's interpretation of the  block  definition
              suggested by Gabriel S et al. (2002) The Structure of Haplotype Blocks in the Human
              Genome.  * Normally, samples with missing phenotypes are not considered by this

              computation; the 'no-pheno-req' modifier lifts this restriction.

              * Normally, size-2 blocks may not span more than 20kb, and size-3 blocks

       are limited to 30kb.
              The 'no-small-max-span' modifier removes these


       The .blocks file is valid input for PLINK 1.07's --hap command.

              the --hap... family of flags has not been reimplemented in PLINK 1.9  due  to  poor
              phasing  accuracy  relative  to  other software; for now, we recommend using BEAGLE
              instead of PLINK for case/control haplotype association  analysis.   (You  can  use
              '--recode   beagle'   to  export  data  to  BEAGLE  3.3.)   We  apologize  for  the
              inconvenience, and plan to develop variants of  the  --hap...  flags  which  handle
              pre-phased data effectively.

       --distance <square | square0 | triangle> <gz | bin | bin4> <ibs> <1-ibs>

              <allele-ct> <flat-missing>

              Write  a  lower-triangular  tab-delimited  table of (weighted) genomic distances in
              allele count units to {output prefix}.dist, and a list of the corresponding  sample
              IDs  to {output prefix}  The first row of the .dist file contains a single
              {genome 1-genome 2} distance, the second  row  has  the  {genome  1-genome  3}  and
              {genome  2-genome 3} distances in that order, etc.  * It is usually best to perform
              this calculation on a marker set in

              approximate linkage equilibrium.

              * If the 'square' or 'square0' modifier is present, a square matrix is

              written instead; 'square0' fills the upper right triangle with zeroes.

              * If the 'gz' modifier is present, a compressed .dist.gz file is written

              instead of a plain text file.

              * If the 'bin' modifier is present, a binary (square) matrix of

              double-precision floating point values, suitable for loading  from  R,  is  instead
              written  to  {output  prefix}.dist.bin.  ('bin4' specifies single-precision numbers
              instead.)  This can be combined with 'square0' if you still want  the  upper  right
              zeroed out, or 'triangle' if you don't want to pad the upper right at all.

              * If the 'ibs' modifier is present, an identity-by-state matrix is written

       to {output prefix}.mibs.
              '1-ibs' causes distances expressed as genomic

              proportions  (i.e.  1  - IBS) to be written to {output prefix}.mdist.  Combine with
              'allele-ct' if you want to generate the usual .dist file as well.

              * By default, distance rescaling in the presence of missing genotype calls

              is sensitive to allele count distributions: if variant A contributes,  on  average,
              twice as much to other pairwise distances as variant B, a missing call at variant A
              will result in twice as large of  a  missingness  correction.   To  turn  this  off
              (because  e.g.  your  missing  calls  are highly nonrandom), use the 'flat-missing'

              * The computation can be subdivided with --parallel.



              These deprecated commands are equivalent to '--distance 1-ibs flat-missing  square'
              and  '--distance  ibs flat-missing square', respectively, except that they generate
              space- instead of tab-delimited text matrices.

       --make-rel <square | square0 | triangle> <gz | bin | bin4>

              <cov | ibc2 | ibc3>

              Write a lower-triangular  variance-standardized  realized  relationship  matrix  to
              {output  prefix}.rel,  and  corresponding  IDs  to {output prefix}  * It is
              usually best to perform this calculation on a marker set in

              approximate linkage equilibrium.

              * 'square', 'square0', 'triangle', 'gz', 'bin', and 'bin4' act as they do

              on --distance.

              * The 'cov' modifier removes the variance standardization step, causing a

              covariance matrix to be calculated instead.

              * By default, the diagonal elements in the relationship matrix are based on

       --ibc's Fhat1; use the 'ibc2' or 'ibc3' modifiers to base them on Fhat2

              or Fhat3 instead.

              * The computation can be subdivided with --parallel.

       --make-grm-gz <no-gz> <cov | ibc2 | ibc3>

       --make-grm-bin <cov | ibc2 | ibc3>

       --make-grm-gz writes the relationships in GCTA's original gzipped list

              format, which describes one pair per line, while --make-grm-bin writes them in GCTA
              1.1+'s   single-precision  triangular  binary  format.   Note  that  these  formats
              explicitly report the number of valid observations  (where  neither  sample  has  a
              missing  call)  for  each  pair,  which  is  useful  input for some scripts.  These
              computations can be subdivided with --parallel.

       --rel-cutoff {val}

              (alias: --grm-cutoff) Exclude one member of each pair of samples  with  relatedness
              greater  than  the  given cutoff value (default 0.025).  If no later operation will
              cause the list of remaining samples to be written to disk, this  will  save  it  to
              {output  prefix}   Note  that  maximizing  the  remaining  sample  size  is
              equivalent to the NP-hard maximum independent set  problem,  so  we  use  a  greedy
              algorithm   instead   of   guaranteeing   optimality.    (Use  the  --make-rel  and
              --keep/--remove flags if you want to try to do better.)

       --ibs-test {permutation count}

       --groupdist {iters} {d}

              Given case/control phenotype data, these commands consider  three  subsets  of  the
              distance matrix: pairs of affected samples, affected-unaffected pairs, and pairs of
              unaffected samples.  Each of these subsets has a distribution of  pairwise  genomic
              distances;  --ibs-test  uses  permutation  to  estimate p-values re: which types of
              pairs are most similar, while --groupdist focuses on the  differences  between  the
              centers   of  these  distributions  and  estimates  standard  errors  via  delete-d

       --regress-distance {iters} {d}

              Linear regression of pairwise genomic distances on pairwise average phenotypes  and
              vice  versa,  using  delete-d jackknife for standard errors.  A scalar phenotype is
              required.  * With less than two parameters, d is  set  to  {number  of  people}^0.6

              With no parameters, 100k iterations are run.

       --regress-rel {iters} {d}

              Linear regression of pairwise genomic relationships on pairwise average phenotypes,
              and vice versa.  Defaults for iters and d are the same as for --regress-distance.

       --genome <gz> <rel-check> <full> <unbounded> <nudge>

              Generate an identity-by-descent report.  * It  is  usually  best  to  perform  this
              calculation on a marker set in

              approximate linkage equilibrium.

              * The 'rel-check' modifier excludes pairs of samples with different FIDs

              from the final report.

              *  'full'  adds  raw  pairwise  comparison  data to the report.  * The P(IBD=0/1/2)
              estimator employed by this command sometimes yields

       numbers outside the range [0,1]; by default, these are clipped.

              'unbounded' modifier turns off this clipping.

              * Then, when PI_HAT^2 < P(IBD=2), 'nudge' adjusts the final P(IBD=0/1/2)

              estimates to a theoretically possible configuration.

              * The computation can be subdivided with --parallel.

       --homozyg <group | group-verbose> <consensus-match> <extend>


       --homozyg-snp [min var count]

       --homozyg-kb [min length]

       --homozyg-density [max inverse density (kb/var)]

       --homozyg-gap [max internal gap kb length]

       --homozyg-het [max hets]

       --homozyg-window-snp [scanning window size]

       --homozyg-window-het [max hets in scanning window hit]

       --homozyg-window-missing [max missing calls in scanning window hit]

       --homozyg-window-threshold [min scanning window hit rate]

              These commands request a set of  run-of-homozygosity  reports,  and  allow  you  to
              customize  how  they  are  generated.   *  If you're satisfied with all the default
              settings described below, just

       use --homozyg with no modifiers.
              Otherwise, --homozyg lets you change a

              few binary settings: * 'group{-verbose}' adds a report on pools of overlapping runs

              (Automatically set when --homozyg-match is present.)

              * With 'group{-verbose}', 'consensus-match' causes pairwise segmental

              matches  to be called based on the variants in the pool's consensus segment, rather
              than the variants in the pairwise intersection.

              * Due to how the scanning window algorithm works, it is possible for a

       reported ROH to be adjacent to a few homozygous variants.
              The 'extend'

              modifier causes them to be included in the reported ROH if that  wouldn't  cause  a
              violation of the --homozyg-density bound.

              * By default, segment bp lengths are calculated as [end bp position] -

       [start bp position] + 1.
              Therefore, reports normally differ slightly

       from PLINK 1.07, which does not add 1 at the end.
              For testing

              purposes,  you  can  use  the  'subtract-1-from-lengths'  modifier to apply the old

              * By default, only runs of homozygosity containing at least 100 variants,

       and of total length >= 1000 kilobases, are noted.
              You can change these

              minimums with --homozyg-snp and --homozyg-kb, respectively.

              * By default, a ROH must have at least one variant per 50 kb on average;

              change this bound with --homozyg-density.

              * By default, if two consecutive variants are more than 1000 kb apart, they

              cannot be in the same ROH; change this bound with --homozyg-gap.

              * By default, a ROH can contain an unlimited number of heterozygous calls;

              you can impose a limit with --homozyg-het.

              * By default, the scanning window contains 50 variants; change this with


              * By default, a scanning window hit can contain at most 1 heterozygous

              call and 5  missing  calls;  change  these  limits  with  --homozyg-window-het  and
              --homozyg-window-missing, respectively.

              * By default, for a variant to be eligible for inclusion in a ROH, the hit

              rate  of  all scanning windows containing the variant must be at least 0.05; change
              this threshold with --homozyg-window-threshold.

       --cluster <cc> <group-avg | old-tiebreaks> <missing> <only2>

              Cluster samples using a pairwise similarity statistic (normally IBS).  *  The  'cc'
              modifier forces every cluster to have at least one case and one


              * The 'group-avg' modifier causes clusters to be joined based on average

              instead of minimum pairwise similarity.

              * The 'missing' modifier causes clustering to be based on

              identity-by-missingness  instead of identity-by-state, and writes a space-delimited
              identity-by-missingness matrix to disk.

              * The 'only2' modifier causes only a .cluster2 file (which is valid input

              for --within) to be written; otherwise 2 other files will be produced.

              * By default, IBS ties are not broken in the same manner as PLINK 1.07, so

       final cluster solutions tend to differ.
              This is generally harmless.

              However, to simplify testing, you can use the  'old-tiebreaks'  modifier  to  force
              emulation of the old algorithm.

       --pca {count} <header> <tabs> <var-wts>

              Calculates      a      variance-standardized      relationship      matrix     (use
              --make-rel/--make-grm-gz/--make-grm-bin to  dump  it),  and  extracts  the  top  20
              principal components.  * It is usually best to perform this calculation on a marker
              set in

              approximate linkage equilibrium.

              * You can change the number of PCs by passing a numeric parameter.  * The  'header'
              modifier adds a header line to the .eigenvec output file.

              (For  compatibility  with  the GCTA flag of the same name, the default is no header

              * The 'tabs' modifier causes the .eigenvec file(s)  to  be  tab-delimited.   *  The
              'var-wts' modifier requests an additional .eigenvec.var file with PCs

              expressed as variant weights instead of sample weights.

       --neighbour [n1] [n2]

              (alias:  --neighbor)  Report  IBS  distances  from  each  sample  to their n1th- to
              n2th-nearest neighbors, associated Z-scores, and the identities of those neighbors.
              Useful for outlier detection.

       --assoc <perm | mperm=[value]> <perm-count> <fisher | fisher-midp> <counts>


       --assoc <perm | mperm=[value]> <perm-count> <qt-means> <lin> <set-test>

       --model <perm | mperm=[value]> <perm-count>

              <fisher | fisher-midp | trend-only> <set-test> <dom | rec | gen | trend>

              Basic  association  analysis  report.   Given  a  case/control  phenotype,  --assoc
              performs a 1df chi-square allelic test, while --model performs  4  other  tests  as
              well  (1df  dominant  gene  action,  1df  recessive  gene  action,  2df  genotypic,
              Cochran-Armitage trend).  * With 'fisher'/'fisher-midp',  Fisher's  exact  test  is
              used to generate

              'fisher-midp' also applies Lancaster's mid-p adjustment.

              *  'perm'  causes  an adaptive permutation test to be performed.  * 'mperm=[value]'
              causes a max(T) permutation test with the specified

              number of replications to be performed.

              * 'perm-count' causes the permutation test report to include counts instead

              of frequencies.

              * 'counts' causes --assoc to  report  allele  counts  instead  of  frequencies.   *
              'set-test' tests the significance of variant sets.  Requires permutation;

              can be customized with --set-p/--set-r2/--set-max.

              * 'dom', 'rec', 'gen', and 'trend' force the corresponding test to be used

       as the basis for --model permutation.
              (By default, the most significant

              result among the allelic, dominant, and recessive tests is used.)

              *  'trend-only'  causes  only the trend test to be performed.  Given a quantitative
              phenotype, --assoc normally performs a Wald test.  * In this case,  the  'qt-means'
              modifier causes trait means and standard

              deviations stratified by genotype to be reported as well.

              * 'lin' causes the Lin statistic to be computed, and makes it the basis for

              multiple-testing corrections and permutation tests.

              Several  other  flags  (most  notably,  --aperm)  can  be  used  to  customize  the
              permutation test.

       --mh <perm | mperm=[value]> <perm-count> <set-test>

              (alias: --cmh)

       --bd <perm | perm-bd | mperm=[value]> <perm-count> <set-test>



              Given a  case/control  phenotype  and  a  set  of  clusters,  --mh  computes  2x2xK
              Cochran-Mantel-Haenszel  statistics  for each variant, while --bd also performs the
              Breslow-Day test for odds ratio homogeneity.  Permutation and variant  set  testing
              based on the CMH (default) or Breslow-Day (when 'perm-bd' is present) statistic are
              supported.  The following similar analyses are also available: *  --mh2  swaps  the
              roles of case/control status and cluster membership,

              performing a phenotype-stratified IxJxK Cochran-Mantel-Haenszel test on association
              between cluster assignments and genotypes.

              * --homog executes an alternative to the Breslow-Day test, based on

              partitioning of the chi-square statistic.

       --gxe {covariate index}

              Given both a quantitative  phenotype  and  a  case/control  covariate  loaded  with
              --covar defining two groups, --gxe compares the regression coefficient derived from
              considering only members of one group to the regression  coefficient  derived  from
              considering  only  members  of  the  other.  By default, the first covariate in the
              --covar file defines the groups; use e.g. '--gxe 3'  to  base  them  on  the  third
              covariate instead.

       --linear <perm | mperm=[value]> <perm-count> <set-test>

              <genotypic  | hethom | dominant | recessive | no-snp> <hide-covar> <sex | no-x-sex>
              <interaction> <beta> <standard-beta> <intercept>

       --logistic <perm | mperm=[value]> <perm-count> <set-test>

              <genotypic | hethom | dominant | recessive | no-snp> <hide-covar> <sex |  no-x-sex>
              <interaction> <beta> <intercept>

              Multi-covariate  association  analysis on a quantitative (--linear) or case/control
              (--logistic) phenotype.  Normally used with --covar.  * 'perm' normally  causes  an
              adaptive permutation test to be performed on

              the main effect, while 'mperm=[value]' starts a max(T) permutation test.

              * 'perm-count' causes the permutation test report to include counts instead

              of frequencies.

       * 'set-test' tests the significance of variant sets.
              Requires permutation;

              can be customized with --set-p/--set-r2/--set-max.

              * The 'genotypic' modifier adds an additive effect/dominance deviation 2df

              joint  test  (0/1/2  and  0/1/0 coding), while 'hethom' uses 0/0/1 and 0/1/0 coding
              instead.  If permutation is also requested, these modifiers cause permutation to be
              based on the joint test.

              * 'dominant' and 'recessive' specify a model assuming full dominance or

              recessiveness, respectively, for the A1 allele.

              * 'no-snp' causes regression to be performed only on the phenotype and the

       covariates, without reference to genomic data.
              If permutation is also

              requested, results are reported for all covariates.

              * 'hide-covar' removes covariate-specific lines from the report.  * By default, sex
              (male = 1, female = 0) is automatically added as a

       covariate on X chromosome variants, and nowhere else.
              The 'sex' modifier

              causes it to be added everywhere, while 'no-x-sex' excludes it.

       * 'interaction' adds genotype x covariate interactions to the model.

              cannot be used with  the  usual  permutation  tests;  use  --tests  to  define  the
              permutation test statistic instead.

              *  'intercept' causes intercepts to be included in the main report.  * For logistic
              regressions, the 'beta' modifier causes regression

              coefficients instead of odds ratios to be reported.

              * With --linear, the 'standard-beta' modifier standardizes the phenotype

              and all predictors to zero mean and unit variance before regression.

       --dosage [allele dosage file] <noheader> <skip0=[i]> <skip1=[j]> <skip2=[k]>

              <dose1> <format=[m]> <Zout> <occur | standard-beta> <sex> <case-control-freqs>

       --dosage [list file] list <sepheader | noheader> <skip0=[i]> <skip1=[j]>

              <skip2=[k]>   <dose1>   <format=[m]>   <Zout>   <occur   |   standard-beta>   <sex>


              Process (possibly gzipped) text files with variant-major allelic dosage data.  This
              cannot be used with a regular input fileset; instead, you  must  *only*  specify  a
              .fam  and  possibly a .map file, and you can't specify any other commands.  * PLINK
              2.0 will have first-class support for genotype probabilities.  An

              equivalent data import flag will be provided then, and --dosage will be retired.

              * By default, --dosage assumes that only one allelic dosage file should be

              To specify multiple files,

       1. create a master list with one entry per line.
              There are normally two

              supported formats for this list: just a filename per line, or variant batch numbers
              in the first column and filenames in the second.

              2.  Provide  the  name  of  that  list as the first --dosage parameter.  3. Add the
              'list' modifier.

              * By default, --dosage assumes the allelic dosage file(s) contain a header

              line, which has 'SNP' in column i+1, 'A1' in column i+j+2, 'A2'  in  column  i+j+3,
              and  sample  FID/IIDs  starting from column i+j+k+4.  (i/j/k are normally zero, but
              can be changed with 'skip0', 'skip1', and 'skip2' respectively.)  If such a  header
              line  is not present, * when all samples appear in the same order as they do in the
              .fam file,

              you can use the 'noheader' modifier.

              * Otherwise, use the 'sepheader' modifier, and append sample ID filenames

              to your 'list' file entries.

              * The 'format' modifier lets you specify the number of values used to

       represent each dosage.
              'format=1' normally indicates a single 0..2 A1

       expected count; 'dose1' modifies this to a 0..1 frequency.

              (the default) indicates a 0..1 homozygous A1 likelihood  followed  by  a  0..1  het
              likelihood, while 'format=3' indicates 0..1 hom A1, 0..1 het, 0..1 hom A2.

              * 'Zout' causes the output file to be gzipped.  * Normally, an association analysis
              is performed.  'standard-beta' and

              'sex'   behave   as   they    are    supposed    to    with    --linear/--logistic.
              'case-control-freqs'  causes  case  and  control  allele frequencies to be reported

              * There are three alternate modes which cause the association analysis to

              be  skipped.   *  'occur'  requests  a  simple  variant   occurrence   report.    *
              --write-dosage causes a simple merged file matching the 'format'

              specification (not including 'dose1') to be generated.

              * --score applies a linear scoring system to the dosages.

       --lasso [h2 estimate] {min lambda} <report-zeroes>

       Estimate variant effect sizes via LASSO regression.
              You must provide an

              additive  heritability estimate to calibrate the regression.  Note that this method
              may require a very large sample size (e.g. hundreds of thousands) to  be  effective
              on complex polygenic traits.

       --test-missing <perm | mperm=[value]> <perm-count> <midp>

              Check  for  association between missingness and case/control status, using Fisher's
              exact test.  The 'midp' modifier causes Lancaster's mid-p adjustment to be applied.

       --make-perm-pheno [ct]

              Generate phenotype permutations  and  write  them  to  disk,  without  invoking  an
              association test.

       --tdt <exact | exact-midp | poo> <perm | mperm=[value]> <perm-count>

              <parentdt1 | parentdt2 | pat | mat> <set-test>

              Report  transmission  disequilibrium test statistics, given case/control phenotypes
              and pedigree information.  * A Mendel error check  is  performed  before  the  main
              tests; offending

              genotypes are treated as missing by this analysis.

              * By default, the basic TDT p-value is based on a chi-square test unless

              you request the exact binomial test with 'exact' or 'exact-midp'.

              * 'perm'/'mperm=[value]' requests a family-based adaptive or max(T)

       permutation test.
              By default, the permutation test statistic is the

              basic   TDT  p-value;  'parentdt1'/'parentdt2'  cause  parenTDT  or  combined  test
              p-values, respectively, to be considered instead.

       * 'set-test' tests the significance of variant sets.
              This cannot be used

              with exact tests for now.

              The 'poo' modifier causes a parent-of-origin analysis to be performed instead, with
              transmissions   from  heterozygous  fathers  and  heterozygous  mothers  considered
              separately.  * The parent-of-origin  analysis  does  not  currently  support  exact
              tests.  * By default, the permutation test statistic is the absolute

              parent-of-origin   test  Z  score;  'pat'/'mat'  cause  paternal  or  maternal  TDT
              chi-square statistics, respectively, to be considered instead.

       --qfam <perm | mperm=[value]> <perm-count> <emp-se>

       --qfam-parents <perm | mperm=[value]> <perm-count> <emp-se>

       --qfam-between <perm | mperm=[value]> <perm-count> <emp-se>

       --qfam-total <perm | mperm=[value]> <perm-count> <emp-se>

              QFAM family-based association test for quantitative traits.  * A Mendel error check
              is performed before the main tests; offending

              genotypes are treated as missing by this analysis.

       * This procedure requires permutation.
              'perm' and 'perm-count' have the

       usual meanings.
              However, 'mperm=[value]' just specifies a fixed number

              of permutations; the method does not support a proper max(T) test.

              * The 'emp-se' modifier adds BETA and EMP_SE (empirical standard error for

              beta) fields to the .perm output file.

       --annotate [PLINK report] <attrib=[file]> <ranges=[file]> <filter=[file]>

              <snps=[file]> <NA | prune> <block> <subset=[file]> <minimal> <distance>

       Add annotations to a variant-based PLINK report.
              This requires an

              annotation source: * 'attrib=[file]' specifies a (possibly gzipped) attribute file.
              * 'ranges=[file]' specifies a gene/range list file.   (Both  source  types  can  be
              specified   simultaneously.)    The   following   options  are  also  supported:  *
              'filter=[file]' causes only variants within one of the ranges in the file

              to be included in the new report.

              * 'snps=[file]' causes only variants named in the file to be included in

              the new report.

              * The 'NA' modifier causes unannotated variants to have 'NA' instead of '.'

              in the new  report's  ANNOT  column,  while  the  'prune'  modifier  excludes  them

              * The 'block' modifier replaces the single ANNOT column with a 0/1-coded

              column for each possible annotation.

              * With 'ranges',

              * 'subset=[file]' causes only intervals named in the subset file to be

              loaded from the ranges file.

              * interval annotations normally come with a parenthesized signed distance

              to  the interval boundary (0 if the variant is located inside the interval; this is
              always true without --border).  They can be excluded with the 'minimal' modifier.

              * the 'distance' modifier adds 'DIST' and 'SGN' columns describing signed

              distance to the nearest interval.

              * When --pfilter is present, high p-values are filtered out.

       --clump [PLINK report filename(s)...]

              Process association analysis report(s) with 'SNP' and p-value  columns,  organizing
              results  by  LD-based  clumps.   Multiple  filenames  can be separated by spaces or

       --gene-report [PLINK report] [gene range file]

              Generate a gene-based report from a variant-based  report.   *  When  --pfilter  is
              present,  high  p-values  are  filtered out.  * When --extract (without 'range') is
              present, only variants named in the

       --extract file are considered.

       --meta-analysis [PLINK report filenames...]

       --meta-analysis [PLINK report filenames...] + <logscale | qt>

              <no-map | no-allele> <study> <report-all> <weighted-z>

              Perform a meta-analysis on  several  variant-based  reports  with  'SNP'  and  'SE'
              fields.  * Normally, an 'OR' odds ratio field must also be present in each input

              With 'logscale', 'BETA' log-odds values/regression coefficients

              are  expected  instead,  but  the  generated  report  will still contain odds ratio
              estimates.  With 'qt', both input and output values are regression betas.

       * 'CHR', 'BP', and 'A1' fields are also normally required.
              'no-map' causes

              them to all be ignored, while 'no-allele' causes just 'A1' to be ignored.

              * If 'A2' fields are present, and neither 'no-map' nor 'no-allele' was

       specified, A1/A2 allele flips are handled properly.
              Otherwise, A1

              mismatches are thrown out.

              * 'study' causes study-specific effect estimates to be collated in the

              meta-analysis report.

              * 'report-all' causes variants present in only a single input file to be

              included in the meta-analysis report.

              * 'weighted-z' requests weighted Z-score-based p-values (as computed by the

              Abecasis Lab's METAL software) in addition  to  the  usual  inverse  variance-based
              analysis.  This requires P and effective sample size fields.

              * When --extract (without 'range') is present, only variants named in the

       --extract file are considered.

              * Unless 'no-map' is specified, chromosome filters are also respected.

       --fast-epistasis <boost | joint-effects | no-ueki> <case-only>

              <set-by-set | set-by-all> <nop>

       --epistasis <set-by-set | set-by-all>

       Scan for epistatic interactions.
              --fast-epistasis inspects 3x3 joint

              genotype   count   tables  and  only  applies  to  case/control  phenotypes,  while
              --epistasis performs linear or logistic regression.  * By default, --fast-epistasis
              uses the PLINK 1.07 allele-based test.  Two

              newer tests are now supported: 'boost' invokes the likelihood ratio test introduced
              by Wan X et al. (2010) BOOST: A Fast Approach to Detecting  Gene-Gene  Interactions
              in  Genome-wide  Case-Control  Studies,  while  'joint-effects'  applies  the joint
              effects test introduced in Ueki  M,  Cordell  HJ  (2012)  Improved  statistics  for
              genome-wide interaction analysis.

              * The original --fast-epistasis test normally applies the variance and

       empty cell corrections suggested by Ueki and Cordell's paper.
              To disable

              them, use the 'no-ueki' modifier.

              *  'case-only'  requests a case-only instead of a case/control test.  * By default,
              all pairs of variants across the entire genome are tested.

              To just test pairs of variants within a single set, add the  'set-by-set'  modifier
              and  load  exactly one set with --set/--make-set; with exactly two sets loaded, all
              variants in one set are tested against all variants  in  the  other.   'set-by-all'
              tests all variants in one set against the entire genome instead.

              *  'nop'  strips  p-values  from  the  main  report.   *  These computations can be
              subdivided with --parallel; however...

       --epistasis-summary-merge [common file prefix] [ct]

              When a --{fast-}epistasis job is subdivided with --parallel, the main report can be
              assembled  at  the  end  by  applying  Unix  'cat'  in  the  usual  manner, but the
              .summary.1,   .summary.2,   ...   files   may   require   a   specialized    merge.
              --epistasis-summary-merge takes care of the latter.

       --twolocus [variant ID] [variant ID]

              Two-locus joint genotype count report.

       --score [filename] {i} {j} {k} <header> <sum | no-sum>

              <no-mean-imputation | center> <include-cnt> <double-dosage>

              Apply  a linear scoring system to each sample.  The input file should have one line
              per scored variant.  Variant IDs are read from column #i,  allele  codes  are  read
              from  column  #j,  and  scores  are  read  from column #k, where i defaults to 1, j
              defaults to i+1, and k defaults to j+1.  * The 'header' modifier causes  the  first
              nonempty line of the input file to

              be ignored; otherwise, --score assumes there is no header line.

              * By default, final scores are averages of the valid per-variant scores.

       The 'sum' modifier causes sums to be reported instead.
              (This cannot be

       used with 'no-mean-imputation'.
              And for backward compatibility, 'sum' is

              automatically on with dosage data unless 'no-sum' is specified.)

              * By default, copies of the unnamed allele contribute zero to score, while

              missing genotypes contribute an amount proportional to the loaded (via --read-freq)
              or imputed allele frequency.  To throw out missing observations instead (decreasing
              the   denominator   in   the   final   average   when   this   happens),   use  the
              'no-mean-imputation' modifier.

              * Alternatively, you can use the 'center' modifier to shift all scores to

              mean zero.

       * This command can be used with dosage data.
              By default, the 'CNT' column

              is omitted from the output file in this case; use 'include-cnt' to keep it.   Also,
              note  that  scores  are multiplied by 0..1 dosages, not 0..2 diploid allele counts,
              unless the 'double-dosage' modifier is present.

       --R [R script file] <debug>

              Connect to a Rserve (preferably version  1.7  or  later)  background  process,  and
              execute  the  Rplink  function  defined  in  the  input  file.  (Unless the 'debug'
              modifier is present; in that case, the R commands that PLINK would  have  tried  to
              execute are logged to a file.)

       --write-var-ranges [block ct]

       Divide the set of variants into equal-size blocks.
              (Can be used with

       --snps to split a job across multiple machines.)

       The   following  other  flags  are  supported.   (Order  of  operations  is  described  at .)

       --script [fname] : Include command-line options from file.

       --rerun {log}
              : Rerun commands in log (default 'plink.log').

              : Display only version number before exiting.

              : Suppress output to console.

              : Reserved for interoperation with gPLINK.

       --missing-genotype [char] : Set missing genotype code (normally '0').

              : Set both FIDs and IIDs to the VCF/BCF sample ID.

       --const-fid {ID}
              : Set all FIDs to the given constant (default '0').

       --id-delim {d}
              : Parse sample IDs as [FID][d][IID] (default delim '_').

       --vcf-idspace-to [c] : Convert spaces in sample IDs to the given character.

       --biallelic-only <strict> <list> : Skip VCF variants with 2+ alt. alleles.

       --vcf-min-qual [val]
              : Skip VCF variants with low/missing QUAL.

       --vcf-filter {exception(s)...}
              : Skip variants which have FILTER failures.

              : Skip variants with no GT field.

       --vcf-min-gq [val]
              : No-call a genotype when GQ is below the given threshold.

       --vcf-min-gp [val]
              : No-call a genotype when 0-1 scaled GP is below the given threshold.

       --vcf-half-call [m]
              : Specify how '0/.' and similar VCF GT values should  be  handled.   The  following
              four modes are supported: * 'error'/'e' (default) errors out and reports line #.  *
              'haploid'/'h' treats them  as  haploid  calls.   *  'missing'/'m'  treats  them  as
              missing.  * 'reference'/'r' treats the missing value as 0.

       --oxford-single-chr [chr nm] : Specify single-chromosome .gen file with
              ignorable first column.

       --oxford-pheno-name [col nm] : Import named phenotype from the .sample file.

       --hard-call-threshold [val]
              : When an Oxford-format fileset is loaded, calls

       --hard-call-threshold random
              with  uncertainty  level greater than 0.1 are normally treated as missing.  You can
              adjust this threshold by providing a numeric parameter, or randomize all calls with

       --missing-code {string list} : Comma-delimited list of missing phenotype

       (alias: --missing_code)
              values for Oxford-format filesets (def. 'NA').

       --simulate-ncases [num]
              : Set --simulate case count (default 1000).

       --simulate-ncontrols [n]
              : Set --simulate control count (default 1000).

       --simulate-prevalence [p] : Set --simulate disease prevalence (default 0.01).

       --simulate-n [num]
              : Set --simulate-qt sample count (default 1000).

       --simulate-label [prefix] : Set --simulate{-qt} FID/IID name prefix.

       --simulate-missing [freq] : Set --simulate{-qt} missing genotype frequency.

       --allow-extra-chr <0>
              : Permit unrecognized chromosome codes.  The '0'

       (alias: --aec)
              modifier causes them to be treated as if they had been set to zero.

       --chr-set [autosome ct] <no-x> <no-y> <no-xy> <no-mt> :

       Specify a nonhuman chromosome set.
              The first parameter sets the number of

              diploid  autosome  pairs  if  positive,  or haploid chromosomes if negative.  Given
              diploid autosomes, the remaining  modifiers  indicate  the  absence  of  the  named
              non-autosomal chromosomes.

       --cow/--dog/--horse/--mouse/--rice/--sheep : Shortcuts for those species.

       --autosome-num [value]
              : Alias for '--chr-set [value] no-y no-xy no-mt'.

       --cm-map [fname pattern] {chr} : Use SHAPEIT-format recombination maps to set
              centimorgan  positions.   To process more than one chromosome, include a '@' in the
              first     parameter     where     the     chrom.     number      belongs,      e.g.

              : Zero out centimorgan positions.

       --pheno [fname]
              :  Load  phenotype data from the specified file, instead of using the values in the
              main input fileset.

              : For basic association tests, loop through all phenotypes in --pheno file.

       --mpheno [n]
              : Load phenotype from column (n+2) in --pheno file.

       --pheno-name [c] : If --pheno file has a header row, use column with the
              given name.

              : When the main input fileset contains an phenotype value for  a  sample,  but  the
              --pheno  file does not, use the original value instead of treating the phenotype as

       --missing-phenotype [v] : Set missing phenotype value (normally -9).

       --1    : Expect case/control phenotypes to be coded as 0 = control, 1 = case,  instead  of
              the  usual  0  = missing, 1 = control, 2 = case.  This also forces phenotypes to be
              interpreted as case/ctrl.

       --make-pheno [fn] [val] : Define a new case/control phenotype.
              If the val parameter is '*', all samples listed in the given file  are  cases,  and
              everyone  else  is  a  control.   (Note  that,  in  some shells, it is necessary to
              surround the * with quotes.)  Otherwise, all samples with third column entry  equal
              to  the  val  parameter  are cases, and all other samples mentioned in the file are

       --tail-pheno [Lt] {Hbt} : Downcode a scalar phenotype to a case/control
              phenotype.  All samples with phenotype values greater than Hbt are cases,  and  all
              with  values  less  than or equal to Lt are controls.  If Hbt is unspecified, it is
              equal to Lt; otherwise, in-between phenotype values are set to missing.

       --covar [filename] <keep-pheno-on-missing-cov> : Specify covariate file.

       --covar-name [...]
              : Specify covariate(s) in --covar file  by  name.   Separate  multiple  names  with
              spaces or commas, and use dashes to designate ranges.

       --covar-number [...]
              : Specify covariate(s) in --covar file by index.

              : Exclude constant covariates.

       --within [f] <keep-NA>
              : Specify initial cluster assignments.

       --mwithin [n]
              : Load cluster assignments from column n+2.

              : Create a cluster for each family ID.

       --loop-assoc [f] <keep-NA>
              :  Run  specified  case/control  association  commands once for each cluster in the
              file, using cluster membership as the phenotype.

       --set [filename]
              : Load sets from a .set file.

       --set-names [name(s)...]
              : Load only sets named on the command line.  Use spaces to separate multiple names.

       --subset [filename]
              : Load only sets named in the given text file.

       --set-collapse-all [set name] : Merge all sets.

              : Invert all sets.  (Names gain 'C_' prefixes.)

       --make-set-complement-all [s] : --set-collapse-all + inversion.

       --make-set [filename]
              : Define sets from a list of named bp ranges.

       --make-set-border [kbs]
              : Stretch regions in --make-set file.

              : Define sets from groups instead of sets in --make-set file.

       --keep [filename]
              : Exclude all samples not named in the file.

       --remove [filename]
              : Exclude all samples named in the file.

       --keep-fam [filename] : Exclude all families not named in the file.

       --remove-fam [fname]
              : Exclude all families named in the file.

       --extract <range> [f] : Exclude all variants not named in the file.

       --exclude <range> [f] : Exclude all variants named in the file.

       --keep-clusters [filename]
              : These can be used individually or in

       --keep-cluster-names [name(s)...]
              combination to define a list of clusters to keep; all samples not in a  cluster  in
              that   list   are  then  excluded.   Use  spaces  to  separate  cluster  names  for

       --remove-clusters [filename]
              : Exclude all clusters named in the file.

       --remove-cluster-names [name(s)...] : Exclude the named clusters.

       --gene [sets...] : Exclude variants not in a set named on the command line.
              (Separate multiple set names with spaces.)

              : Exclude variants which aren't a member of any set.  (PLINK 1.07 automatically did
              this under some circumstances.)

       --attrib [f] {att lst} : Given a file assigning attributes to variants, and a

       --attrib-indiv [f] {a}
              comma-delimited   list   (with   no   whitespace)   of   attribute   names,  remove
              variants/samples which are either missing from the file or don't have  any  of  the
              listed  attributes.   If some attribute names in the list are preceded by '-', they
              are treated as 'negative match conditions' instead:  variants  with  at  least  one
              negative  match attribute are removed.  The first character in the list cannot be a
              '-', due to how command-line parsing works; add a comma  in  front  to  get  around

       --chr [chrs...]
              :  Exclude  all  variants not on the given chromosome(s).  Valid choices for humans
              are 0 (unplaced), 1-22, X, Y, XY,  and  MT.   Separate  multiple  chromosomes  with
              spaces  and/or  commas,  and  use a dash (no adjacent spaces permitted) to denote a
              range, e.g. '--chr 1-4, 22, xy'.

       --not-chr [...]
              : Reverse of --chr (exclude variants on listed chromosomes).

              : Exclude all non-autosomal variants.

              : Exclude  all  non-autosomal  variants,  except  those  with  chromosome  code  XY
              (pseudo-autosomal region of X).

       --snps-only <just-acgt> : Exclude non-SNP variants.
              By default, SNP = both allele codes are single-character; 'just-acgt' restricts SNP
              codes to {A,C,G,T,a,c,g,t,[missing]}.

       --from [var ID]
              : Use ID(s) to specify a variant range to load.  When used

       --to   [var ID]    together, both variants must be on the same chromosome.

       --snp  [var ID]  : Specify a single variant to load.

       --exclude-snp [] : Specify a single variant to exclude.

              [kbs]  : With --snp or --exclude-snp, loads/excludes all variants within  half  the
              specified kb distance of the named one.

       --from-bp [pos]
              : Use physical position(s) to define a variant range to

              [pos]    load.  --from-kb/--to-kb/--from-mb/--to-mb allow decimal

       --from-kb [pos]
              values.  You must also specify a single chromosome (using

              [pos]    e.g. --chr) when using these flags.

       --from-mb [pos]


       --snps [var IDs...]
              : Use IDs to specify variant range(s) to load or

       --exclude-snps [...]
              exclude.  E.g. '--snps rs1111-rs2222, rs3333, rs4444'.

       --thin [p]
              : Randomly remove variants, retaining each with prob. p.

       --thin-count [n] : Randomly remove variants until n of them remain.

       --bp-space [bps] : Remove variants so that each pair is no closer than the
              given bp distance.  (Equivalent to VCFtools --thin.)

       --thin-indiv [p]
              : Randomly remove samples, retaining with prob. p.

       --thin-indiv-count [n]
              : Randomly remove samples until n of them remain.

       --filter [f] [val(s)...] : Exclude all samples without a 3rd column entry in
              the given file matching one of the given space-separated value(s).

       --mfilter [n]
              : Match against (n+2)th column instead.

       --geno {val}
              :  Exclude variants with missing call frequencies greater than a threshold (default
              0.1).  (Note that the default threshold  is  only  applied  if  --geno  is  invoked
              without  a  parameter;  when  --geno  is  not  invoked, no per-variant missing call
              frequency ceiling is enforced at all.  Other inclusion/exclusion default thresholds
              work the same way.)

       --mind {val}
              :  Exclude  samples with missing call frequencies greater than a threshold (default

       --oblig-missing [f1] [f2] : Specify blocks of missing genotype calls for
              --geno/--mind to ignore.  The first file should  have  variant  IDs  in  the  first
              column  and  block IDs in the second, while the second file should have FIDs in the
              first column, IIDs in the second, and block IDs in the third.

              : Remove samples with missing phenotypes.

       --maf {freq}
              : Exclude variants with minor allele frequency  lower  than  a  threshold  (default

       --max-maf [freq]
              : Exclude variants with MAF greater than the threshold.

       --mac [ct]
              : Exclude variants with minor allele count lower than the

       (alias: --min-ac)
              given threshold.

       --max-mac [ct]
              : Exclude variants with minor allele count greater than

       (alias: --max-ac)
              the given threshold.

              :  Rule  of succession MAF estimation (used in EIGENSOFT).  Given j observations of
              one allele and k >= j observations of the other, infer a MAF of  (j+1)  /  (j+k+2),
              rather than the default j / (j+k).

       --read-freq [fn] : Estimate MAFs and heterozygote frequencies from the given
              --freq{x} report, instead of the input fileset.

       --hwe [p] <midp> <include-nonctrl> : Exclude variants with Hardy-Weinberg
              equilibrium exact test p-values below a threshold.

       --me [t] [v] <var-first> : Filter out trios and variants with Mendel error
              rates exceeding the given thresholds.

       --me-exclude-one {ratio} : Make --me exclude only one sample per trio.

       --qual-scores [f] {qcol} {IDcol} {skip} : Filter out variants with
              out-of-range quality scores.  Default range is now [0, \infty ).

       --qual-threshold [min qual score]
              : Set --qual-scores range floor.

       --qual-max-threshold [max qual score]
              : Set --qual-scores range ceiling.

              :  Do  not  treat  ambiguous-sex  samples  as having missing phenotypes in analysis
              commands.  (Automatic /w --no-sex.)

              :       Force       ambiguous-sex       phenotypes       to       missing        on

              : Include only cases in the current analysis.

              : Include only controls.

              : Include only males.

              : Include only females.

              : Include only founders.

       --filter-nonfounders : Include only nonfounders.

              : Include nonfounders in allele freq/HWE calculations.

       --make-founders <require-2-missing> <first> : Clear parental IDs for those
              with 1+ missing parent(s).

       --recode-allele [fn] : With --recode A/A-transpose/AD, count alleles named in
              the file (otherwise A1 alleles are always counted).

       --output-chr [MT code] : Set chromosome coding scheme in output files by
              providing  the  desired  human  mitochondrial  code.  (Options are '26', 'M', 'MT',
              '0M', 'chr26', 'chrM', and 'chrMT'.)

       --output-missing-genotype [ch] : Set the code used to represent missing
              genotypes in output files (normally the --missing-genotype value).

       --output-missing-phenotype [s] : Set the string used to represent missing
              phenotypes in output files (normally the --missing-phenotype value).

       --zero-cluster [f] : In combination with --within/--family, set blocks of
              genotype calls to missing.  The input file should have variant  IDs  in  the  first
              column and cluster IDs in the second.  This must now be used with --make-bed and no
              other output commands.

              : Cause --make-bed and --recode to set heterozygous haploid genotypes to missing.

       --set-mixed-mt-missing : Cause --make-bed and --recode to set mixed MT
              genotypes to missing.

       --split-x [bp1] [bp2] <no-fail> : Changes chromosome code of all X chromosome

       --split-x [build] <no-fail>
              variants with bp position <= bp1 or >= bp2 to XY.  The following  build  codes  are
              supported  as shorthand: * 'b36'/'hg18' = NCBI 36, 2709521/154584237 * 'b37'/'hg19'
              = GRCh37, 2699520/154931044 * 'b38'/'hg38' = GRCh38, 2781479/155701383 By  default,
              PLINK  errors  out  when  no variants would be affected by --split-x; the 'no-fail'
              modifier (useful in scripts) overrides this.

       --merge-x <no-fail>
              : Merge XY chromosome back with X.

              : Cause --make-bed to set Mendel errors to missing.

       --fill-missing-a2 : Cause --make-bed to replace all missing calls with
              homozygous A2 calls.

       --set-missing-var-ids [t]
              : Given a template string with a '@' where the chromosome code should  go  and  '#'
              where     the     bp     coordinate    belongs,    --set-missing-var-ids    assigns
              chromosome-and-bp-based IDs to unnamed variants.  You may also use '$1' and '$2' to
              refer  to  allele  names in the template string, and in fact this becomes essential
              when multiple variants share the same coordinate.

       --new-id-max-allele-len [n] : Specify maximum number of leading characters
              from allele names to include in new variant IDs (default 23).

       --missing-var-code [string] : Change unnamed variant code (default '.').

              [f] {chrcol} {IDcol}  {skip} : Update variant chromosome codes.

              [f] {cmcol}  {IDcol}  {skip} : Update centimorgan positions.

              [f] {bpcol}  {IDcol}  {skip} : Update variant bp positions.

       --update-name [f] {newcol} {oldcol} {skip} : Update variant IDs.

       --update-alleles [fname] : Update variant allele codes.

       --allele1234 <multichar> : Interpret/recode A/C/G/T alleles as 1/2/3/4.
              With 'multichar', converts all A/C/G/Ts in allele names to 1/2/3/4s.

       --alleleACGT <multichar> : Reverse of --allele1234.

       --update-ids [f]
              : Update sample IDs.

       --update-parents [f] : Update parental IDs.

       --update-sex [f] {n} : Update sexes.
              Sex (1 or M = male, 2 or F = female,  0  =  missing)  is  loaded  from  column  n+2
              (default n is 1).

       --flip [filename]
              : Flip alleles (A<->T, C<->G) for SNP IDs in the file.

       --flip-subset [fn]
              : Only apply --flip to samples in --flip-subset file.

       --flip-scan-window [ct+1] : Set --flip-scan max variant ct dist. (def. 10).

       --flip-scan-window-kb [x] : Set --flip-scan max kb distance (default 1000).

       --flip-scan-threshold [x] : Set --flip-scan min correlation (default 0.5).

              : Keep the allele order defined in the .bim file,

              instead of forcing A2 to be the major allele.  --real-ref-alleles also removes 'PR'
              from the INFO values emitted by --recode vcf{-fid/-iid}.

       --a1-allele [f] {a1col} {IDcol} {skip} : Force alleles in the file to A1.

       --a2-allele [filename] {a2col} {IDcol} {skip} :

       Force alleles in the file to A2.
              ("--a2-allele [VCF filename] 4 3 '#'",

              which scrapes reference allele assignments from a VCF file, is especially useful.)

       --indiv-sort [m] {f} : Specify FID/IID sort order.
              The following four modes are supported: * 'none'/'0' keeps  samples  in  the  order
              they were

              Default for non-merge operations.

       * 'natural'/'n' invokes 'natural sort', e.g.
              'id2' < 'ID3' < 'id10'.  Default when merging.

       * 'ascii'/'a' sorts in ASCII order, e.g.
              'ID3' < 'id10' < 'id2'.

       * 'file'/'f' uses the order in the given file (named
              in the second parameter).

       For now, only --merge/--bmerge/--merge-list and
              --make-bed/--make-just-fam respect this flag.

       --with-phenotype <no-parents> <no-sex | female-2> : Include more sample info
              in new .cov file.

       --dummy-coding {N} <no-round> : Split categorical variables (n categories,
              2 < n <= N, default N is 49) into n-1 binary dummy variables when writing covariate

       --merge-mode [n]
              : Adjust --{b}merge/--merge-list behavior based on a numeric code.  1  (default)  =
              ignore missing calls, otherwise difference

       -> missing
              2  =  only overwrite originally missing calls 3 = only overwrite when nonmissing in
              new file 4/5 = never overwrite and always overwrite, respectively 6  =  report  all
              mismatching  calls  without merging 7 = report mismatching nonmissing calls without

              : With --merge/--bmerge/--merge-list,  merge  variants  with  different  names  but
              identical  positions.   (Exception: same-position chromosome code 0 variants aren't

              : Make Mendel error checks consider samples with only one parent in the dataset.

              : Make Mendel error checks consider (great-)grandparental genotypes  when  parental
              genotype data is missing.

       --ld-window [ct+1] : Set --r/--r2 max variant ct pairwise distance (usu. 10).

       --ld-window-kb [x] : Set --r/--r2 max kb pairwise distance (usually 1000).

       --ld-window-cm [x] : Set --r/--r2 max centimorgan pairwise distance.

       --ld-window-r2 [x] : Set threshold for --r2 report inclusion (usually 0.2).

       --ld-snp [var ID]
              : Set first variant in all --r/--r2 pairs.

       --ld-snps [vID...] : Restrict first --r/--r2 variant to the given ranges.

       --ld-snp-list [f]
              : Restrict first --r/--r2 var. to those named in the file.

              : Generate the 'all' mode report when using --show-tags in file mode.

       --tag-kb [kbs]
              : Set --show-tags max tag kb distance (default 250).

       --tag-r2 [val]
              : Set --show-tags min tag r-squared (default 0.8)

              : Use two-column --show-tags (file mode) I/O format.

       --ld-xchr [code]
              : Set Xchr model for --indep{-pairwise}, --r/--r2, --flip-scan, and --show-tags.  1
              (default) = males coded 0/1, females 0/1/2 (A1 dosage) 2 =  males  coded  0/2  3  =
              males coded 0/2, but females given double weighting

       --blocks-max-kb [kbs]
              : Set --blocks maximum haploblock span (def. 200).

       --blocks-min-maf [cutoff]
              : Adjust --blocks MAF minimum (default 0.05).

       --blocks-strong-lowci [x]
              : Set --blocks 'strong LD' CI thresholds (defaults

       --blocks-strong-highci [x]
              0.70 and 0.98).

       --blocks-recomb-highci [x] : Set 'recombination' CI threshold (default 0.90).

       --blocks-inform-frac [x]
              :  Force haploblock [strong LD pairs]:[total informative pairs] ratios to be larger
              than this value (default 0.95).

       --distance-wts exp=[x]
              : When computing genomic distances, assign each variant a weight of (2q(1-q))^{-x},
              where q is the loaded or inferred MAF.

       --read-dists [dist file] {id file} : Load a triangular binary distance matrix
              instead of recalculating from scratch.

       --ppc-gap [val]
              :  Minimum number of base pairs, in thousands, between informative pairs of markers
              used in --genome PPC test.  500 if unspecified.

       --min [cutoff]
              : Specify minimum PI_HAT for inclusion in --genome report.

       --max [cutoff]
              : Specify maximum PI_HAT for inclusion in --genome report.

       --homozyg-match [] : Set minimum concordance across jointly homozygous
              variants for a pairwise allelic match to be declared.

       --pool-size [ct]
              : Set minimum size of pools in '--homozyg group' report.

       --read-genome [fn] : Load --genome report for --cluster/--neighbour, instead
              of recalculating IBS and PPC test p-values from scratch.

       --ppc [p-val]
              : Specify minimum PPC test p-value within a cluster.

       --mc [max size]
              : Specify maximum cluster size.

       --mcc [c1] [c2]
              : Specify maximum case and control counts per cluster.

       --K [min count]
              : Specify minimum cluster count.

       --ibm [val]
              : Specify minimum identity-by-missingness.

       --match [f] {mv} : Use covariate values to restrict clustering.
              Without --match-type, two samples can only be in the same cluster if all covariates
              match.   The  optional  second  parameter  specifies  a covariate value to treat as

       --match-type [f] : Refine interpretation of --match file.
              The --match-type file is expected to be a single line with as many entries  as  the
              --match  file  has covariates; '0' entries specify 'negative matches' (i.e. samples
              with equal covariate values cannot be in the same  cluster),  '1'  entries  specify
              'positive  matches'  (default),  and  '-1' causes the corresponding covariate to be

       --qmatch [f] {m} : Force all members of a cluster to have similar

       --qt [fname]
              quantitative covariate values.  The --qmatch file contains  the  covariate  values,
              while  the  --qt  file  is  a  list  of  nonnegative  tolerances (and '-1's marking
              covariates to skip).

       --pca-cluster-names [...] : These can be used individually or in combination

       --pca-clusters [fname]
              to  define  a  list  of  clusters  to  use  in   the   basic   --pca   computation.
              (--pca-cluster-names  expects  a  space-delimited  sequence of cluster names, while
              --pca-clusters expects a file with one cluster name per line.)  All samples outside
              those clusters will then be projected on to the calculated PCs.

       --mds-plot [dims] <by-cluster> <eigendecomp> <eigvals> :

       Multidimensional scaling analysis.
              Requires --cluster.

       --cell [thresh]
              :  Skip some --model tests when a contingency table entry is smaller than the given

       --condition [var ID] <dominant | recessive> : Add one variant as a --linear
              or --logistic covariate.

       --condition-list [f] <dominant | recessive> : Add variants named in the file
              as --linear/--logistic covs.

       --parameters [...]
              : Include only the given covariates/interactions in the --linear/--logistic models,
              identified by a list of 1-based indices and/or ranges of them.

       --tests <all> {...} : Perform a (joint) test on the specified term(s) in the
              --linear/--logistic model, identified by 1-based indices and/or ranges of them.  If
              permutation  was  requested,  it  is  based  on  this  test.   *  Note  that,  when
              --parameters is also present, the

       indices refer to the terms remaining AFTER pruning by

              * You can use '--tests all' to include all terms.

       --vif [max VIF]
              : Set VIF threshold for --linear multicollinearity check (default 50).

       --xchr-model [code] : Set the X chromosome --linear/--logistic model.
              0  =  skip  sex  and  haploid chromosomes 1 (default) = add sex as a covariate on X
              chromosome 2 = code male genotypes 0/2 instead of 0/1  3  =  test  for  interaction
              between genotype and sex

       --lasso-select-covars {cov(s)...} : Subject some or all covariates to LASSO
              model selection.

       --adjust <gc> <log10> <qq-plot>
              : Report some multiple-testing corrections.

       --lambda [val]
              : Set genomic control lambda for --adjust.

       --ci [size]
              : Report confidence intervals for odds ratios.

       --pfilter [val]
              : Filter out association test results with higher p-values.

       --aperm [min perms - 1] {max perms} {alpha} {beta} {init interval} {slope} :

              Set  up  to six parameters controlling adaptive permutation tests.  * The first two
              control the minimum and maximum number of permutations that

              may be run for each variant; default values are 5 and 1000000.

       * The next two control the early termination condition.

              100% * (1 - beta/2T) confidence interval is calculated for each empirical  p-value,
              where  T is the total number of variants; whenever this confidence interval doesn't
              contain alpha, the variant is exempted from further permutation  testing.   Default
              values are 0 and 1e-4.

       * The last two control when the early termination condition is checked.

              a  check  occurs  at  permutation  #p, the next check occurs after [slope]p + [init
              interval] more permutations (rounded down).  Default initial  interval  is  1,  and
              default slope is 0.001.

              : Save best max(T) permutation test statistics.

       --mperm-save-all : Save all max(T) permutation test statistics.

       --set-p [p-val]
              : Adjust set test significant variant p-value ceiling (default 0.05).

       --set-r2 {v} <write>
              :  Adjust set test significant variant pairwise r^2 ceiling (default 0.5).  'write'
              causes violating pairs to be dumped to {output prefix}.ldset.

       --set-max [ct]
              : Adjust set test maximum # of significant variants considered per set (default 5).

       --set-test-lambda [v] : Specify genomic control correction for set test.

       --border [kbs]
              : Extend --annotate range intervals by given # kbs.

       --annotate-snp-field [nm] : Set --annotate variant ID field name.

       --clump-p1 [pval] : Set --clump index var. p-value ceiling (default 1e-4).

       --clump-p2 [pval] : Set --clump secondary p-value threshold (default 0.01).

       --clump-r2 [r^2]
              : Set --clump r^2 threshold (default 0.5).

       --clump-kb [kbs]
              : Set --clump kb radius (default 250).

       --clump-snp-field [n...]
              : Set --clump variant ID field name (default 'SNP').  With  multiple  field  names,
              earlier names take precedence over later ones.

       --clump-field [name...]
              : Set --clump p-value field name (default 'P').

              : Let --clump non-index vars. join multiple clumps.

              : Request extended --clump report.

       --clump-annotate [hdr...] : Include named extra fields in --clump-verbose and
              --clump-best reports.  (Field names can be separated with spaces or commas.)

       --clump-range [filename]
              : Report overlaps between clumps and regions.

       --clump-range-border [kb] : Stretch regions in --clump-range file.

              : Extract --clump index vars. from only first file.

              : Exclude clumps which contain secondary results from only one file.

              : Report best proxy for each --clump index var.

       --meta-analysis-snp-field [n...] : Set --meta-analysis variant ID, A1/A2

       --meta-analysis-a1-field [n...]
              allele, p-value, and/or effective sample

       --meta-analysis-a2-field [n...]
              size field names.  Defauls are 'SNP',

       --meta-analysis-p-field [n...]
              'A1', 'A2', 'P', and 'NMISS',

       --meta-analysis-ess-field [n...]
              respectively.   When  multiple  parameters  are given to these flags, earlier names
              take precedence over later ones.  Note that, if the numbers of cases  and  controls
              are unequal, effective sample size should be

              4 / (1/[# cases] + 1/[# controls]).

              : When a variant appears multiple times in in the same file, report that.

       --gene-list-border [kbs]
              : Extend --gene-report regions by given # of kbs.

       --gene-subset [filename]
              : Specify gene name subset for --gene-report.

       --gene-report-snp-field [] : Set --gene-report variant ID field name (default
              'SNP').  Only relevant with --extract.

       --gap [kbs]
              : Set '--fast-epistasis case-only' min. gap (default 1000).

       --epi1 [p-value] : Set --{fast-}epistasis reporting threshold (default
              5e-6 for 'boost', 1e-4 otherwise).

       --epi2 [p-value] : Set threshold for contributing to SIG_E count (def. 0.01).

       --je-cellmin [n] : Set required number of observations per 3x3x2 contingency
              table cell for joint-effects test (default 5).

       --q-score-range [range file] [data file] {i} {j} <header> :

              Apply  --score  to  subset(s)  of  variants in the primary score list based on e.g.
              p-value ranges.  * The first file should have range labels  in  the  first  column,

              lower  bounds  in  the  second column, and upper bounds in the third column.  Lines
              with too few entries, or nonnumeric values in  the  second  or  third  column,  are

              * The second file should contain a variant ID and a p-value on each

       nonempty line (except possibly the first).
              Variant IDs are read from

              column  #i  and  p-values  are  read  from  column  #j, where i defaults to 1 and j
              defaults to i+1.  The 'header' modifier causes the first nonempty line of this file
              to be skipped.

       --R-port [port #]
              : Connect to Rserve on a port other than 6311.

       --R-host [host]
              : Connect to Rserve host.

       --R-socket [sock]
              : Connect to Rserve socket.

       --parallel [k] [n] : Divide the output matrix into n pieces, and only compute
              the  kth piece.  The primary output file will have the piece number included in its
              name, e.g. plink.rel.13 or plink.rel.13.gz if k is 13.  Concatenating  these  files
              in  order  will  yield  the full matrix of interest.  (Yes, this can be done before
              unzipping.)  N.B. This generally cannot be  used  to  directly  write  a  symmetric
              square  matrix.   Choose  square0  or  triangle  shape  instead, and postprocess as

       --memory [val]
              : Set size, in MB, of initial workspace  malloc  attempt.   (Practically  mandatory
              when using GNU parallel.)

       --threads [val]
              :  Set  maximum  number of concurrent threads.  This has one known limitation: some
              BLAS/LAPACK linear algebra operations are multithreaded in a way that PLINK  cannot
              control.   If  this  is  problematic,  you should recompile against single-threaded

       --d [char]
              : Change variant/covariate range delimiter (normally '-').

       --seed [val...]
              : Set random number  seed(s).   Each  value  must  be  an  integer  between  0  and
              4294967295 inclusive.

       --perm-batch-size [val] : Set number of permutations per batch for some
              permutation tests.

       --output-min-p [p] : Specify minimum p-value to write to reports.

              : Use slower, more crash-resistant logging method.

       Primary  methods  paper:  Chang CC, Chow CC, Tellier LCAM, Vattikuti S, Purcell SM, Lee JJ
       (2015) Second-generation PLINK: rising to the challenge of  larger  and  richer  datasets.
       GigaScience, 4.

       For     further     documentation     and    support,    consult    the    main    webpage
       (      )      and/or       the       mailing       list
       ( ).


       The full documentation for PLINK is maintained as a Texinfo manual.  If the info and PLINK
       programs are properly installed at your site, the command

              info PLINK

       should give you access to the complete manual.