Provided by: raxml_8.2.12+dfsg-8_amd64 bug

NAME

       raxmlHPC - Randomized Axelerated Maximum Likelihood

SYNOPSIS

       raxmlHPC
       [-SSE3|-AVX|-PTHREADS|-PTHREADS-SSE3|-PTHREADS-AVX|-HYBRID|-HYBRID-SSE3|HYBRID-AVX]     -s
       sequenceFileName   -n   outputFileName   -m   substitutionModel  [-a  weightFileName]  [-A
       secondaryStructureSubstModel] [-b bootstrapRandomNumberSeed] [-B wcCriterionThreshold] [-c
       numberOfCategories]  [-C]  [-d]  [-D]  [-e  likelihoodEpsilon]  [-E  excludeFileName]  [-f
       a|A|b|B|c|C|d|D|e|E|F|g|G|h|H|i|I|j|J|k|m|n|N|o|p|P|q|r|R|s|S|t|T|u|v|V|w|W|x|y] [-F]  [-g
       groupingFileName]  [-G  placementThreshold] [-h] [-H] [-i initialRearrangementSetting] [-I
       autoFC|autoMR|autoMRE|autoMRE_IGN] [-j] [-J MR|MR_DROP|MRE|STRICT|STRICT_DROP|T_<PERCENT>]
       [-k]  [-K]  [-L  MR|MRE|T_<PERCENT>] [-M] [-o outGroupName1[,outGroupName2[,...]]][-O] [-p
       parsimonyRandomSeed]     [-P     proteinModel]     [-q     multipleModelFileName]      [-r
       binaryConstraintTree]    [-R   binaryModelParamFile]   [-S   secondaryStructureFile]   [-t
       userStartingTree] [-T numberOfThreads]  [-u]  [-U]  [-v]  [-V]  [-w  outputDirectory]  [-W
       slidingWindowSize]      [-x      rapidBootstrapRandomNumberSeed]     [-X]     [-y]     [-Y
       quartetGroupingFileName|ancestralSequenceCandidatesFileName] [-z multipleTreesFile] [-#|-N
       numberOfRuns|autoFC|autoMR|autoMRE|autoMRE_IGN]
       [--mesquite][--silent][--no-seq-check][--no-bfgs]
       [--asc-corr=stamatakis|felsenstein|lewis]      [--flag-check][--auto-prot=ml|bic|aic|aicc]
       [--epa-keep-placements=number][--epa-accumulated-threshold=threshold]
       [--epa-prob-threshold=threshold]     [--JC69][--K80][--HKY85]    [--bootstop-perms=number]
       [--quartets-without-replacement] [---without-replacement] [--print-identical-sequences]

OPTIONS

       -a     Specify a column weight file name to assign individual weights to  each  column  of
              the  alignment.  Those weights must be integers separated by any type and number of
              whitespaces whithin a separate file, see file "example_weights" for an example.

       -A     Specify one of the secondary structure substitution models  implemented  in  RAxML.
              The  same  nomenclature as in the PHASE manual is used, available models: S6A, S6B,
              S6C, S6D, S6E, S7A, S7B, S7C, S7D, S7E, S7F, S16, S16A, S16B

              DEFAULT: 16-state GTR model (S16)

       -b     Specify an integer number (random seed) and turn on bootstrapping

              DEFAULT: OFF

       -B     specify a floating point number between 0.0 and 1.0 that will  be  used  as  cutoff
              threshold for the MR-based bootstopping criteria. The recommended setting is 0.03.

              DEFAULT: 0.03 (recommended empirically determined setting)

       -c     Specify   number   of  distinct  rate  catgories  for  RAxML  when  model  of  rate
              heterogeneity is  set  to  CAT  Individual  per-site  rates  are  categorized  into
              numberOfCategories rate categories to accelerate computations.

              DEFAULT: 25

       -C     Enable  verbose  output for the "-L" and "-f i" options. This will produce more, as
              well as more verbose output files

              DEFAULT: OFF

       -d     start ML optimization from random starting tree

              DEFAULT: OFF

       -D     ML search convergence criterion. This will break off ML searches  if  the  relative
              Robinson-Foulds  distance  between the trees obtained from two consecutive lazy SPR
              cycles is smaller or equal to 1%. Usage recommended  for  very  large  datasets  in
              terms  of  taxa.   On  trees with more than 500 taxa this will yield execution time
              improvements of approximately 50% While yielding only slightly worse trees.

              DEFAULT: OFF

       -e     set model optimization precision in log likelihood units for final optimization  of
              tree topology

       DEFAULT: 0.1
              for models not using proportion of invariant sites estimate

              0.001 for models using proportion of invariant sites estimate

       -E     specify  an exclude file name, that contains a specification of alignment positions
              you wish to exclude.  Format is similar to Nexus, the file  shall  contain  entries
              like  "100-200  300-400", to exclude a single column write, e.g., "100-100", if you
              use a mixed model, an appropriately adapted model file will be written.

       -f     select algorithm:

              -f a: rapid Bootstrap analysis and search for best-scoring ML tree in  one  program
              run

              -f  A:  compute  marginal ancestral states on a ROOTED reference tree provided with
              "-t"

              -f b: draw bipartition information on a tree provided with "-t" based  on  multiple
              trees (e.g., from a bootstrap) in a file specified by "-z"

              -f  B:  optimize  br-len  scaler and other model parameters (GTR, alpha, etc.) on a
              tree provided with "-t".  The tree needs to  contain  branch  lengths.  The  branch
              lengths will not be optimized, just scaled by a single common value.

              -f c: check if the alignment can be properly read by RAxML -f C: ancestral sequence
              test for Jiajie, users will also need to provide a  list  of  taxon  names  via  -Y
              separated by whitespaces -f d: new rapid hill-climbing

              DEFAULT: ON

              -f D: rapid hill-climbing with RELL bootstraps

              -f e: optimize model+branch lengths for given input tree under GAMMA/GAMMAI only

              -f E: execute very fast experimental tree search, at present only for testing

              -f F: execute fast experimental tree search, at present only for testing

              -f g: compute per site log Likelihoods for one or more trees passed via

              -z  and  write them to a file that can be read by CONSEL. The model parameters will
              be estimated on the first tree only!

              -f G: compute per site log Likelihoods for one or more trees passed  via  "-z"  and
              write  them  to  a  file  that  can be read by CONSEL. The model parameters will be
              re-estimated for each tree

              -f h: compute log likelihood test (SH-test) between best tree passed via "-t" and a
              bunch  of other trees passed via "-z" The model parameters will be estimated on the
              first tree only!

              -f H: compute log likelihood test (SH-test) between best tree passed via "-t" and a
              bunch  of other trees passed via "-z" The model parameters will be re-estimated for
              each tree

              -f i: calculate IC and TC scores (Salichos and Rokas 2013) on a tree provided  with
              "-t" based on multiple trees (e.g., from a bootstrap) in a file specified by "-z"

              -f  I:  a  simple  tree  rooting algorithm for unrooted trees. It roots the tree by
              rooting it at the branch that best balances the subtree lengths (sum over  branches
              in  the  subtrees)  of the left and right subtree. A branch with an optimal balance
              does not always exist! You need to specify the tree you want to root via "-t".

              -f j: generate a bunch of bootstrapped alignment files from an  original  alignemnt
              file. You need to specify a seed with "-b" and the number of replicates with "-#"

              -f J: Compute SH-like support values on a given tree passed via "-t".

              -f  k: Fix long branch lengths in partitioned data sets with missing data using the
              branch length stealing algorithm. This option only works in conjunction with  "-t",
              "-M",  and  "-q".  It will print out a tree with shorter branch lengths, but having
              the same likelihood score.

              -f m: compare bipartitions between two bunches of trees passed via  "-t"  and  "-z"
              respectively.  This  will  return  the Pearson correlation between all bipartitions
              found      in      the      two      tree      files.      A      file       called
              RAxML_bipartitionFrequencies.outpuFileName   will  be  printed  that  contains  the
              pair-wise bipartition frequencies of the two sets

              -f n: compute the log likelihood score of  all  trees  contained  in  a  tree  file
              provided  by  "-z"  under  GAMMA  or  GAMMA+P-Invar.  The  model parameters will be
              estimated on the first tree only!

              -f N: compute the log likelihood score of  all  trees  contained  in  a  tree  file
              provided  by  "-z"  under  GAMMA  or  GAMMA+P-Invar.  The  model parameters will be
              re-estimated for each tree

              -f o: old and slower rapid hill-climbing without heuristic cutoff

              -f p: perform pure stepwise MP addition of new sequences to an incomplete  starting
              tree and exit

              -f  P: perform a phylogenetic placement of sub trees specified in a file passed via
              "-z" into a given reference tree in which these  subtrees  are  contained  that  is
              passed via "-t" using the evolutionary placement algorithm.

              -f q: fast quartet calculator

              -f r: compute pairwise Robinson-Foulds (RF) distances between all pairs of trees in
              a tree file passed via "-z" if the trees have node labales represented  as  integer
              support  values  the  program  will  also  compute  two  flavors  of  the  weighted
              Robinson-Foulds (WRF) distance

              -f R: compute all pairwise Robinson-Foulds (RF) distances between a large reference
              tree passed via "-t" and many smaller trees (that must have a subset of the taxa of
              the large tree)  passed  via  "-z".  This  option  is  intended  for  checking  the
              plausibility of very large phylogenies that can not be inspected visually any more.

              -f s: split up a multi-gene partitioned alignment into the respective subalignments

              -f  S:  compute site-specific placement bias using a leave one out test inspired by
              the evolutionary placement algorithm

              -f t: do randomized tree searches on one fixed starting tree

              -f T: do final thorough optimization of ML tree  from  rapid  bootstrap  search  in
              stand-alone mode

              -f  u: execute morphological weight calibration using maximum likelihood, this will
              return a weight vector. you  need  to  provide  a  morphological  alignment  and  a
              reference tree via "-t"

              -f  v:  classify  a  bunch  of  environmental sequences into a reference tree using
              thorough read insertions you will need to  start  RAxML  with  a  non-comprehensive
              reference tree and an alignment containing all sequences (reference + query)

              -f  V:  classify  a  bunch  of  environmental sequences into a reference tree using
              thorough read insertions you will need to  start  RAxML  with  a  non-comprehensive
              reference tree and an alignment containing all sequences (reference + query)

              WARNING:   this   is   a   test  implementation  for  more  efficient  handling  of
              multi-gene/whole-genome datasets!

              -f w: compute ELW test on a bunch of trees passed via "-z".  The  model  parameters
              will be estimated on the first tree only!

              -f  W:  compute  ELW test on a bunch of trees passed via "-z". The model parameters
              will be re-estimated for each tree

              -f x: compute pair-wise ML distances, ML model parameters will be estimated  on  an
              MP  starting  tree  or  a  user-defined  tree  passed  via  "-t",  only allowed for
              GAMMA-based models of rate heterogeneity

              -f y: classify a bunch of environmental  sequences  into  a  reference  tree  using
              parsimony  you will need to start RAxML with a non-comprehensive reference tree and
              an alignment containing all sequences (reference + query)

              DEFAULT for -f: new rapid hill climbing

       -F     enable ML tree searches under CAT model for very large trees without  switching  to
              GAMMA  in  the  end  (saves  memory).   This option can also be used with the GAMMA
              models in order to avoid the thorough optimization of the best-scoring ML  tree  in
              the end.

              DEFAULT: OFF

       -g     specify  the  file name of a multifurcating constraint tree this tree does not need
              to be comprehensive, i.e. must not contain all taxa

       -G     enable the ML-based evolutionary placement algorithm  heuristics  by  specifiyng  a
              threshold  value  (fraction  of  insertion  branches  to  be  evaluated  using slow
              insertions under ML).

       -h     Display this help message.

       -H     Disable pattern compression.

              DEFAULT: ON

       -i     Initial rearrangement setting for the subsequent application of topological changes
              phase

       -I a posteriori bootstopping analysis. Use:

              -I autoFC for the frequency-based criterion

              -I autoMR for the majority-rule consensus tree criterion

              -I autoMRE for the extended majority-rule consensus tree criterion

              -I  autoMRE_IGN  for  metrics  similar  to  MRE, but include bipartitions under the
              threshold whether they are compatible or not. This emulates MRE but  is  faster  to
              compute.

              You also need to pass a tree file containg several bootstrap replicates via "-z"

       -j     Specifies that intermediate tree files shall be written to file during the standard
              ML and BS tree searches.

              DEFAULT: OFF

       -J     Compute majority rule consensus  tree  with  "-J  MR"  or  extended  majority  rule
              consensus  tree  with  "-J  MRE"  or  strict consensus tree with "-J STRICT". For a
              custom consensus threshold >= 50%,  specify  T_<NUM>,  where  100  >=  NUM  >=  50.
              Options "-J STRICT_DROP" and "-J MR_DROP" will execute an algorithm that identifies
              dropsets which contain rogue taxa as proposed by Pattengale et  al.  in  the  paper
              "Uncovering  hidden  phylogenetic consensus".  You will also need to provide a tree
              file containing several UNROOTED trees via "-z"

       -k     Specifies that bootstrapped trees should  be  printed  with  branch  lengths.   The
              bootstraps will run a bit longer, because model parameters will be optimized at the
              end of each run under GAMMA or GAMMA+P-Invar respectively.

              DEFAULT: OFF

       -K     Specify one of the multi-state substitution models (max 32 states)  implemented  in
              RAxML.  Available models are: ORDERED, MK, GTR

              DEFAULT: GTR model

       -L     Compute  consensus  trees  labelled  by  IC  supports  and  the overall TC value as
              proposed in Salichos and Rokas 2013.  Compute a majority rule consensus  tree  with
              "-L  MR"  or  an extended majority rule consensus tree with "-L MRE".  For a custom
              consensus threshold >= 50%, specify "-L T_<NUM>", where 100 >= NUM >= 50.  You will
              of  course  also  need to provide a tree file containing several UNROOTED trees via
              "-z"!

       -m     Model  of  Binary  (Morphological),  Nucleotide,   Multi-State,   or   Amino   Acid
              Substitution:

              BINARY:

       "-m BINCAT[X]"
              : Optimization of site-specific

       evolutionary rates which are categorized into numberOfCategories distinct
              rate categories for greater computational efficiency. Final tree might be evaluated
              automatically under BINGAMMA, depending  on  the  tree  search  option.   With  the
              optional "X" appendix you can specify a ML estimate of base frequencies.

       "-m BINCATI[X]"
              : Optimization of site-specific

       evolutionary rates which are categorized into numberOfCategories distinct
              rate categories for greater computational efficiency. Final tree might be evaluated
              automatically under BINGAMMAI, depending on  the  tree  search  option.   With  the
              optional "X" appendix you can specify a ML estimate of base frequencies.

       "-m ASC_BINCAT[X]"
              : Optimization of site-specific

       evolutionary rates which are categorized into numberOfCategories distinct
              rate categories for greater computational efficiency. Final tree might be evaluated
              automatically under BINGAMMA, depending  on  the  tree  search  option.   With  the
              optional  "X"  appendix you can specify a ML estimate of base frequencies.  The ASC
              prefix willl correct the likelihood for ascertainment bias.

       "-m BINGAMMA[X]"
              : GAMMA model of rate heterogeneity (alpha parameter will be estimated).

              With the optional "X" appendix you can specify a ML estimate of base frequencies.

       "-m ASC_BINGAMMA[X]" :  GAMMA  model  of  rate  heterogeneity  (alpha  parameter  will  be
       estimated).
              The  ASC  prefix  willl  correct  the  likelihood for ascertainment bias.  With the
              optional "X" appendix you can specify a ML estimate of base frequencies.

       "-m BINGAMMAI[X]"
              : Same as BINGAMMA, but with estimate of proportion of invariable sites.

              With the optional "X" appendix you can specify a ML estimate of base frequencies.

              NUCLEOTIDES:

       "-m GTRCAT[X]"
              : GTR + Optimization of substitution rates + Optimization of site-specific

       evolutionary rates which are categorized into numberOfCategories distinct
              rate  categories  for  greater  computational  efficiency.   Final  tree  might  be
              evaluated  under  GTRGAMMA, depending on the tree search option.  With the optional
              "X" appendix you can specify a ML estimate of base frequencies.

       "-m GTRCATI[X]"
              : GTR + Optimization of substitution rates + Optimization of site-specific

       evolutionary rates which are categorized into numberOfCategories distinct
              rate  categories  for  greater  computational  efficiency.   Final  tree  might  be
              evaluated  under GTRGAMMAI, depending on the tree search option.  With the optional
              "X" appendix you can specify a ML estimate of base frequencies.

       "-m ASC_GTRCAT[X]"
              : GTR + Optimization of substitution rates + Optimization of site-specific

       evolutionary rates which are categorized into numberOfCategories distinct
              rate  categories  for  greater  computational  efficiency.   Final  tree  might  be
              evaluated  under  GTRGAMMA, depending on the tree search option.  With the optional
              "X" appendix you can specify a ML estimate of base  frequencies.   The  ASC  prefix
              willl correct the likelihood for ascertainment bias.

       "-m GTRGAMMA[X]"
              : GTR + Optimization of substitution rates + GAMMA model of rate

       heterogeneity (alpha parameter will be estimated).
              With the optional "X" appendix you can specify a ML estimate of base frequencies.

       "-m ASC_GTRGAMMA[X]" : GTR + Optimization of substitution rates + GAMMA model of rate
              heterogeneity  (alpha  parameter  will be estimated).  The ASC prefix willl correct
              the likelihood for ascertainment bias.  With the  optional  "X"  appendix  you  can
              specify a ML estimate of base frequencies.

       "-m GTRGAMMAI[X]"
              : Same as GTRGAMMA, but with estimate of proportion of invariable sites.

              With the optional "X" appendix you can specify a ML estimate of base frequencies.

              MULTI-STATE:

       "-m MULTICAT[X]"
              : Optimization of site-specific

       evolutionary rates which are categorized into numberOfCategories distinct
              rate categories for greater computational efficiency. Final tree might be evaluated
              automatically under MULTIGAMMA, depending on the  tree  search  option.   With  the
              optional "X" appendix you can specify a ML estimate of base frequencies.

       "-m MULTICATI[X]"
              : Optimization of site-specific

       evolutionary rates which are categorized into numberOfCategories distinct
              rate categories for greater computational efficiency. Final tree might be evaluated
              automatically under MULTIGAMMAI, depending on the tree  search  option.   With  the
              optional "X" appendix you can specify a ML estimate of base frequencies.

       "-m ASC_MULTICAT[X]"
              : Optimization of site-specific

       evolutionary rates which are categorized into numberOfCategories distinct
              rate categories for greater computational efficiency. Final tree might be evaluated
              automatically under MULTIGAMMA, depending on the  tree  search  option.   With  the
              optional  "X"  appendix you can specify a ML estimate of base frequencies.  The ASC
              prefix willl correct the likelihood for ascertainment bias.

       "-m MULTIGAMMA[X]"
              : GAMMA model of rate heterogeneity (alpha parameter will be estimated).

              With the optional "X" appendix you can specify a ML estimate of base frequencies.

       "-m ASC_MULTIGAMMA[X]" : GAMMA model  of  rate  heterogeneity  (alpha  parameter  will  be
       estimated).
              The  ASC  prefix  willl  correct  the  likelihood for ascertainment bias.  With the
              optional "X" appendix you can specify a ML estimate of base frequencies.

       "-m MULTIGAMMAI[X]"
              : Same as MULTIGAMMA, but with estimate of proportion of invariable sites.

              With the optional "X" appendix you can specify a ML estimate of base frequencies.

              You can use up to 32 distinct character states to encode multi-state regions,  they
              must  be  used in the following order: 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, A, B, C, D, E,
              F, G, H, I, J, K, L, M, N, O, P, Q, R, S, T, U, V i.e.,  if  you  have  6  distinct
              character  states you would use 0, 1, 2, 3, 4, 5 to encode these.  The substitution
              model for the multi-state regions can be selected via the "-K" option

              AMINO ACIDS:

       "-m PROTCATmatrixName[F|X]"
              : specified AA matrix +  Optimization  of  substitution  rates  +  Optimization  of
              site-specific

       evolutionary rates which are categorized into numberOfCategories distinct
              rate  categories  for  greater  computational  efficiency.    Final  tree  might be
              evaluated automatically  under  PROTGAMMAmatrixName[F|X],  depending  on  the  tree
              search  option.   With  the  optional "X" appendix you can specify a ML estimate of
              base frequencies.

       "-m PROTCATImatrixName[F|X]"
              : specified AA matrix +  Optimization  of  substitution  rates  +  Optimization  of
              site-specific

       evolutionary rates which are categorized into numberOfCategories distinct
              rate  categories  for  greater  computational  efficiency.    Final  tree  might be
              evaluated automatically under  PROTGAMMAImatrixName[F|X],  depending  on  the  tree
              search  option.   With  the  optional "X" appendix you can specify a ML estimate of
              base frequencies.

       "-m ASC_PROTCATmatrixName[F|X]"
              : specified AA matrix +  Optimization  of  substitution  rates  +  Optimization  of
              site-specific

       evolutionary rates which are categorized into numberOfCategories distinct
              rate  categories  for  greater  computational  efficiency.    Final  tree  might be
              evaluated automatically  under  PROTGAMMAmatrixName[F|X],  depending  on  the  tree
              search  option.   With  the  optional "X" appendix you can specify a ML estimate of
              base frequencies.  The ASC prefix willl correct the  likelihood  for  ascertainment
              bias.

       "-m PROTGAMMAmatrixName[F|X]"
              : specified AA matrix + Optimization of substitution rates + GAMMA model of rate

       heterogeneity (alpha parameter will be estimated).
              With the optional "X" appendix you can specify a ML estimate of base frequencies.

       "-m  ASC_PROTGAMMAmatrixName[F|X]"  :  specified  AA matrix + Optimization of substitution
       rates + GAMMA model of rate
              heterogeneity (alpha parameter will be estimated).  The ASC  prefix  willl  correct
              the  likelihood  for  ascertainment  bias.   With the optional "X" appendix you can
              specify a ML estimate of base frequencies.

       "-m PROTGAMMAImatrixName[F|X]"
              : Same as PROTGAMMAmatrixName[F|X], but with estimate of proportion  of  invariable
              sites.

              With the optional "X" appendix you can specify a ML estimate of base frequencies.

              Available  AA  substitution  models: DAYHOFF, DCMUT, JTT, MTREV, WAG, RTREV, CPREV,
              VT, BLOSUM62, MTMAM, LG, MTART, MTZOA, PMB, HIVB,  HIVW,  JTTDCMUT,  FLU,  STMTREV,
              DUMMY, DUMMY2, AUTO, LG4M, LG4X, PROT_FILE, GTR_UNLINKED, GTR With the optional "F"
              appendix you can specify if you want to use empirical base frequencies.  AUTOF  and
              AUTOX  are  not  supported  any  more, if you specify AUTO it will test prot subst.
              models with and without empirical base  frequencies  now!   Please  note  that  for
              partitioned  models  you  can  in  addition  specify  the  per-gene AA model in the
              partition file (see manual for details). Also note that  if  you  estimate  AA  GTR
              parameters on a partitioned dataset, they will be linked (estimated jointly) across
              all partitions to avoid over-parametrization

       -M     Switch on estimation of individual per-partition branch lengths.  Only  has  effect
              when used in combination with "-q" Branch lengths for individual partitions will be
              printed to separate files A weighted average of the branch lengths is  computed  by
              using the respective partition lengths

              DEFAULT: OFF

       -n     Specifies the name of the output file.

       -o     Specify  the  name  of a single outgroup or a comma-separated list of outgroups, eg
              "-o Rat" or "-o Rat,Mouse", in case that multiple outgroups  are  not  monophyletic
              the first name in the list will be selected as outgroup, don't leave spaces between
              taxon names!

       -O     Disable check for completely undetermined sequence in alignment.  The program  will
              not exit with an error message when "-O" is specified.

              DEFAULT: check enabled

       -p     Specify  a  random  number  seed  for  the parsimony inferences. This allows you to
              reproduce your results and will help me debug the program.

       -P     Specify the file name of a user-defined AA (Protein) substitution model. This  file
              must  contain 420 entries, the first 400 being the AA substitution rates (this must
              be a symmetric matrix) and the last 20 are the empirical base frequencies

       -q     Specify the file  name  which  contains  the  assignment  of  models  to  alignment
              partitions  for multiple models of substitution. For the syntax of this file please
              consult the manual.

       -r     Specify the file name of a binary constraint tree.  this tree does not need  to  be
              comprehensive, i.e. must not contain all taxa

       -R     Specify  the  file  name  of a binary model parameter file that has previously been
              generated with RAxML using the -f e tree evaluation option. The  file  name  should
              be: RAxML_binaryModelParameters.runID

       -s     Specify the name of the alignment data file in PHYLIP format

       -S     Specify  the  name  of  a  secondary  structure  file. The file can contain "." for
              alignment columns that do not form part of a  stem  and  characters  "()<>[]{}"  to
              define stem regions and pseudoknots

       -t     Specify a user starting tree file name in Newick format

       -T     PTHREADS VERSION ONLY! Specify the number of threads you want to run.  Make sure to
              set "-T" to at most the number of CPUs you have on your machine,  otherwise,  there
              will be a huge performance decrease!

       -u     use  the  median  for  the  discrete  approximation  of  the  GAMMA  model  of rate
              heterogeneity

              DEFAULT: OFF

       -U     Try to save memory by using SEV-based implementation for gap columns on large gappy
              alignments         The         technique         is         described         here:
              http://www.biomedcentral.com/1471-2105/12/470 This will only work  for  DNA  and/or
              PROTEIN data and only with the SSE3 or AVX-vextorized version of the code.

       -v     Display version information

       -V     Disable rate heterogeneity among sites model and use one without rate heterogeneity
              instead.  Only works if you specify the CAT model of rate heterogeneity.

              DEFAULT: use rate heterogeneity

       -w     FULL (!) path to the directory into which RAxML shall write its output files

              DEFAULT: current directory

       -W     Sliding window size for leave-one-out site-specific placement bias  algorithm  only
              effective when used in combination with "-f S"

              DEFAULT: 100 sites

       -x     Specify  an  integer  number (random seed) and turn on rapid bootstrapping CAUTION:
              unlike in version 7.0.4 RAxML will conduct rapid BS replicates under the  model  of
              rate heterogeneity you specified via "-m" and not by default under CAT

       -X     Same  as  the  "-y" option below, however the parsimony search is more superficial.
              RAxML  will  only  do  a  randomized  stepwise  addition   order   parsimony   tree
              reconstruction  without  performing  any  additional SPRs.  This may be helpful for
              very broad whole-genome  datasets,  since  this  can  generate  topologically  more
              different starting trees.

              DEFAULT: OFF

       -y     If  you want to only compute a parsimony starting tree with RAxML specify "-y", the
              program will exit after computation of the starting tree

              DEFAULT: OFF

       -Y     Pass a quartet grouping file name defining four groups from which to draw  quartets
              The file input format must contain 4 groups in the following form: (Chicken, Human,
              Loach), (Cow, Carp), (Mouse, Rat, Seal), (Whale, Frog); Only works  in  combination
              with -f q !

       -z     Specify  the  file  name  of a file containing multiple trees e.g. from a bootstrap
              that shall be used to draw bipartition values onto a tree provided  with  "-t",  It
              can also be used to compute per site log likelihoods in combination with "-f g" and
              to read a bunch of trees for a couple of other options ("-f h", "-f m", "-f n").

       -#|-N  Specify the number of alternative runs on distinct starting  trees  In  combination
              with  the "-b" option, this will invoke a multiple boostrap analysis Note that "-N"
              has been added as an alternative since "-#" sometimes caused problems with  certain
              MPI  job  submission  systems,  since "-#" is often used to start comments.  If you
              want to use the bootstopping criteria specify "-# autoMR" or "-#  autoMRE"  or  "-#
              autoMRE_IGN"  for  the  majority-rule  tree  based  criteria (see -I option) or "-#
              autoFC"  for  the  frequency-based  criterion.   Bootstopping  will  only  work  in
              combination with "-x" or "-b"

              DEFAULT: 1 single analysis

       --mesquite Print output files that can be parsed by Mesquite.

              DEFAULT: Off

       --silent  Disables  printout  of  warnings  related  to  identical  sequences and entirely
              undetermined sites in the alignment

              DEFAULT: Off

       --no-seq-check Disables checking the  input  MSA  for  identical  sequences  and  entirely
       undetermined sites.
              Enabling   this  option  may  save  time,  in  particular  for  large  phylogenomic
              alignments.  Before using this, make sure to check the alignment using the  "-f  c"
              option!

              DEFAULT: Off

       --no-bfgs  Disables  automatic usage of BFGS method to optimize GTR rates on unpartitioned
              DNA datasets

              DEFAULT: BFGS on

       --asc-corr Allows to specify the type of ascertainment bias correction you  wish  to  use.
              There are 3

              types   available:   --asc-corr=lewis:   the  standard  correction  by  Paul  Lewis
              --asc-corr=felsenstein: a correction introduced by Joe Felsenstein that  allows  to
              explicitely specify

              the number of invariable sites (if known) one wants to correct for.

       --asc-corr=stamatakis:  a  correction  introduced  by  myself  that  allows to explicitely
       specify
              the number of invariable sites for each character (if known) one wants  to  correct
              for.

       --flag-check  When  using  this  option,  RAxML  will only check if all command line flags
              specifed are available and then exit

              with a message listing all invalid command line flags or  with  a  message  stating
              that all flags are valid.

       --auto-prot=ml|bic|aic|aicc When using automatic protein model selection you can chose the
              criterion for selecting these models.

              RAxML will test all  available  prot  subst.  models  except  for  LG4M,  LG4X  and
              GTR-based  models,  with  and  without  empirical  base frequencies.  You can chose
              between ML score based selection and the BIC, AIC, and AICc criteria.

              DEFAULT: ml

       --epa-keep-placements=number specify the number of potential placements you want  to  keep
              for each read in the EPA algorithm.

              Note  that,  the  actual  values  printed  will  also  depend  on  the settings for
              --epa-prob-threshold=threshold !

              DEFAULT: 7

       --epa-prob-threshold=threshold  specify  a  percent  threshold  for  including   potential
              placements of a read depending on the

              maximum  placement  weight  for this read. If you set this value to 0.01 placements
              that have a placement weight of 1 per cent of the maximum placement will  still  be
              printed to file if the setting of --epa-keep-placements allows for it

              DEFAULT: 0.01

       --epa-accumulated-threshold=threshold  specify  an accumulated likelihood weight threshold
              for which different placements of read are printed

              to file. Placements for a read will be printed until the  sum  of  their  placement
              weights  has  reached  the  threshold value.  Note that, this option can neither be
              used in combination with --epa-prob-threshold nor with --epa-keep-placements!

       --JC69 specify that all DNA partitions will evolve  under  the  Jukes-Cantor  model,  this
              overrides all other model specifications for DNA partitions.

              DEFAULT: Off

       --K80  specify that all DNA partitions will evolve under the K80 model, this overrides all
              other model specifications for DNA partitions.

              DEFAULT: Off

       --HKY85 specify that all DNA partitions will evolve under the HKY85 model, this  overrides
              all other model specifications for DNA partitions.

              DEFAULT: Off

       --bootstop-perms=number  specify  the  number  of  permutations  to  be  conducted for the
              bootstopping/bootstrap convergence test.

              The allowed minimum number is 100!

              DEFAULT: 100

       --quartets-without-replacement specify that quartets are randomly subsampled, but  without
              replacement.

              DEFAULT: random sampling with replacements

       --print-identical-sequences  specify  that  RAxML  shall automatically generate a .reduced
              alignment with all

              undetermined columns removed, but without removing exactly identical sequences

              DEFAULT: identical sequences will also be removed in the .reduced file

See also

       Please also consult the RAxML-manual.

       Please report bugs via the RAxML google group!  Please send us all input files, the  exact
       invocation,  details of the HW and operating system, as well as all error messages printed
       to screen.

AUTHOR

       This manpage was written by Andreas Tille for the Debian distribution and can be used  for
       any other usage of the program.

       The  code  itself  was  written  by  Alexandros Stamatakis.  With greatly appreciated code
       contributions by:

              Andre Aberer      (HITS)

              Simon Berger      (HITS)

              Alexey Kozlov     (HITS)

              Kassian Kobert    (HITS)

              David Dao         (KIT and HITS)

              Sarah Lutteropp   (KIT and HITS)

              Nick Pattengale   (Sandia)

              Wayne Pfeiffer    (SDSC)

              Akifumi S. Tanabe (NRIFS)

              Charlie Taylor    (UF)