Provided by: grinder_0.5.4-5_all bug


       grinder - Versatile omics shotgun and amplicon sequencing read simulator


              grinder   -rf   <reference_file>   |   -reference_file   <reference_file>   |   -gf
              <reference_file> | -genome_file <reference_file> [cli optional  arguments]  grinder
              --help grinder --man grinder --usage grinder --version

   Cli required arguments:
       -rf <reference_file> | -reference_file <reference_file> | -gf

              <reference_file> | -genome_file <reference_file>

              FASTA  file  that  contains  the  input reference sequences (full genomes, 16S rRNA
              genes, transcripts, proteins...) or '-' to read them from the standard  input.  See
              the  README  file for examples of databases you can use and where to get them from.
              Default: -

   Cli optional arguments:
       -tr <total_reads> | -total_reads <total_reads>

              Number of shotgun or amplicon reads to generate for each library.  Do  not  specify
              this if you specify the fold coverage. Default: 100

       -cf <coverage_fold> | -coverage_fold <coverage_fold>

              Desired  fold  coverage  of  the input reference sequences (the output FASTA length
              divided by the input FASTA length). Do not specify this if you specify  the  number
              of reads directly.

       -rd <read_dist>... | -read_dist <read_dist>...

              Desired  shotgun or amplicon read length distribution specified as: average length,
              distribution ('uniform' or 'normal') and standard deviation.

              Only the first element is required. Examples:

              All reads exactly 101 bp long (Illumina  GA  2x):  101  Uniform  read  distribution
              around 100+-10 bp: 100 uniform 10 Reads normally distributed with an average of 800
              and a standard deviation of 100

              bp (Sanger reads): 800 normal 100

              Reads normally distributed with an average of 450 and a standard deviation of 50

              bp (454 GS-FLX Ti): 450 normal 50

              Reference sequences smaller than the specified read length are not  used.  Default:

       -id <insert_dist>... | -insert_dist <insert_dist>...

              Create  paired-end  or mate-pair reads spanning the given insert length. Important:
              the insert is defined in the biological sense, i.e. its length includes the  length
              of  both  reads  and  of  the stretch of DNA between them: 0 : off, or: insert size
              distribution in bp, in the same format as the read length distribution  (a  typical
              value  is  2,500 bp for mate pairs) Two distinct reads are generated whether or not
              the mate pair overlaps. Default: 0

       -mo <mate_orientation> | -mate_orientation <mate_orientation>

              When generating paired-end or mate-pair  reads  (see  <insert_dist>),  specify  the
              orientation of the reads (F: forward, R: reverse):

       FR:    ---> <---  e.g. Sanger, Illumina paired-end, IonTorrent mate-pair

       FF:    ---> --->  e.g. 454

       RF:    <--- --->  e.g. Illumina mate-pair

       RR:    <--- <---

              Default: FR

       -ec <exclude_chars> | -exclude_chars <exclude_chars>

              Do  not create reads containing any of the specified characters (case insensitive).
              For example, use 'NX' to prevent reads with ambiguities  (N  or  X).  Grinder  will
              error  if  it  fails  to find a suitable read (or pair of reads) after 10 attempts.
              Consider using <delete_chars>,  which  may  be  more  appropriate  for  your  case.
              Default: ''

       -dc <delete_chars> | -delete_chars <delete_chars>

              Remove  the  specified  characters from the reference sequences (case-insensitive),
              e.g. '-~*' to remove gaps (- or ~) or terminator (*). Removing these characters  is
              done once, when reading the reference sequences, prior to taking reads. Hence it is
              more efficient than <exclude_chars>. Default:

       -fr <forward_reverse> | -forward_reverse <forward_reverse>

              Use DNA amplicon sequencing  using  a  forward  and  reverse  PCR  primer  sequence
              provided in a FASTA file. The reference sequences and their reverse complement will
              be searched for PCR primer matches. The  primer  sequences  should  use  the  IUPAC
              convention  for  degenerate  residues  and the reference sequences that that do not
              match the specified primers are excluded. If  your  reference  sequences  are  full
              genomes, it is recommended to use <copy_bias> = 1 and <length_bias> = 0 to generate
              amplicon reads. To sequence from the forward strand, set <unidirectional> to 1  and
              put  the  forward  primer  first  and  reverse  primer second in the FASTA file. To
              sequence from the reverse strand, invert the primers in  the  FASTA  file  and  use
              <unidirectional>  =  -1.  The  second  primer  sequence in the FASTA file is always
              optional. Example: AAACTYAAAKGAATTGRCGG and ACGGGCGGTGTGTRC for the 926F and  1392R
              primers that target the V6 to V9 region of the 16S rRNA gene.

       -un <unidirectional> | -unidirectional <unidirectional>

              Instead  of  producing  reads  bidirectionally,  from  the reference strand and its
              reverse complement, proceed unidirectionally, from  one  strand  only  (forward  or
              reverse).  Values:  0  (off,  i.e.   bidirectional), 1 (forward), -1 (reverse). Use
              <unidirectional> = 1 for amplicon and strand-specific transcriptomic  or  proteomic
              datasets. Default: 0

       -lb <length_bias> | -length_bias <length_bias>

              In  shotgun  libraries,  sample reference sequences proportionally to their length.
              For example, in simulated microbial datasets, this means that at the same  relative
              abundance,  larger  genomes  contribute  more  reads  than smaller genomes (and all
              genomes have the same fold coverage). 0 = no, 1 = yes. Default: 1

       -cb <copy_bias> | -copy_bias <copy_bias>

              In amplicon libraries  where  full  genomes  are  used  as  input,  sample  species
              proportionally  to  the  number  of  copies  of  the target gene: at equal relative
              abundance, genomes that have multiple copies of the  target  gene  contribute  more
              amplicon reads than genomes that have a single copy. 0 = no, 1 = yes. Default: 1

       -md <mutation_dist>... | -mutation_dist <mutation_dist>...

              Introduce   sequencing   errors   in   the  reads,  under  the  form  of  mutations
              (substitutions, insertions and deletions) at  positions  that  follow  a  specified
              distribution  (with replacement): model (uniform, linear, poly4), model parameters.
              For example, for a uniform 0.1% error rate, use: uniform 0.1.  To  simulate  Sanger
              errors,  use  a linear model where the errror rate is 1% at the 5' end of reads and
              2% at the 3' end: linear 1 2.  To  model  Illumina  errors  using  the  4th  degree
              polynome  3e-3  + 3.3e-8 * i^4 (Korbel et al 2009), use: poly4 3e-3 3.3e-8. Use the
              <mutation_ratio> option to alter how many of these mutations are  substitutions  or
              indels.  Default: uniform 0 0

       -mr <mutation_ratio>... | -mutation_ratio <mutation_ratio>...

              Indicate  the  percentage of substitutions and the number of indels (insertions and
              deletions). For example, use '80 20' (4 substitutions for each  indel)  for  Sanger
              reads.   Note   that   this   parameter  has  no  effect  unless  you  specify  the
              <mutation_dist> option. Default: 80 20

       -hd <homopolymer_dist> | -homopolymer_dist <homopolymer_dist>

              Introduce sequencing errors in the reads under the form of homopolymeric  stretches
              (e.g.  AAA,  CCCCC)  using a specified model where the homopolymer length follows a
              normal distribution N(mean, standard deviation) that is function of the homopolymer
              length n:

       Margulies: N(n, 0.15 * n)
              ,  Margulies et al. 2005.

              : N(n, 0.15 * sqrt(n))        ,  Richter et al. 2008.

       Balzer : N(n, 0.03494 + n * 0.06856) ,  Balzer et al. 2010.

              Default: 0

       -cp <chimera_perc> | -chimera_perc <chimera_perc>

              Specify  the  percent  of  reads  in  amplicon  libraries  that  should be chimeric
              sequences. The 'reference' field in the description of chimeric reads will  contain
              the  ID  of  all  the  reference sequences forming the chimeric template. A typical
              value is 10% for amplicons.  This option can be used to generate  chimeric  shotgun
              reads as well.  Default: 0 %

       -cd <chimera_dist>... | -chimera_dist <chimera_dist>...

              Specify the distribution of chimeras: bimeras, trimeras, quadrameras and multimeras
              of higher order. The default is the average values from Quince et al. 2011: '314 38
              1',  which  corresponds to 89% of bimeras, 11% of trimeras and 0.3% of quadrameras.
              Note that this option only takes effect when you request the generation of chimeras
              with the <chimera_perc> option. Default: 314 38 1

       -ck <chimera_kmer> | -chimera_kmer <chimera_kmer>

              Activate  a  method  to form chimeras by picking breakpoints at places where k-mers
              are shared between sequences. <chimera_kmer> represents k, the length of the k-mers
              (in  bp).  The  longer  the  kmer,  the more similar the sequences have to be to be
              eligible to form chimeras.  The more frequent a k-mer is in the pool  of  reference
              sequences (taking into account their relative abundance), the more often this k-mer
              will be chosen. For example, CHSIM (Edgar et al. 2011)  uses  this  method  with  a
              k-mer  length  of  10  bp.  If  you  do  not  want to use k-mer information to form
              chimeras, use 0, which will result in the reference sequences and breakpoints to be
              taken  randomly  on  the  "aligned" reference sequences. Note that this option only
              takes effect when you request the generation of chimeras  with  the  <chimera_perc>
              option.  Also, this options is quite memory intensive, so you should probably limit
              yourself to a relatively small number of reference sequences if you want to use it.
              Default: 10 bp

       -af <abundance_file> | -abundance_file <abundance_file>

              Specify  the  relative  abundance  of  the reference sequences manually in an input
              file. Each line of the file  should  contain  a  sequence  name  and  its  relative
              abundance  (%),  e.g. 'seqABC 82.1' or 'seqABC 82.1 10.2' if you are specifying two
              different libraries.

       -am <abundance_model>... | -abundance_model <abundance_model>...

              Relative abundance model  for  the  input  reference  sequences:  uniform,  linear,
              powerlaw,  logarithmic or exponential. The uniform and linear models do not require
              a parameter, but the other models take a parameter in the range [0,  infinity).  If
              this parameter is not specified, then it is randomly chosen. Examples:

              uniform  distribution:  uniform  powerlaw distribution with parameter 0.1: powerlaw
              0.1 exponential distribution with automatically chosen parameter: exponential

              Default: uniform 1

       -nl <num_libraries> | -num_libraries <num_libraries>

              Number of independent libraries to create. Specify how  diverse  and  similar  they
              should   be  with  <diversity>,  <shared_perc>  and  <permuted_perc>.  Assign  them
              different MID tags with <multiplex_mids>. Default: 1

       -mi <multiplex_ids> | -multiplex_ids <multiplex_ids>

              Specify an optional FASTA file that contains multiplex sequence identifiers  (a.k.a
              MIDs  or  barcodes) to add to the sequences (one sequence per library, in the order
              given). The MIDs are included in the length specified with  the  -read_dist  option
              and can be altered by sequencing errors. See the MIDesigner or BarCrawl programs to
              generate MID sequences.

       -di <diversity>... | -diversity <diversity>...

              This option specifies alpha diversity, specifically the richness,  i.e.  number  of
              reference  sequences  to  take  randomly and include in each library. Use 0 for the
              maximum richness possible (based on the number of reference  sequences  available).
              Provide  one  value  to make all libraries have the same diversity, or one richness
              value per library otherwise. Default: 0

       -sp <shared_perc> | -shared_perc <shared_perc>

              This option controls an aspect of beta-diversity. When creating multiple libraries,
              specify  the percent of reference sequences they should have in common (relative to
              the diversity of the least diverse library). Default: 0 %

       -pp <permuted_perc> | -permuted_perc <permuted_perc>

              This option controls another aspect  of  beta-diversity.  For  multiple  libraries,
              choose  the  percent  of the most-abundant reference sequences to permute (randomly
              shuffle) the rank-abundance of.  Default: 100 %

       -rs <random_seed> | -random_seed <random_seed>

              Seed number to use for the pseudo-random number generator.

       -dt <desc_track> | -desc_track <desc_track>

              Track read information (reference sequence, position, errors, ...)  by  writing  it
              in the read description. Default: 1

       -ql <qual_levels>... | -qual_levels <qual_levels>...

              Generate  basic  quality  scores for the simulated reads. Good residues are given a
              specified good score (e.g. 30) and residues that are the result of an insertion  or
              substitution  are  given  a  specified  bad score (e.g. 10). Specify first the good
              score and then the bad score on the command-line, e.g.: 30 10. Default:

       -fq <fastq_output> | -fastq_output <fastq_output>

              Whether to write the generated reads in FASTQ format (with  Sanger-encoded  quality
              scores)  instead of FASTA and QUAL or not (1: yes, 0: no). <qual_levels> need to be
              specified for this option to be effective. Default: 0

       -bn <base_name> | -base_name <base_name>

              Prefix of the output files. Default: grinder

       -od <output_dir> | -output_dir <output_dir>

              Directory where the results should be written.  This  folder  will  be  created  if
              needed. Default: .

       -pf <profile_file> | -profile_file <profile_file>

              A  file  that contains Grinder arguments. This is useful if you use many options or
              often use the same options. Lines with  comments  (#)  are  ignored.  Consider  the
              profile file, 'simple_profile.txt':

              # A simple Grinder profile -read_dist 105 normal 12 -total_reads 1000

              Running: grinder -reference_file viral_genomes.fa -profile_file simple_profile.txt

              Translates  into: grinder -reference_file viral_genomes.fa -read_dist 105 normal 12
              -total_reads 1000

              Note that the arguments specified in the profile should not be specified  again  on
              the command line.


       grinder(7), grinder(1), average_genome_size(1) and change_paired_read_orientation(1).