A collection of scripts for analyzing 2bRAD genotyping data.
Eli-Meyer/2bRAD_utilities
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A collection of scripts for analysis of 2bRAD sequence data. For instructions, see the User's Guide at http://eli-meyer.github.io/2bRAD_utilities ------------------------- AlleleFilter.pl ------------------------- ------------------------------------------------------------ AlleleFilter.pl Excludes loci containing too many alleles. Usage: AlleleFilter.pl -i input -n max_alleles <options> Required arguments: -i input name of the input file, a matrix of genotypes. Input format: rows=loci and columns=samples. row 1 = column label, column 1 = tag, column 2 = position subsequent columns contain genotypes for each sample -n max_alleles maximum number of alleles allowed. Loci with more than this number of allels will be excluded. Options: -p option y=print filtered loci and summary; n=only print summary (default=n) -o output a name for the output file (loci passing this filter) (required if -p y) ------------------------------------------------------------ ------------------------- BuildRef.pl ------------------------- ------------------------------------------------------------ BuildRef.pl Builds a reference for de novo analysis of 2bRAD sequences from samples without a sequenced genome. The script filters, clusters, and compares similar sequences to infer the set of loci present in the species of interest, using a subset of reads from the samples themselves. Usage: BuildRef.pl -i input -o output <OPTIONS> Required arguments: -i input The set of processed (truncated, HQ) reads (FASTQ) to be used for reference development. Ideally this should include 10-20 million reads spanning the range of known diversity (e.g. from all populations in your study). Prepare this ahead of time by concatenating together a subset of reads from your samples. -o output a name for the output file, to be used as a reference in mapping and genotyping Options: -v overwrite 0=do not overwrite existing files; use them for analysis. (default) 1=do not use existing files; overwrite them with new files. -n mincov Minimum depth to qualify as a valid allele. (default=2) -q threshold Quality scores below this threshold are low quality (default=30) -x number Maximum number of low quality bases allowed for reference construction (default=0) -m mismatches Maximum number of mismatches allowed in clustering of related alleles (default=2) -d distance Minimum number of bases required to resolve sub-clusters (default=1) -a haplotypes For very large clusters containing more than this number of unique sequences, do not attempt to resolve sub clusters. These indicate repetitive sequences which are not useful for genotyping anyway, and resolving these large clusters is computationally intensive. (default=32) ------------------------------------------------------------ ------------------------- CallGenotypes.pl ------------------------- ------------------------------------------------------------ CallGenotypes.pl Determines SNP genotypes from nucleotide frequencies. Input file contains nucleotide frequencies from multiple samples. Output file lists the genotypes called from those frequencies. Usage: CallGenotypes.pl -i input -o output <OPTIONS> Required arguments: -i input Input file, tab delimited text file of nucleotide frequencies (output from NtFrequences.pl) column = tag, column 2 = locus, column 3 = reference genotype subsequent columns = nucleotide frequences in each sample, as A/C/G/T (e.g. 0/0/10/12) -o output A name for the output file (tab delimited text) Options: -c coverage Minimum coverage required to determine genotypes. Lower coverage loci wil be discarded. Default: 10 -e ends y: exclude terminal positions in alignments where errors may arise during ligation. (default) n: do not exclude terminal positions. -m method "nf": nucleotide frequencies (classic method; the default). This method determines genotypes directly from nucleotide frequencies, using thresholds defined by the user. If minor allele frequency (MAF) <= x at a locus, the genotype is called homozygous for the major allele at that locus. If MAF >= n, genotype is called heterozygous. Genotypes are not called at intermediate MAF (if x > MAF > n) where errors are likely. "pgf": NF informed by population genotype frequencies. (an update on the classic method) This method first identifies valid alleles at each locus based on their frequency in the population (the two most common alleles with frequencies >=y times in >= q individuals), then applies relaxed nucleotide frequency thresholds for those alleles (using y instead of n for valid alleles). "bgc" = Bayesian Genotype Caller This method calls the BGC software, which implements a maximum-likelihood (ML) method for calling genotypes that incorporates prior population-level information on genotype frequencies and error rates from a genotype-frequency estimator. For more details see (Maruki & Lynch, [doi: 10.1534/g3.117.039008], and cite that paper if using this option. Options for method "nf" or "pgf": -x max_MAF Maximum frequency of the minor allele you're willing to ignore and call the position homozygous for the major allele (0-1). Default: 0.01 -n min_MAF Minimum frequency of the minor allele you're willing to accept as evidence of heterozygosity, and call the locus heterozygous (0-1). Default: 0.25 -r min_reads Because low frequencies translate into 1 or fewer reads at low coverage, the script also imposes a minimum read number for detection of heterozygotes. (default: 2) Options for method "pgf": -y frequency Minimum frequency a second allele must be detected to be considered valid. (default: 0.05) -q samples Each allele must present in at least q samples to be considered valid. (default: 2) Options for method "bgc": -p p-value Critical p-value for the chi-square polymorphism test (BGC) (default: 0.05) -v maxcov Coverage at which the pipeline switches from BGC (for low coverage data) to HGC (for high coverage data). Default=80 (i.e. HGC above 80). Examples: CallGenotypes.pl -i allele_counts.tab -o genotypes.tab # basic usage CallGenotypes.pl -i allele_counts.tab -o genotypes.tab -c 20 # increase coverage threshold CallGenotypes.pl -i allele_counts.tab -o genotypes.tab -m bgc # use Bayesian Genotype Caller CallGenotypes.pl -i allele_counts.tab -o genotypes.tab -m pgf -y 0.05 # use population method ------------------------------------------------------------ ------------------------- CombineAlleleCounts.pl ------------------------- ------------------------------------------------------------ CombineAlleleCounts.pl Counts observations of alleles at each locus in a collection of base counts from 2bRAD (the output from SAMBaseCounts.pl). This script identifies the major and minor allele at each locus, and combines all samples into a single file containing the number of times each of these alleles was observed in each sample (two columns per sample, for major and minor allele respectively). Output format: columns 1=tag, 2=position, 3=major allele, 4=minor allele, 5=major allele counts for sample A, 6=minor allele counts for sample A, etc. Missing data are shown as "NA" for both alleles, and the minor allele is reported as "NA" for monomorphic loci. Usage: CombineAlleleCounts.pl <options> file_1 file_2 ... file_n > output_file Required arguments: files 1-n: nucleotide frequencies (output from SAMBaseCounts.pl) for each sample output_file: a name for the output; tab-delimited text Options: -a max_alleles maximum number of alleles allowed at each locus. Loci with more than this number of alleles will be excluded. (default=2) -v min_cov minimum coverage required to consider an allele present. (default=2) -s min_samp minimum number of samples in which an allele must be present (default=1) ------------------------------------------------------------ ------------------------- CombineBaseCounts.pl ------------------------- ------------------------------------------------------------ CombineBaseCounts.pl Counts the number of times each allele was observed, for each locus, in a collection of 2bRAD data describing nucleotide frequencies for each locus and sample (the output from SAMBaseCounts.pl). Output format: columns 1=tag, 2=position, 3=reference allele, 5=allele counts for sample 1 (A/C/G/T), 6=for sample 2, etc.. Missing data are shown as "NA" for all alleles. Usage: CombineBaseCounts.pl file_1 file_2 ... file_n > output_file Where: files 1-n: nucleotide frequencies (output from SAMBasecaller.pl) for each sample output_file: a name for the output; tab-delimited text ------------------------------------------------------------ ------------------------- CompareSNPMatrices.pl ------------------------- ------------------------------------------------------------ CompareSNPMatrices.pl Compare two matrices of SNP genotypes (e.g. produced from RAD data) from the same set of samples to evaluate overlap in genotyped loci, and the level of agreement and disagreement in genotypes. This is useful for comparing different genotyping algorithms. Input files are formatted as the output from NFGenotyper or BGCGenotyper: tab-delimited text, rows are loci, columns 1-2 are tag and locus and subsequent columns are samples, homozygotes shown as e.g. "A", heterozygotes as e.g. "A C", and missing data as "0". Usage: CompareSNPMatrices.pl -f file1 -s file2 <OPTIONS> Required arguments: -f file1 name of the first SNP matrix (tab delimited text) -s file2 name of the second SNP matrix (tab delimited text) Options: -o option 0: (default) don't print any detailed info on disagreements 1: show detailed info on loci called different homozygous genotypes in each file 2: show detailed info on loci called different heterozygous genotypes in each file 3: show detailed info on loci called homozygous in file1 and heterozygous in file2 4: show detailed info on loci called homozygous in file2 and heterozygous in file1 5: show detailed info on loci called in file 1 but not in file 2 -b counts (required if -o > 0) the file of allele counts from which genotypes were called. ------------------------------------------------------------ ------------------------- EvalFrags.pl ------------------------- ------------------------------------------------------------ EvalFrags.pl Evaluates the uniqueness of type IIb restriction fragments in a FASTA file. e.g. a collection of 36-bp AlfI fragments extracted from a genome sequence using AlfI_Extract.pl Usage: EvalFrags.pl input.fasta Where: input.fasta: a collection of 36-bp sequences (FASTA) ------------------------------------------------------------ ------------------------- ExtractSites.pl ------------------------- ------------------------------------------------------------ ExtractSites.pl Counts and extracts type IIb restriction fragments from a set of DNA sequences. Output: a fasta file of those sites, named by position. Usage: ExtractSites.pl -i input -o output Required arguments: -i input a fasta file containing the sequences to be searched -e enzyme choice of enzyme (AlfI, BsaXI, BcgI) -o output name for the output file, a fasta file of those sites ------------------------------------------------------------ ------------------------- FastaStats.pl ------------------------- ------------------------------------------------------------ FastaStats.pl Summarizes length statistics for a set of DNA sequences. Usage: FastaStats.pl -i input -o output Required arguments: -i input name of the input file (FASTA) -o output a name for the output file (TXT) ------------------------------------------------------------ ------------------------- gt2bayes.pl ------------------------- ------------------------------------------------------------ gt2bayes.pl Converts a 2bRAD genotype matrix into the input format required by BayeScan. Usage: gt2bayes.pl -i input -p pop.file -o output Required arguments: -i input tab-delimited genotype matrix, with rows=loci and columns=samples. First two columns indicate tag and position respectively. This format is the output from CallGenotypes.pl. -p pop.file a tab-delimited text file showing which population each sample was drawn from. Formatted as: SampleName "\t" PopName "\n" Note -- make sure that sample names in this file are exactly identical to those shown in the first row of the genotype matrix. -o output a name for the BayeScan formatted output file. ------------------------------------------------------------ ------------------------- gt2colony.pl ------------------------- ------------------------------------------------------------ gt2colony.pl Converts a genotype matrix (loci x samples) into the appropriate input format for COLONY. Usage: gt2colony.pl -i input -o output Required arguments: -i input tab-delimited genotype matrix, with rows=loci and columns=samples. First two columns indicate tag and position respectively. This format is the output from CallGenotypes.pl. -o output a name for the output file. COLONY input format. ------------------------------------------------------------ ------------------------- gt2dadi.pl ------------------------- ------------------------------------------------------------ gt2dadi.pl Converts a SNP matrix (produced from CallGenotypes.pl) into the format required by the software DADI, described at: https://bitbucket.org/gutenkunstlab/dadi/wiki/DataFormats Usage: gt2dadi.pl -i input -k key -r reference -o output Where: -i input tab-delimited genotype matrix, with rows=loci and columns=samples. First two columns indicate tag and position respectively. This format is the output from CallGenotypes.pl. -k key a tab-delimited text file associating each sample in the input with a population label. Alleles will be counted and reported by the population labels assigned in this file. Formated as: Sample_name Population_name -r reference Name of the reference file from which these SNPs were called (FASTA format) -o output a name for the output file. Tab delimited text in DADI format. ------------------------------------------------------------ ------------------------- gt2fasta.pl ------------------------- ------------------------------------------------------------ gt2fasta.pl Converts a genotype matrix (loci x samples) to a FASTA-formatted alignment. Usage: gt2fasta.pl -i input -o output Required arguments: -i input tab-delimited genotype matrix, with rows=loci and columns=samples. First two columns indicate tag and position respectively. This format is the output from CallGenotypes.pl. -o output a name for the output file. FASTA alignment format. ------------------------------------------------------------ ------------------------- gt2fstat.pl ------------------------- ------------------------------------------------------------ gt2fstat.pl Converts a genotype matrix (loci x samples) to FSTAT format. Usage: gt2fstat.pl -i input -o output Required arguments: -i input tab-delimited genotype matrix, with rows=loci and columns=samples. First two columns indicate tag and position respectively. This format is the output from CallGenotypes.pl. -o output a name for the output file. FSTAT format. corresponding locus_key and sample_key files are also produced. ------------------------------------------------------------ ------------------------- gt2phy.pl ------------------------- ------------------------------------------------------------ gt2phy.pl Converts a genotype matrix (loci x samples) to a PHYLIP-formatted alignment. Usage: gt2phy.pl -i input -o output Required arguments: -i input tab-delimited genotype matrix, with rows=loci and columns=samples. First two columns indicate tag and position respectively. This format is the output from CallGenotypes.pl. -o output a name for the output file. PHYLIP alignment format. ------------------------------------------------------------ ------------------------- gt2related.pl ------------------------- ------------------------------------------------------------ gt2related.pl Converts a genotype matrix (loci x samples) into the appropriate input format for the R package related Usage: gt2related.pl -i input -o output Required arguments: -i input tab-delimited genotype matrix, with rows=loci and columns=samples. First two columns indicate tag and position respectively. This format is the output from CallGenotypes.pl. -o output a name for the output file. RELATED format. ------------------------------------------------------------ ------------------------- gt2remlf90.pl ------------------------- ------------------------------------------------------------ gt2remlf90.pl Converts a SNP genotype matrix (loci x samples) produced from 2bRAD genotyping into the format required for the BLUPF90 family of programs for mixed models and quantitative genetic analysis. See BLUPF90 manual for details of that format. Usage: gt2remlf90.pl -i input -o output Required arguments: -i input Name of the input file, from CallGenotypes.pl. (rows=loci, columns=samples, columns 1 & 2 show tag name and position in tag) -o output A name for the output file, in the format expected by BLUPF90 programs, e.g. sample0 02221022511020101020 sample100 12221222221222200010 ------------------------------------------------------------ ------------------------- gt2Rqtl.pl ------------------------- ------------------------------------------------------------ gt2Rqtl.pl Converts a 2bRAD genotype matrix into the csv input format required by R/qtl. Usage: gt2Rqtl.pl -i input -t traits -o output Where: -i input tab-delimited genotype matrix, with rows=loci and columns=samples. First two columns indicate tag and position respectively. This format is the output from CallGenotypes.pl. -t traits tab-delimited file of data on traits, as "sample1 trait1 ... traitN" (note that sample names must match column headers in snps file) -m map tab-delimited file of map positions as "marker LG position" -o output a name for the csv formatted output file. ------------------------------------------------------------ ------------------------- gt2snpmatrix.pl ------------------------- ------------------------------------------------------------ gt2snpmatrix.pl Converts a genotype matrix (loci x samples) to a snp matrix, as described in the manual for the R package diveRsity. This snp matrix can be converted to genepop format using diveRsity's snp2gen function. Usage: gt2snpmatrix.pl -i input -o output Required arguments: -i input tab-delimited genotype matrix, with rows=loci and columns=samples. First two columns indicate tag and position respectively. This format is the output from CallGenotypes.pl. -o output a name for the output file. SNP matrix format, input for snp2gen. ------------------------------------------------------------ ------------------------- gt2structure.pl ------------------------- ------------------------------------------------------------ gt2structure.pl Converts a genotype matrix (loci x samples) into the appropriate input format for STRUCTURE. Usage: gt2structure.pl -i input -o output Required arguments: -i input tab-delimited genotype matrix, with rows=loci and columns=samples. First two columns indicate tag and position respectively. This format is the output from CallGenotypes.pl. -o output a name for the output file. STRUCTURE input format. ------------------------------------------------------------ ------------------------- gt2vcf.pl ------------------------- ------------------------------------------------------------ gt2vcf.pl Converts a genotype matrix (loci x samples) to a VCF file. Usage: gt2vcf.pl -i input -r reference -o output <options> Required arguments: -i input tab-delimited genotype matrix, with rows=loci and columns=samples. First two columns indicate tag and position respectively. This format is the output from CallGenotypes.pl. -o output a name for the output file. FASTA alignment format. -r reference Complete path to the reference file used to generate these genotypes (FASTA). Options: -f filters a text file described filters applied to the genotypes. this information will be included in the VCF file. e.g. "MD removed loci genotyped in <20 samples" ------------------------------------------------------------ ------------------------- LowcovSampleFilter.pl ------------------------- ------------------------------------------------------------ LowcovSampleFilter.pl Excludes samples with too much missing data (genotypes called at too few loci) Usage: LowcovSampleFilter.pl -i input -n min_data <OPTIONS> Required arguments: -i input name of the input file, a matrix of genotypes or allele counts (see -m for format) -n min_data samples in which fewer than this number of loci were genotyped will be excluded Options: -m mode g=genotypes (default). Input file contains genotypes from individuals. Input format: rows=loci and columns=samples. row 1 = column label, column 1 = tag, column 2 = position subsequent columns contain genotypes for each sample a=allele counts. Input file contains allele counts from pooled samples. Input format: rows=loci and columns=samples. row 1 = column label, column 1 = tag, column 2 = position column 3 = major allele, column 4 = minor allele subsequent pairs of columns contain allele counts (major then minor) for each sample -p option y=print filtered loci and summary; n=only print summary (default=n) -o output a name for the output file (loci passing this filter) (required if -p y) ------------------------------------------------------------ ------------------------- MDFilter.pl ------------------------- ------------------------------------------------------------ MDFilter.pl Excludes loci containing too many missing data (genotyped in too few samples) Usage: MDFilter.pl -i input -n min_data <OPTIONS> Required arguments: -i input name of the input file, a matrix of genotypes or allele counts (see -m for format) -n min_data loci that were genotyped in fewer samples than this will be excluded Options: -m mode g=genotypes (default). Input file contains genotypes from individuals. Input format: rows=loci and columns=samples. row 1 = column label, column 1 = tag, column 2 = position subsequent columns contain genotypes for each sample a=allele counts. Input file contains allele counts from pooled samples. Input format: rows=loci and columns=samples. row 1 = column label, column 1 = tag, column 2 = position column 3 = major allele, column 4 = minor allele subsequent pairs of columns contain allele counts (major then minor) for each sample -p option y=print filtered loci and summary; n=only print summary (default=n) -o output a name for the output file (loci passing this filter) (required if -p y) ------------------------------------------------------------ ------------------------- OneSNPPerTag.pl ------------------------- ------------------------------------------------------------ OneSNPPerTag.pl Selects a single SNP from each tag in a matrix or genotypes or allele counts. Chooses the locus with the least missing data. Usage: OneSNPPerTag.pl -i input <OPTIONS> Required arguments: -i input name of the input file, a matrix of genotypes or allele counts (see -m for format) Options: -m mode g=genotypes (default). Input file contains genotypes from individuals. Input format: rows=loci and columns=samples. row 1 = column label, column 1 = tag, column 2 = position subsequent columns contain genotypes for each sample a=allele counts. Input file contains allele counts from pooled samples. Input format: rows=loci and columns=samples. row 1 = column label, column 1 = tag, column 2 = position column 3 = major allele, column 4 = minor allele subsequent pairs of columns contain allele counts (major then minor) for each sample -p option y=print filtered loci and summary; n=only print summary (default=n) -o output a name for the output file (loci passing this filter) (required if -p y) ------------------------------------------------------------ ------------------------- PolyFilter.pl ------------------------- ------------------------------------------------------------ PolyFilter.pl Excludes loci containing too few classes of genotypes or numbers of alleles (keeps polymorphic loci). Usage: PolyFilter.pl -i input <OPTIONS> Required arguments: -i input name of the input file, a matrix of genotypes or allele counts (see -m for format) Options: -g genotypes minimum number of unique genotypes (for -m g) or alleles (for -m a) required to consider a locus polymorphic (default=2) -m mode g=genotypes (default). Input file contains genotypes from individuals. Input format: rows=loci and columns=samples. row 1 = column label, column 1 = tag, column 2 = position subsequent columns contain genotypes for each sample a=allele counts. Input file contains allele counts from pooled samples. Input format: rows=loci and columns=samples. row 1 = column label, column 1 = tag, column 2 = position column 3 = major allele, column 4 = minor allele subsequent pairs of columns contain allele counts (major then minor) for each sample -v min_cov (for -m a) minimum coverage required to consider an allele present (default=2) -s min_samp minimum number of samples in which an allele must be present (default=1) -p option y=print filtered loci and summary; n=only print summary (default=n) -o output a name for the output file (loci passing this filter) (required if -p y) ------------------------------------------------------------ ------------------------- QualFilterFastq.pl ------------------------- ------------------------------------------------------------ QualFilterFastq.pl Removes reads containing too many low quality basecalls from a set of short sequences Output: high-quality reads in FASTQ format Usage: QualFilterFastq.pl -i input -m min_score -x max_LQ -o output Required arguments: -i input raw input reads in FASTQ format -m min_score quality scores below this are considered low quality (LQ) -x max_LQ reads with more than this many LQ bases are excluded -o output name for ourput file of HQ reads in FASTQ format ------------------------------------------------------------ ------------------------- RandomFastq.pl ------------------------- ------------------------------------------------------------ RandomFastq.pl Draws the specified number of sequences randomly from a FASTQ sequence file. Usage: RandomFastq.pl -i input -n num_seq -o output Required arguments: -i input name of the input file from which sequences will be randomly drawn. -n num_seq number of sequences to draw -o output a name for the output file (FASTQ) ------------------------------------------------------------ ------------------------- RepTagFilter.pl ------------------------- ------------------------------------------------------------ RepTagFilter.pl Excludes tags containing too many SNPs, suggesting repetive regions of the genome Usage: RepTagFilter.pl -i input -n max_snps <OPTIONS> Required arguments: -i input name of the SNP input file, a matrix of genotypes or allele counts (see -m for format) note: the script assumes the input only includes polymorphic loci -n max_snps all SNPs from tags containing more than this number of SNPs will be excluded Options: -m mode g=genotypes (default). Input file contains genotypes from individuals. Input format: rows=loci and columns=samples. row 1 = column label, column 1 = tag, column 2 = position subsequent columns contain genotypes for each sample a=allele counts. Input file contains allele counts from pooled samples. Input format: rows=loci and columns=samples. row 1 = column label, column 1 = tag, column 2 = position column 3 = major allele, column 4 = minor allele subsequent pairs of columns contain allele counts (major then minor) for each sample -p option y=print filtered loci and summary; n=only print summary (default=n) -o output a name for the output file (loci passing this filter) (required if -p y) ------------------------------------------------------------ ------------------------- SAMBaseCounts.pl ------------------------- ------------------------------------------------------------ SAMBaseCounts.pl Counts nucleotide frequencies at each locus in a 2bRAD sequence data set. Usage: SAMBaseCounts.pl -i input -r reference -o <OPTIONS> Required arguments: -i input input alignments, SAM format -r reference reference used to generate the input alignments, FASTA format -o output a name for the output file (tab delimited text) Options: -c coverage loci with lower coverage are discarded (default: 3) ------------------------------------------------------------ ------------------------- SAMFilter.pl ------------------------- ------------------------------------------------------------ SAMFilter.pl Filters the alignments produced by mapping short reads against a reference, excluding ambiguous, short, and weak matches. NOTE: make sure that when a read matches multiple reference sequences (ambigous) your mapper reports at least two alignments in the output. This is NOT the default behavior for some mappers, but is required to exclude ambiguous matches before genotyping. Usage: SAMFilter.pl -i input -m matches -o output <options> Required arguments: -i input Output from any short read mapper, in SAM format. -m matches Minimum number of matching bases required to consider an alignment valid. -o output A name for the filtered output (SAM format). Options: -c option 1: Report the number of reads matching each reference sequence in a separate output files "counts.tab". 0: Don't produce this file (default). -l length Minimum length of aligned region (match, mismatch, + gaps) required to consider an alignment valid. Only relevant if your mapper uses local alignment. For global alignments, this is set equal to -m. ------------------------------------------------------------ ------------------------- TruncateFastq.pl ------------------------- ------------------------------------------------------------ TruncateFastq.pl Truncates a set of short reads in FASTQ format to keep the region specified Usage: TruncateFastq.pl -i input -s start -e end -o output Required arguments: -i input file of short reads to be filtered, fastq format -s start beginning of the region to keep, nucleotide position -e end end of the region to keep, nucleotide position -o output a name for the output file (fastq format) ------------------------------------------------------------
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A collection of scripts for analyzing 2bRAD genotyping data.
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