Picard中文使用手册

The Picard command-line tools are packaged as a single executable jar file. They require Java 1.6. They can be invoked as follows:

java jvm-args -jar picard.jar PicardCommandName OPTION1=value1 OPTION2=value2...

Most of the commands are designed to run in 2GB of JVM, so the JVM argument -Xmx2g is recommended.

The following options are relevant for most Picard programs:

Adds one or more comments to the header of a specified BAM file. Copies the file with the modified header to a specified output file. Note that a block copying method is used to ensure efficient transfer to the output file. SAM files are not supported

Replaces all read groups in the INPUT file with a single new read group and assigns all reads to this read group in the OUTPUT BAM

Create BFQ files from a BAM file for use by the Maq aligner.

Generates BAM index statistics, including the number of aligned and unaligned SAMRecords for each reference sequence, and the number of SAMRecords with no coordinate.Input BAM file must have a corresponding index file.

Converts a BED file to an Picard Interval List.

Generates a BAM index (.bai) file.

Calculates a set of Hybrid Selection specific metrics from an aligned SAMor BAM file. If a reference sequence is provided, AT/GC dropout metrics will be calculated, and the PER_TARGET_COVERAGE option can be used to output GC and mean coverage information for every target.

Cleans the provided SAM/BAM, soft-clipping beyond-end-of-reference alignments and setting MAPQ to 0 for unmapped reads

Produces a file containing summary alignment metrics from a SAM or BAM.

Usage example:

    java -jar picard.jar CollectAlignmentMetrics \
        R=reference.fasta \
        I=input.bam \
        O=output.txt

Program to chart the nucleotide distribution per cycle in a SAM or BAM file.

Tool to collect information about GC bias in the reads in a given BAM file. Computes the number of windows (of size specified by SCAN_WINDOW_SIZE) in the genome at each GC% and counts the number of read starts in each GC bin. What is output and plotted is the "normalized coverage" in each bin - i.e. the number of reads per window normalized to the average number of reads per window across the whole genome..

Reads a SAM or BAM file and writes a file containing metrics about the statistical distribution of insert size (excluding duplicates) and generates a Histogram plot.

Takes an input BAM and reference sequence and runs one or more Picard metrics modules at the same time to cut down on I/O. Currently all programs are run with default options and fixed output extensions, but this may become more flexible in future.

Calculates a set of metrics to Illumina Truseq Custom Amplicon sequencing from an aligned SAMor BAM file. If a reference sequence is provided, AT/GC dropout metrics will be calculated, and the PER_TARGET_COVERAGE option can be used to output GC and mean coverage information for every target.

Collect metrics about the alignment of RNA to various functional classes of loci in the genome:coding, intronic, UTR, intergenic, ribosomal. Also determines strand-specificity for strand-specific libraries.

Computes a number of metrics that are useful for evaluating coverage and performance of whole genome sequencing experiments.

USAGE: CompareSAMS Compares the headers of the two input SAM or BAM files, and, if possible, the SAMRecords. For SAMRecords, compares only the readUnmapped flag, reference name, start position and strand. Reports the number of SAMRecords that match, differ in alignment, are mapped in only one input, or are missing in one of the files

Read fasta or fasta.gz containing reference sequences, and write as a SAM or BAM file with only sequence dictionary.

Randomly down-sample a SAM or BAM file to retain only a subset of the reads in the file. All reads for a templates are kept or discarded as a unit, with the goal of retaining readsfrom PROBABILITY * input templates. While this will usually result in approximately PROBABILITY * input reads being retained also, for very small PROBABILITIES this may not be the case. A number of different downsampling strategies are supported using the STRATEGY option: ConstantMemory: Downsamples a stream or file of SAMRecords using a hash-projection strategy such that it can run in constant memory. The downsampling is stochastic, and therefore the actual retained proportion will vary around the requested proportion. Due to working in fixed memory this strategy is good for large inputs, and due to the stochastic nature the accuracy of this strategy is highest with a high number of output records, and diminishes at low output volumes. HighAccuracy: Attempts (but does not guarantee) to provide accuracy up to a specified limit. Accuracy is defined as emitting a proportion of reads as close to the requested proportion as possible. In order to do so this strategy requires memory that is proportional to the number of template names in the incoming stream of reads, and will thus require large amounts of memory when running on large input files. Chained: Attempts to provide a compromise strategy that offers some of the advantages of both the ConstantMemory and HighAccuracy strategies. Uses a ConstantMemory strategy to downsample the incoming stream to approximately the desired proportion, and then a HighAccuracy strategy to finish. Works in a single pass, and will provide accuracy close to (but often not as good as) HighAccuracy while requiring memory proportional to the set of reads emitted from the ConstantMemory strategy to the HighAccuracy strategy. Works well when downsampling large inputs to small proportions (e.g. downsampling hundreds of millions of reads and retaining only 2%. Should be accurate 99.9% of the time when the input contains >= 50,000 templates (read names). For smaller inputs, HighAccuracy is recommended instead.

Determine the barcode for each read in an Illumina lane. For each tile, a file is written to the basecalls directory of the form s___barcode.txt. An output file contains a line for each read in the tile, aligned with the regular basecall output. The output file contains the following tab-separated columns: * read subsequence at barcode position * Y or N indicating if there was a barcode match * matched barcode sequence Note that the order of specification of barcodes can cause arbitrary differences in output for poorly matching barcodes.

Attempts to estimate library complexity from sequence of read pairs alone. Does so by sorting all reads by the first N bases (5 by default) of each read and then comparing reads with the first N bases identical to each other for duplicates. Reads are considered to be duplicates if they match each other with no gaps and an overall mismatch rate less than or equal to MAX_DIFF_RATE (0.03 by default). Reads of poor quality are filtered out so as to provide a more accurate estimate. The filtering removes reads with any no-calls in the first N bases or with a mean base quality lower than MIN_MEAN_QUALITY across either the first or second read. Unpaired reads are ignored in this computation. The algorithm attempts to detect optical duplicates separately from PCR duplicates and excludes these in the calculation of library size. Also, since there is no alignment to screen out technical reads one further filter is applied on the data. After examining all reads a Histogram is built of [#reads in duplicate set -> #of duplicate sets] all bins that contain exactly one duplicate set are then removed from the Histogram as outliers before library size is estimated.

Extracts read sequences and qualities from the input fastq file and writes them into the output file in unaligned BAM format. Input files can be in GZip format (end in .gz).

Provides a large, configurable, FIFO buffer that can be used to buffer input and output streams between programs with a buffer size that is larger than that offered by native unix FIFOs (usually 64k).

Produces a new SAM or BAM file by including or excluding aligned reads or a list of reads names supplied in the READ_LIST_FILE from the INPUT SAM or BAM file.

Applies one or more hard filters to a VCF file to filter out genotypes and variants.

Ensure that all mate-pair information is in sync between each read and its mate pair. If no OUTPUT file is supplied then the output is written to a temporary file and then copied over the INPUT file. Reads marked with the secondary alignment flag are written to the output file unchanged.

Concatenates one or more BAM files together as efficiently as possible. Assumes that the list of BAM files provided as INPUT are in the order that they should be concatenated and simply concatenates the bodies of the BAM files while retaining the header from the first file. Operates via copying of the gzip blocks directly for speed but also supports generation of an MD5 on the output and indexing of the output BAM file. Only support BAM files, does not support SAM files.

Gathers multiple VCF files from a scatter operation into a single VCF file. Input files must be supplied in genomic order and must not have events at overlapping positions.

Calculates the concordance between genotype data for two samples in two different VCFs - one being considered the truth (or reference) the other being considered the call. The concordance is broken into separate results sections for SNPs and indels. Summary and detailed statistics are reported Note that for any pair of variants to compare, only the alleles for the samples under interrogation are considered and MNP, Symbolic, and Mixed classes of variants are not included.

Generate fastq file(s) from data in an Illumina basecalls output directory. Separate fastq file(s) are created for each template read, and for each barcode read, in the basecalls. Template fastqs have extensions like ..fastq, where is the number of the template read, starting with 1. Barcode fastqs have extensions like .barcode_.fastq, where is the number of the barcode read, starting with 1.

Generate a SAM or BAM file from data in an Illumina basecalls output directory

Check that the files to provide the data specified by DATA_TYPES are available, exist, and are reasonably sized for every tile/cycle. Reasonably sized means non-zero sized for files that exist per tile and equal size for binary files that exist per cycle/per tile. CheckIlluminaDirectory DOES NOT check that the individual records in a file are well-formed.

General tool for manipulating interval lists, including sorting, merging, padding, uniqueifying, and other set-theoretic operations. Default operation if given one or more inputs is to merge and sort them. Other options are controlled by arguments.

Lifts a VCF over from one genome build to another using UCSC liftover. The output file will be sorted and indexed. Records may be rejected because they cannot be lifted over or because post-liftover the reference allele mismatches the target genome build. Rejected records will be emitted with filters to the REJECT file, on the source genome.

Reads a VCF/VCF.gz/BCF and removes all genotype information from it while retaining all site level information, including annotations based on genotypes (e.g. AN, AF). Output an be any support variant format including .vcf, .vcf.gz or .bcf.

Examines aligned records in the supplied SAM or BAM file to locate duplicate molecules. All records are then written to the output file with the duplicate records flagged.

Examines aligned records in the supplied SAM or BAM file to locate duplicate molecules. All records are then written to the output file with the duplicate records flagged.

Program to generate a data table and pdf chart of mean base quality by cycle from a SAM or BAM file. Works best on a single lane/run of data, but can be applied tomerged BAMs. Uses R to generate chart output.

Merges alignment data from a SAM or BAM file with additional data stored in an unmapped BAM file and produces a third SAM or BAM file of aligned and unaligned reads. The purpose is to use information from the unmapped BAM to fix up aligner output, so that the resulting file is valid for use by other Picard programs. For simple BAM file merges, use MergeSamFiles. NOTE that MergeBamAlignment expects to find a sequence dictionary in the same directory as REFERENCE_SEQUENCE and expects it to have the same base name as the reference fasta except with the extension '.dict'

Merges multiple SAM/BAM files into one file.

Merges multiple VCF or BCF files into one VCF file. Input files must be sorted by their contigs and, within contigs, by start position. The input files must have the same sample and contig lists. An index file is created and a sequence dictionary is required by default.

Takes any file that conforms to the fasta format and normalizes it so that all lines of sequence except the last line per named sequence are of the same length.

Extracts one or more intervals described in an interval_list file from a given reference sequence and writes them out in FASTA format. Requires a fasta index file to be present.

Program to chart quality score distributions in a SAM or BAM file.

Not to be confused with SortSam which sorts a SAM or BAM file with a valid sequence dictionary, ReorderSam reorders reads in a SAM/BAM file to match the contig ordering in a provided reference file, as determined by exact name matching of contigs. Reads mapped to contigs absent in the new reference are dropped. Runs substantially faster if the input is an indexed BAM file.

Replace the SAMFileHeader in a SAM file with the given header. Validation is minimal. It is up to the user to ensure that all the elements referred to in the SAMRecords are present in the new header. Sort order of the two input files must be the same.

Reverts SAM or BAM files to a previous state by removing certain types of information and/or substituting in the original quality scores when available.

Reverts the original base qualities and adds the mate cigar tag to read-group BAMs.

Convert a BAM file to a SAM file, or SAM to BAM. Input and output formats are determined by file extension.

Extracts read sequences and qualities from the input SAM/BAM file and writes them into the output file in Sanger fastq format. In the RC mode (default is True), if the read is aligned and the alignment is to the reverse strand on the genome, the read's sequence from input SAM file will be reverse-complemented prior to writing it to fastq in order restore correctlythe original read sequence as it was generated by the sequencer.

Sorts the input SAM or BAM. Input and output formats are determined by file extension.

Sorts one or more VCF files according to the order of the contigs in the header/sequence dictionary and then by coordinate. Can accept an external sequence dictionary. If no external dictionary is supplied, multiple inputs' headers must have the same sequence dictionaries. Multiple inputs must have the same sample names (in order)

Takes a VCF and a second file that contains a sequence dictionary and updates the VCF with the new sequence dictionary.

Convert a VCF file to a BCF file, or BCF to VCF. Input and output formats are determined by file extension.

Reads a SAM or BAM file and rewrites it with new adapter-trimming tags. Clear any existing adapter-trimming tags (XT:i:). Only works for unaligned files in query-name order. Note: This is a utility program and will not be run in the pipeline.

Splits an input VCF or BCF file into two VCF files, one for indel records and one for SNPs. Theheaders of the two output files will be identical. An index file is created and asequence dictionary is required by default.

Read a SAM or BAM file and report on its validity.

Prints a SAM or BAM file to the screen.

Converts a VCF or BCF file to a Picard Interval List.