A Clojure interface to the Genome Analysis Toolkit (GATK) to analyze variant data in VCF files. It supports scoring for the Archon Genomic X PRIZE competition but is also a general framework for variant file comparison.
- presentation from Bioinformatics Open Source Conference 2012
- presentation overview of the project
- howto description of interfacing with GATK
- code documentation
Requires Java 1.6 or better and Leiningen. We use the 2.x version of Leiningen, so be sure to get the preview release:
$ wget https://raw.github.com/technomancy/leiningen/preview/bin/lein $ chmod 755 lein && sudo mv lein /usr/local/bin
Then use Leiningen to install all dependencies:
$ lein deps
Generate summary of concordance between variant calls
A YAML configuration file specifies the variant files for comparison. The project contains example configuration and associated variant files that demonstrate the features of the library.
An example of scoring a phased diploid genome against a haploid reference genome:
$ lein variant-compare config/reference-grading.yaml
An example of assessing variant calls produced by different calling algorithms:
$ lein variant-compare config/method-comparison.yaml
Normalize a variant file
A tricky part of variant comparisons is that VCF format is flexible enough to allow multiple representations. As a result two files may contain the same variants, but one might have it present in a multi-nucleotide polymorphism while another represents it as an individual variant.
To produce a stable, decomposed variant file for comparison run:
$ lein variant-prep your_variants.vcf your_reference.fasta
This will also handle re-ordering variants to match the reference file ordering, essential for feeding into tools like GATK, and remapping hg19 to GRCh37 chromosome names.
A web interface automates the process of preparing configuration files and running a variant comparison:
$ lein variant-web config/web-processing.yaml
Run GATK walker for variant statistics
$ lein uberjar $ java -jar target/bcbio.variation-0.0.1-SNAPSHOT-standalone.jar -T VcfSimpleStats -R test/data/GRCh37.fa --variant test/data/gatk-calls.vcf --out test.png
Run custom GATK annotator
$ lein uberjar $ java -jar target/bcbio.variation-0.0.1-SNAPSHOT-standalone.jar -T VariantAnnotator -A MeanNeighboringBaseQuality -R test/data/GRCh37.fa -I test/data/aligned-reads.bam --variant test/data/gatk-calls.vcf -o annotated-file.vcf
A YAML configuration file defines targets for comparison processing. Two example files for reference grading and comparison of calling methods provide example starting points and details on available options are below:
dir: base: Base directory to allow use of relative paths (optional). out: Working directory to write output. prep: Prep directory where files will be pre-processed. experiments: # one or more experiments - sample: Name of current sample. ref: Reference genome in FASTA format. intervals: Intervals to process in BED format (optional). align: Alignments for all calls in BAM format (optional). summary-level: Amount of summary information to provide, [full,quick] (default:full) approach: Type of comparison to do [compare,grade]. Default compare. calls: # two or more calls to compare - name: Name of call type file: One or more input files in VCF format align: Alignment for specific call in BAM format (optional). ref: Reference genome if different than experiment ref (optional) intervals: Genome intervals to process in BED format (optional). metadata: Dictionary of annotations associated with the call set. Finalizers use these to provide annotation specific filtering of calls. filters: Provide hard filtering of variants prior to comparison with specified JEXL GATK expressions. format-filters: Provide hard filtering of variants based on attributes in the genotype FORMAT field. recall: Recall, using GATK, all non-called variant positions after merging multiple input calls. (boolean; default false) annotate: Annotate calls with GATK annotations (boolean; default false). normalize: Normalize MNPs and indels (boolean: default true). prep: Prep with in-order chromosomes and sample names (boolean; default false). prep-sort-pos: Sort by position during prep. Required if variants are not coordinate sorted within chromosomes. (boolean; default false). prep-sv-genotype: Normalize structural variant genotypes to a single ref call (boolean; default false). prep-allele-count: Number of alleles to convert calls to during prep work (default 2) preclean: Remove problematic characters from input VCFs (boolean; default false). remove-refcalls: Remove reference, non-variant calls. (boolean; default false). make-haploid: Convert a set of diploid calls to haploid variants (boolean; default false)
In addition to the pairwise comparisons, the configuration allows specification
of additional filtration and all-by-all comparisons based on the pairwise
calls, specify these under an experiment with the
tag. Available methods are:
multiplewhich does a comparison of a target call method to all other calls. A comparison of GATK calls to all other methods looks like:
finalize: - method: multiple target: gatk ignore: 
and produces three output files:
- true positives -- calls detected in all methods
- false negatives -- calls not found in gatk, but detected in all other methods
- false positives -- calls found in gatk but callable and discordant in one of the other methods
ignoreoption provides a list of methods to ignore in the all-by-all overlap comparison.
recal-filterto do post-comparisons filtering of calls. This can use either the results of a pairwise comparison or
multiplecomparison. An example demonstrating all of the filtering options re-filters a GATK versus FreeBayes comparison:
finalize: - method: recal-filter target: [gatk, freebayes] params: filters: [HRun > 5.0] annotations: [QD, HaplotypeScore, MQRankSum, ReadPosRankSum] lenient: false classifiers: [AD, DP, QUAL] trusted: total: 0.75 technology: 0.65
The options for filtering are:
filters-- Perform hard filtering of the file with specified expressions.
annotations-- Perform GATK Variant Quality Score Recalibration using the supplied annotations. The
lenientoption allows VQSR on samples with a lower number of total variations and is useful in VQSR fails.
classifiers-- Perform classification of true/false reads based on the provided attributes.
trusted-- Metadata annotation values that specify trusted variants not subjected to filtering. The example retains variants present in more than 75% of calls or 65% of different technologies.
You can specify the background to use for training with
support. There are two options:
support: gatk-- Use an all-by-all comparison based on GATK to establish true and false positives.
support: [gatk, freebayes]-- Use the gatk/freebayes pairwise comparison for true and false positives.
This library also contains useful command line utilities to help with variant preparation and analysis:
Create a BAM file compatible with GATK. This converts coordinates between hg19 and GRCh37 for human samples, reorders chromosomes relative to the input file and adds run group information with a defined sample name:
lein variant-reorder your_file.bam /path/to/GRCh37.fa SampleName
Provide a summary CSV file of call information for a VCF file, including mappings back to an original set of pairwise analyses:
lein variant-utils callsummary variants.vcf original-combined-config.yaml
- Brad Chapman
- Chris Fields
- Kevin Lynagh
- Justin Zook
The code is freely available under the MIT license.