MultiVCFAnalyzer

Table of Contents

• Description
• Citation
• Usage
• Example
• Output
• FAQs

Description

MultiVCFAnalyzer is a SNP filtering and SNP alignment generation tool, designed around (but not limited to) low coverage ancient DNA data. MultiVCFanalyzer reads multiple VCF files as produced by GATK UnifiedGenotyper, performs filtering based on a number of criteria, and provides the combined genotype calls in a number of formats that are suitable for follow-up analyses such as phylogenetic reconstruction, SNP effect analyses, population genetic analyses etc.

Furthermore, the results are provided in the form of various tables for manual inspection and presentation/publication purposes.

Citation

If you use MultiVCFAnalyzer please cite:

Bos, Harkins, Herbig, Coscolla et al. ‘Pre-Columbian mycobacterial genomes reveal seals as a source of New World human tuberculosis’ Nature 514, 494–497 (23 October 2014) doi:10.1038/nature13591

A more detailed description of the program can be seen in the supplementary information under “SNP Calling and Phylogenetic Analysis”.

In case of any questions please contact Alexander Herbig (alexander_herbig@eva.mpg.de).

Usage

The tool is a java program and requires openJDK 8. Input VCF files must be generated from GATK UnifiedGenotyper (<= 3.5), and ploidy must be set to 2 (to give allele frequency values).

To get the help message run

java -jar MultiVCFAnalyzer_X-XX-X.jar <OPTIONS>

Please start the program with the following parameters in strictly this order:

1. SNP effect analysis result file (from SnpEff; txt format) [OPTIONAL]
2. Reference genome file (fasta) - the same as used for VCF construction
3. Reference genome gene annotation (gff) [OPTIONAL]
4. Output directory - location of where to put output files
5. Write allele frequencies (‘T’ or ‘F’) - whether to include the percentage of reads a given allele is present in in the SNP table e.g. A (70%). In haploid microbial contexts, this can be used to assess cross-strain mapping.
6. Minimal genotyping quality (GATK) - a threshold of which a SNP call falling under is ‘discarded’
7. Minimal coverage for base call - the minimum number of a reads that a position must be covered by to be reported
8. Minimal allele frequency for homozygous call - the fraction of reads a base must have to be called ‘homozygous’
9. Minimal allele frequency for heterozygous call - a fraction of which whereby if a call falls above this value, and lower than the homozygous threshold, a base will be called ‘heterozygous’ and reported with a IUPAC uncertainity code
10. List of positions to exclude (gff) [OPTIONAL] - a file listing positions that will be ‘filtered’ (i.e. ignored)
11. [vcf_files …] input vcf files as generated by the GATK UnifiedGenotyper

To omit an optional input file put NA as the file name.

Example

The following is an example of running MultiVCFAnalyzer requiring a minimum genotyping quality of 30, a minimum fold coverage threshold of 5, a homozygous Ref/Allele being called if the base is >= 90% of

java -jar MultiVCFanalyzer_X-XX-X.jar \
NA \
/<PATH>/<TO>/<REFERENCE>.fasta \
NA \
/<PATH>/<TO>/<OUTPUTDIRECTORY>/ \
T \
30 \
5 \
0.9 \
0.1 \
NA \
/<PATH>/<TO>/Sample_1/<VCFFILE1>.vcf.gz \
/<PATH>/<TO>/Sample_2/<VCFFILE2>.vcf.gz \
/<PATH>/<TO>/Sample_3/<VCFFILE3>.vcf.gz

Output

Output files

The following files are created in output directory:

• fullAlignment.fasta a fasta file of all positions contained in the VCF files i.e. including ref calls
• info.txt information about the run
• snpAlignment.fasta a fasta file of just SNP positions with samples only
• snpAlignmentIncludingRefGenome.fasta a fasta file of just SNP positions with reference genome
• snpStatistics.tsv some basic statistics about the SNP calls of each sample
• snpTableForSnpEff.tsv input file for SnpEff
• snpTable.tsv basic SNP table of combined positions taken from each VCF file
• snpTableWithUncertaintyCalls.tsv same as above, but with lower case characters indicating uncertain call
• structureGenoypes_noMissingData-Columns.tsv alternate input file for STRUCTURE
• structureGenotypes.tsv input file for STRUCTURE

The snpTable.tsv file will not display positions that are the same call across all samples (e.g. if all samples have N, or . [a reference call])!

snpStatistics.tsv

The snpStatistics column definitions are as follows

1. Sample: folder name of VCF file
2. allPos: length of FASTA file in base pairs (bp)
3. noCall: Number of positions with no call made as reported by GATK
4. discardedRefCall: Number of positions with a discarded reference call for not passing genotyping or coverage thresholds
5. discardedVarCall: Number of positions with a discarded variant call for not passing genotyping or coverage thresholds
6. filteredVarCall: Number of positions with discarded calls based on user filter list
7. unhandledGenotype: Number of positions with discarded calls for having more than two possible alleles (e.g. Ref: A, ALT: G,T)
8. refCall: Number of reference calls made
9. SNP Calls (all): Total number of non-reference homozygous and heterozgyous calls made
10. SNP Calls (het): Total number of non-reference calls not passing user-supplied heterozygosity/homozygosity thresholds
11. coverage(fold): Average number of reads covering final calls
12. coverage(percent): Percent coverage of all positions with final calls

Even if ‘EMIT_ALL_SITES’ is turned on, GATK will ignore any non-ACGT positions in the reference entirely (e.g. Ns), and will not export that position in the VCF file. Thus, refCall + SNP Calls (all) may not match allPos - noCall - discardedRefCall - discardedVarCall - filteredVarCall - unhandledGenotype as these positions are not supplied to MultiVCFAnalyzer’. You can check for this by checking the discrepancy of the two previous calculations is equal across every sample.

FAQs

How do I restrict to only ‘homozygous’ SNPs?

Set both homozygous and heterozygous frequency to the same value. Only ACTGs passing your thresholds will then be reported.

How do I increase the amount of memory?

Increase the amount of memory allocated to java with the -Xmx parameter (here 16 gigabytes)

java -Xmx16G -jar MultiVCFAnalyzer_X-XX-X.jar <OPTIONS>

How to build the JAR file from source?

If you want to create a JAR file and use the tool, simply install Gradle and follow this:

git clone https://github.com/alexherbig/MultiVCFAnalyzer
cd MultiVCFAnalyzer
gradle build

This will create a folder build/libs/ that contains the compiled JAR file automatically for you. You can then use the tool as described above using:

java -jar build/libs/MultiVCFAnalyzer-VERSION.jar [...]