PharmCAT VCF Preprocessor

The PharmCAT VCF Preprocessor is a script that can preprocess VCF files for PharmCAT (see PharmCAT's VCF Requirements).

This tool will:

  1. Strip out PGx positions that PharmCAT does not care about.
  2. Automatically download the necessary Human Reference Genome Sequence FASTA and index files from the NIH FTP site if they are not provided.
  3. Perform VCF normalization - a standardization process that turns VCF into a parsimonious, left-aligned variant representation format (as discussed in Unified Representation of Genetic Variants by Tan, Abecasis, and Kang).
  4. Normalize the multiallelic variant representation to PharmCAT's expectation.
  5. Optionally filter out data for a subset of samples if requested.

By default, the PharmCAT VCF preprocessing produces two types of output:

  1. A PharmCAT-ready VCF file
  2. A report of missing pharmacogenomics core allele defining positions in user's input

Prerequisites

Install the Software

You can skip this if are running PharmCAT in Docker.

  1. You will need python 3.10.14 or higher
  2. You will need the following bioinformatic tools:
  3. Download the preprocessor tar file from our releases page.
    • Untar the file
  4. You will need the following python dependencies:
    • colorama >= 0.4.6
    • pandas >= 1.5.1
    • packaging ~= 21.3

To install the necessary python packages, run the following code:

$ pip3 install -r requirements.txt

You can find requirements.txt in the preprocessor tar file you downloaded.

How to run the PharmCAT VCF Preprocessor

Below you will find a detailed introduction to the PharmCAT VCF Preprocessor. We have put together interactive materials on the PharmCAT tutorial GitHub repo.

Command line

To normalize and prepare a VCF file, run the following code substituted with proper arguments/inputs:

$ python3 pharmcat_vcf_preprocessor.py -vcf path/to/file.vcf(.bgz)

Mandatory argument: -vcf.

-vcf
Path to a single VCF file or a file containing the list of VCF file paths (one per line), sorted by chromosome position. All VCF files must have the same set of samples. Use this when data for a sample has been split among multiple files (e.g. VCF files from large cohorts, such as UK Biobank). Input VCF files must at least comply with Variant Call Format (VCF) Version >= 4.2.

VCF files can have more than 1 sample and should be bgzip compressed. If not bgzip compressed, they will be automatically bgzipped.

Example valid list file:

  chr1_set1.vcf
  chr1_set2.vcf
  chr2_set1.vcf
  chr2_set2.vcf
  ...

Example invalid list file:

  chr3_set2.vcf
  chr2_set2.vcf
  chr1_set1.vcf
  chr1_set2.vcf
  ...

Optional Arguments

-S <txt_file>
or --sample-file <txt_file>
The list of samples to be processed and prepared for PharmCAT. The file should contain one sample per line.
-s <samples>
or --samples <samples>
A comma-separated list of sample IDs.
-o <dir>
or --output-dir <dir>
Directory to save preprocessed VCF to. Default is the parent directory of the input VCF.
-bf <name>
or --base-filename <name>
Prefix of the output VCF files. Default is the input base file name plus sample IDs.
-k
or --keep-intermediate-files
This option will help you save useful intermediate files, for example, a normalized, multiallelic VCF named <base_input_file_name>.pgx_regions.normalized.multiallelic.vcf.bgz, which will include all PGx regions from the first position to the last one in each chromosome as listed in the reference PGx VCF.
-ss
or --single-sample
Generate 1 VCF file per sample.
-0
or --missing-to-ref
This option will add missing PGx positions to the output. Missing PGx positions are those whose genotypes are all missing "./." in every single sample.
  • This option will not convert "./." to "0/0" if any other sample has non-missing genotype at this position as these missing calls are likely missing for good reasons.
  • This SHOULD ONLY BE USED if you are sure your data is reference at the missing positions instead of unreadable/uncallable at those positions. Running PharmCAT with positions as missing vs reference can lead to different results.
-c
or --concurrent-mode
Enable concurrent mode. This defaults to using one less than the number of CPU cores available. Note that this is only useful if processing many files/samples. With only a few files/samples, the overhead of using concurrent mode is more than the benefit it may provide.
-cp <num processes>
or --max-concurrent-processes <num processes>
The maximum number of processes to use if concurrent mode is enabled.
-v
or --verbose
Print verbose messages.
-V
or --version
Display PharmCAT version.

Advanced Arguments

These options allow you to override default locations if the preprocessor cannot find its dependencies.

-refVcf <vcf_file>
or --reference-pgx-vcf <vcf_file>
A sorted, compressed VCF of PGx core allele defining positions used by PharmCAT. By default, the preprocessor will look for pharmcat_positions.vcf.bgz under the current working directory. You can find this VCF in the pharmcat_preprocessor-<release_version>.tar.gz available from the PharmCAT GitHub releases page.
-refFna <fna_file>
or --reference-genome <fna_file>
The GRCh38.p13 FASTA file. The FASTA file can be either decompressed or compressed but has to be indexed (.fai and, in addition, .gzi for the compressed file). We recommended the compressed reference genome FASTA file for the sake of storage. These mandatory files will be automatically downloaded (~0.9 GB) to the same directory as the reference PGx VCF file (-refVcf) if not provided by user (see Notes for details).
-R
or --retain-specific-regions
Retain the genomic regions specified by '-refRegion'
-refRegion <bed_file>
or --reference-regions-to-retain <bed_file>
A sorted bed file of specific PGx regions to retain. Must be used with the -R argument.
-bcftools </path/to/bcftools>
or --path-to-bcftools </path/to/bcftools>
bcftools must be installed. This argument is optional if bcftools is available in your PATH. If not, you can download and compile bcftools and provide the path to the bcftools program. Alternatively, set using the BCFTOOLS_PATH environment variable.
-bgzip </path/to/bgzip>
or --path-to-bgzip </path/to/bgzip>
bgzip must be installed. This argument is optional if bgzip is available in your PATH. If not, bgzip is a part of the htslib. You can download and compile it and provide the path to the bgzip program. Alternatively, set using the BGZIP_PATH environment variable.
-G
or --no-gvcf-check
Bypass the check of the gVCF file format.
  • This SHOULD ONLY BE USED if you are certain your data is not a gVCF.

Output

By default, the preprocessor will produce a (multi-sample) VCF named <base_filename>.preprocessed.vcf.bgz, which is ready to be used by PharmCAT.

All preprocessor output files will use the base filename of the input file unless otherwise specified using the -bf/--base-filename argument. For example, if the input file is "study.vcf", then the base filename is "study". If the input file is "biobank_files.txt" then the base filename is "biobank_files".

If there are multiple samples, and the -ss flag is provided, the preprocessor will produce one PharmCAT-ready VCF file per sample. The output files are named <base_filename>.<sample_id>.preprocessed.vcf

If there are missing PGx positions, it will also produce a report named <base_filename>.missing_pgx_var.vcf. This file only reports positions that are missing in all samples. If -0/--missing-to-ref is turned on, you can use this report to trace positions whose genotypes are missing in all samples (./.) in the original input but have now been added into the output VCF(s) as reference (0/0).

Tutorial

Case 1 - single-sample VCF

Imagine we have a VCF named "test_1.vcf.bgz" to be used in PharmCAT.

$ gunzip -c test_1.vcf.bgz
$ cat test_1.vcf
<...header truncated...>
#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	Sample_1
2	233760233	rs3064744	C	CAT	.	PASS	.	GT	1/0
2	233760233	rs3064744	CAT	C	.	PASS	.	GT	0/0
2	233760233	rs3064744	C	CATAT	.	PASS	.	GT	0/1
7	117548628	.	GTTTTTTTA	GTTTTTA	.	PASS	.	GT	0/1

Command to run the PharmCAT VCF Preprocessor:

$ python3 pharmcat_vcf_preprocessor.py -vcf test_1.vcf.bgz

The VCF Preprocessor will return two files in this test case.

  1. one named "test_1.preprocessed.vcf", which is a PharmCAT-ready VCF
  2. the other named "test_1.missing_pgx_var.vcf" as a report of missing PGx positions.

Note that the chr7 variant is not used in PharmCAT and was removed by the PharmCAT VCF Preprocessor.

$ cat test_1.preprocessed.vcf
<...header truncated...>
#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	Sample_1
chr2	233760233	rs3064744	CAT	C,CATATAT,CATAT	.	PASS	PX=UGT1A1	3/2

$ cat test_1.missing_pgx_var.vcf
<...header truncated...>
#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	PharmCAT
chr1	97078987	rs114096998	G	T	.	PASS	PX=DPYD	GT	0/0
chr1	97078993	rs148799944	C	G	.	PASS	PX=DPYD	GT	0/0
chr1	97079005	rs140114515	C	T	.	PASS	PX=DPYD	GT	0/0
<...truncated...>

Case 2 - multi-sample VCF

Imagine we have a VCF named "test_2.vcf.bgz" that has two samples.

$ gunzip -c test_2.vcf.bgz
<...header truncated...>
#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	Sample_1	Sample_2
1	97740414	rs72549309	AATGA	A	.	PASS	.	GT	1/0	0/1
2	233760233	rs3064744	C	CAT	.	PASS	.	GT	1/0	0/0
2	233760233	rs3064744	CAT	C	.	PASS	.	GT	0/0	0/1
2	233760233	rs3064744	C	CATAT	.	PASS	.	GT	0/1	1/0
7	117548628	.	GTTTTTTTA	GTTTTTA	.	PASS	.	GT	0/1	1/0
10	94942212	rs1304490498	AAGAAATGGAA	A	.	PASS	.	GT	1/0	0/1
13	48037826	rs777311140	G	GCGGG	.	PASS	.	GT	1/0	0/1
19	38499645	rs121918596	GGAG	G	.	PASS	.	GT	1/0	0/1
22	42130727	.	AG	A	.	PASS	.	GT	1/0	0/1
M	1555	.	G	A	PASS	.	GT	1/0	0/1

Command to run the PharmCAT VCF Preprocessor:

$ python3 pharmcat_vcf_preprocessor.py -vcf test_2.vcf.bgz

The VCF Preprocessor will return three (3) files in this test case:

  1. "test_2.preprocessed.vcf"
  2. "test_2.missing_pgx_var.vcf"

Note that the PharmCAT-ready VCFs will use the sample names from the input VCF.

$ cat test_2.preprocessed.vcf
<...header truncated...>
#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	Sample_1	Sample_2
chr1    97740410        rs72549309      GATGA   G       .       PASS    PX=DPYD       GT      1/0	0/1
chr2    233760233       rs3064744       CAT     C,CATATAT,CATAT .       PASS    PX=UGT1A1 GT      3/2	2/1
chr10   94942205        rs1304490498    CAATGGAAAGA     C       .       PASS    PX=CYP2C9     GT      1/0	0/1
chr13   48037825        rs777311140     C       CGCGG   .       PASS    PX=NUDT15     GT      1/0	0/1
chr19   38499644        rs121918596     TGGA    T       .       PASS    PX=RYR1       GT      1/0	0/1

$ cat test_2.missing_pgx_var.vcf
<...header truncated...>
#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	PharmCAT
chr1	97078987	rs114096998	G	T	.	PASS	PX=DPYD	GT	0/0
chr1	97078993	rs148799944	C	G	.	PASS	PX=DPYD	GT	0/0
chr1	97079005	rs140114515	C	T	.	PASS	PX=DPYD	GT	0/0
<...truncated...>

Case 3 - multi-sample VCF input and single-sample VCF ouputs

Given the same "test_2.vcf.bgz" as in the case 2, to obtain single-sample VCF files for each sample, run the following command:

$ python3 pharmcat_vcf_preprocessor.py -vcf test_2.vcf.bgz -ss

The VCF Preprocessor will return three (3) files in this test case:

  1. "test_2.Sample_1.preprocessed.vcf"
  2. "test_2.Sample_2.preprocessed.vcf"
  3. "test_2.missing_pgx_var.vcf"

Note that the PharmCAT-ready VCFs will use the sample names from the input VCF.

$ cat test_2.Sample_1.preprocessed.vcf
<...header truncated...>
#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	Sample_1
chr1    97740410        rs72549309      GATGA   G       .       PASS    PX=DPYD       GT      1/0
chr2    233760233       rs3064744       CAT     C,CATATAT,CATAT .       PASS    PX=UGT1A1 GT      3/2
chr10   94942205        rs1304490498    CAATGGAAAGA     C       .       PASS    PX=CYP2C9     GT      1/0
chr13   48037825        rs777311140     C       CGCGG   .       PASS    PX=NUDT15     GT      1/0
chr19   38499644        rs121918596     TGGA    T       .       PASS    PX=RYR1       GT      1/0

$ cat test_2.Sample_2.preprocessed.vcf
<...header truncated...>
#CHROM  POS     ID      REF     ALT     QUAL    FILTER  INFO    FORMAT  Sample_2
chr1    97740410        rs72549309      GATGA   G       .       PASS    PX=DPYD       GT      0/1
chr2    233760233       rs3064744       CAT     C,CATATAT,CATAT .       PASS    PX=UGT1A1 GT      2/1
chr10   94942205        rs1304490498    CAATGGAAAGA     C       .       PASS    PX=CYP2C9     GT      0/1
chr13   48037825        rs777311140     C       CGCGG   .       PASS    PX=NUDT15     GT      0/1
chr19   38499644        rs121918596     TGGA    T       .       PASS    PX=RYR1       GT      0/1

Explanation of INFO

The PharmCAT VCF Preprocessor updates the INFO on genetic variants that warrant further inspection. Please check positions with these INFO flags:

  1. PCATxREF
    1. The reference allele at this position does not match the PharmCAT reference allele at this PGx allele defining positions, which is based on the RefSeq reference human genome sequence on GRCh38. This cannot be fixed by normalizing and flipping the REF and ALT alleles in the PharmCAT VCF Preprocessor.
  2. PCATxALT
    1. The alternate allele at this position does not match the PharmCAT alternate alleles at this PGx allele defining positions.
  3. PCATxINDEL
    1. This position has an unexpected format for INDELs, especially an INDEL with <*> (an unspecified ALT allele ) or . (absence of alternative alleles). INDELs needs to be represented with a meaningful alternative allele.

Notes

PharmCAT uses GRCh38.p13. It is available through the NCBI RefSeq FTP site.

PharmCAT takes this file and prepares it for use with the following commands:

# curl -#fSL https://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/000/001/405/GCF_000001405.39_GRCh38.p13/GRCh38_major_release_seqs_for_alignment_pipelines/GCA_000001405.15_GRCh38_full_plus_hs38d1_analysis_set.fna.gz -o genomic.fna.gz
# gunzip genomic.fna.gz
# awk '{ if ((NR>1)&&($0~/^>/)) { printf("\n%s", $0); } else if (NR==1) { printf("%s", $0); } else { printf("\t%s", $0); } }' genomic.fna | grep -v "^>chr\S*_" - | tr "\t" "\n" > genomic.short.fna
# bgzip -c genomic.short.fna > reference.fna.bgz
# samtools faidx reference.fna.bgz
# tar -czvf GRCh38_reference_fasta.tar reference.fna.bgz reference.fna.bgz.fai reference.fna.bgz.gzi

PharmCAT makes this indexed FASTA files available on Zenodo.


PharmCAT is managed at Stanford University & University of Pennsylvania (NHGRI U24HG013077).