vembrane 0.3.2

Filter VCF/BCF files with Python expressions.

vembrane: variant filtering using python expressions

Vembrane allows to simultaneously filter variants based on any INFO field, CHROM, POS, REF, ALT, QUAL, and the annotation field ANN. When filtering based on ANN, annotation entries are filtered first. If no annotation entry remains, the entire variant is deleted.

Filter expression

The filter expression can be any valid python expression that evaluates to bool. However, functions and symbols available have been restricted to the following:

• all, any
• abs, len, max, min, round, sum
• enumerate, filter, iter, map, next, range, reversed, sorted, zip
• dict, list, set, tuple
• bool, chr, float, int, ord, str
• Any function or symbol from math
• Regular expressions via re

Available fields

The following VCF fields can be accessed in the filter expression:

Name	Type	Interpretation	Example expression
INFO	Dict[str, Any¹]	INFO field -> Value	INFO["DP"] > 0
ANN	Dict[str, Any²]	ANN field -> Value	ANN["Gene_Name"] == "CDH2"
CHROM	str	Chromosome Name	CHROM == "chr2"
POS	int	Chromosomal position	24 < POS < 42
ID	str	Variant ID	ID == "rs11725853"
REF	str	Reference allele	REF == "A"
ALT	List[str]	Alternative alleles	"C" in ALT or ALT[0] == "G"
QUAL	float	Quality	QUAL >= 60
FILTER
FORMAT	Dict[str, Dict[str, Any¹]]	Format -> (Sample -> Value)	FORMAT["DP"][SAMPLES[0]] > 0
SAMPLES	List[str]	[Sample]	"Tumor" in SAMPLES

¹ depends on type specified in VCF header

² for the usual snpeff and vep annotations, custom types have been specified; any unknown ANN field will simply be of type str. If something lacks a custom parser/type, please consider filing an issue in the issue tracker.

Examples

• Only keep annotations and variants where gene equals "CDH2" and its impact is "HIGH":

  vembrane 'ANN["Gene_Name"] == "CDH2" and ANN["Annotation_Impact"] == "HIGH"' variants.bcf
  

• Only keep variants with quality at least 30:

  vembrane 'QUAL >= 30' variants.vcf
  

• Only keep annotations and variants where feature (transcript) is ENST00000307301:

  vembrane 'ANN["Feature"] == "ENST00000307301"' variants.bcf
  

• Only keep annotations and variants where protein position is less than 10:

  vembrane 'ANN["Protein"].start < 10' variants.bcf
  

• Only keep variants where mapping quality is exactly 60:

  vembrane 'INFO["MQ"] == 60' variants.bcf
  

• Only keep annotations and variants where consequence contains the word "stream" (matching "upstream" and "downstream"):

  vembrane 're.search("stream", ANN["Consequence"])' variants.vcf
  

• Only keep annotations and variants where CLIN_SIG contains "pathogenic", "likely_pathogenic" or "drug_response":

  vembrane 'any(entry in ANN["CLIN_SIG"] for entry in ("pathogenic", "likely_pathogenic", "drug_response"))' variants.vcf
  

Custom ANN types

vembrane parses the following annotation fields to a custom type:

• (snpeff) cDNA.pos / cDNA.length, CDS.pos / CDS.length and AA.pos / AA.length are re-exposed as cDNA, CDS and AA respectively with properties start, end and length, e.g. can be accessed like this: ANN["cDNA"].start
• (vep) cDNA_position, CDS_position and Protein_position are re-exposed as cDNA, CDS and Protein respectively with properties start, end and length, e.g. can be accessed like this: ANN["cDNA"].start
• CLIN_SIG is split at '&' into a list of entries

Any unknown annotation field will be left as is.

Missing values in annotations

If a certain annotation field lacks a value, it will be replaced with the special value of NA. Comparing with this value will always result in False, e.g. ANN["cDNA"].start > 0 will always evaluate to False if there was no value in the "cDNA.pos / cDNA.length" field of (snpeff) ANN (otherwise the comparison will be carried out with the usual semantics). One way to handle optional values is by asserting that the field is not None, e.g ID and "foo" in ID.

Development

pre-commit hooks

Since we enforce code formatting with black by checking for that in CI, we can avoid "fmt" commits by ensuring formatting is done upon comitting changes:

1. make sure pre-commit is installed on your machine / in your env (should be available in pip, conda, archlinux repos, ...)
2. run pre-commit install. This will activate pre-commit hooks to your local .git

Now when calling git commit, your changed code will be formatted with black, checked withflake8, get trailing whitespace removed and trailing newlines added (if needed)

Authors

• Marcel Bargull (@mbargull)
• Jan Forster (@jafors)
• Till Hartmann (@tedil)
• Johannes Köster (@johanneskoester)
• Elias Kuthe (@eqt)
• Felix Mölder (@felixmoelder)
• Christopher Schröder (@christopher-schroeder)