If you use slivar
, please cite the paper
slivar is a set of command-line tools that enables rapid querying and filtering of VCF files. It facilitates operations on trios and groups and allows arbitrary expressions using simple javascript.
- annotate variants with gnomad allele frequencies from combined exomes + whole genomes at > 30K variants/second using only a 1.5GB compressed annotation file.
- call denovo variants with a simple expression that uses mom, dad, kid labels that is applied to each trio in a cohort (as inferred from a pedigree file).
kid.het && mom.hom_ref && dad.hom_ref && kid.DP > 10 && mom.DP > 10 && dad.DP > 10
- define and filter on arbitrary groups with labels. For example, 7 sets of samples each with 1 normal and 3 tumor time-points:
normal.AD[0] = 0 && tumor1.AB < tumor2.AB && tumor2.AB < tumor3.AB
- filter variants with simple expressions:
variant.call_rate > 0.9 && variant.FILTER == "PASS" && INFO.AC < 22 && variant.num_hom_alt == 0
- see using slivar for rare disease research
slivar has sub-commands:
- expr: filter and/or annotate with INFO, trio, sample, group expressions
- make-gnotate: make a compressed zip file of annotations for use by slivar
- compound-hets: true compound hets using phase-by-inheritance within gene annotations
- Installation
- QuickStart
- Commands
- expr
- compound-het
- tsv
- duo-del
- ddc
- Attributes
- How it works
- Gnotation Files
get the latest binary from: https://github.com/brentp/slivar/releases/latest
slivar_static
does not depend on any libraries and should work on any 64 bit linux system.
slivar_shared
will require libhts.so (from htslib) to be in the usual places or in a directory indicated in LD_LIBRARY_PATH
.
or use via docker from: brentp/slivar:latest
To get started quickly, grab a static binary for the latest release and then follow this example
So for hg38:
vcf=/path/to/your/vcf.vcf.gz
ped=/path/to/your/pedigree.ped
wget https://github.com/brentp/slivar/releases/download/v0.2.8/slivar
chmod +x ./slivar
wget https://raw.githubusercontent.com/brentp/slivar/master/js/slivar-functions.js
wget https://slivar.s3.amazonaws.com/gnomad.hg38.genomes.v3.fix.zip
# example command
./slivar expr --js slivar-functions.js -g gnomad.hg38.genomes.v3.fix.zip \
--vcf $vcf --ped $ped \
--info "INFO.gnomad_popmax_af < 0.01 && variant.FILTER == 'PASS'" \
--trio "example_denovo:denovo(kid, dad, mom)" \
--family-expr "denovo:fam.every(segregating_denovo)" \
--trio "custom:kid.het && mom.het && dad.het && kid.GQ > 20 && mom.GQ > 20 && dad.GQ > 20" \
--pass-only
The pedigree format is explained here
expr
allows filtering on (abstracted) trios and groups. For example, given a VCF (and ped/fam file) with
100 trios, slivar
will apply an expression with kid
, mom
, dad
identifiers to each trio that it automatically
extracts.
expr
can also be used, for example to annotate with population allele frequencies from a gnotate
file without
any sample filtering. See the wiki for more detail and the gnotate
section for gnotation files that we distribute for slivar
.
expr
commands are quite fast, but can be parallelized using pslivar.
when --trio is used, slivar
finds all trios in a VCF, PED pair and let's the user specify an expression with indentifiers
of kid
, mom
, dad
that is applied to each possible trio. For example, a simple expression to call
de novo variants:
variant.FILTER == 'PASS' && \ #
variant.call_rate > 0.95 && \ # genotype must be known for most of cohort.
INFO.gnomad_af < 0.001 && \ # rare in gnomad (must be in INFO [but see below])
kid.het && mom.hom_ref && dad.hom_ref && \ # also unknown
kid.DP > 7 && mom.DP > 7 && dad.DP > 7 && \ # sufficient depth in all
(mom.AD[1] + dad.AD[1]) == 0 # no evidence for alternate in the parents
This requires passing variants that are rare in gnomad that have the expected genotypes and do
not have any alternate evidence in the parents. If there are 200 trios in the ped::vcf
given, then this expression
will be tested on each of those 200 trios.
When trios are not sufficient, use Family Expressions which allow more heterogeneous family structures.
The expressions are javascript so the user can make these as complex as needed.
slivar expr \
--pass-only \ # output only variants that pass one of the filters (default is to output all variants)
--vcf $vcf \
--ped $ped \
# compressed zip that allows fast annotation so that `gnomad_af` is available in the expressions below.
--gnotate $gnomad_af.zip \
# any valid javascript is allowed in a file here. provide functions to be used below.
--js js/slivar-functions.js \
--out-vcf annotated.bcf \
# this filter is applied before the trio filters and can speed evaluation if it is stringent.
--info "variant.call_rate > 0.9" \
--trio "denovo:kid.het && mom.hom_ref && dad.hom_ref \
&& kid.AB > 0.25 && kid.AB < 0.75 \
&& (mom.AD[1] + dad.AD[1]) == 0 \
&& kid.GQ >= 20 && mom.GQ >= 20 && dad.GQ >= 20 \
&& kid.DP >= 12 && mom.DP >= 12 && dad.DP >= 12" \
--trio "informative:kid.GQ > 20 && dad.GQ > 20 && mom.GQ > 20 && kid.alts == 1 && \
((mom.alts == 1 && dad.alts == 0) || (mom.alts == 0 && dad.alts == 1))" \
--trio "recessive:trio_autosomal_recessive(kid, mom, dad)"
Note that slivar
does not give direct access to the genotypes, instead exposing
hom_ref
, het
, hom_alt
and unknown
or via alts
where 0 is homozygous reference, 1 is heterozygous, 2 is
homozygous alternate and -1 when the genotype is unknown. It is recommended to decompose a VCF before sending to slivar
Here it is assumed that trio_autosomal_recessive
is defined in slivar-functions.js
; an example implementation of that
and other useful functions is provided here.
Note that it's often better to use --family-expr instead as it's more flexible than trio expressions.
Trios are a nice abstraction for cohorts consisting of only trios, but for more general uses, there is --family-expr
for example, given either a duo, or a quartet, we can find variants present only in affected samples with:
--family-expr "aff_only:fam.every(function(s) { return s.het == s.affected && s.hom_ref == !s.affected && s.GQ > 5 })"
Note that this does not explicitly check for transmission or non-transmission between parents and off-spring
so it is less transparent than the trio
mode, but more flexible.
A trio
is a special-case of a group
that can be inferred from a pedigree. For more specialized use-cases, a group
can be
specified. For example we could, instead of using --trio
, use a group
file like:
#kid mom dad
sample1 sample2 sample3
sample4 sample5 sample6
sample7 sample8 sample9
Where, here we have specified 3 trios below a header with their "labels". This can be accomplished using --trio
, but we can
for example specify quartets like this:
#kid mom dad sibling
sample1 sample2 sample3 sample10
sample4 sample5 sample6 sample11
sample7 sample8 sample9 sample12
where sample10
will be available as "sibling" in the first family and an expression like:
kid.alts == 1 && mom.alts == 0 && dad.alts == 0 and sibling.alts == 0
could be specified and it would automatically be applied to each of the 3 families.
Another example could be looking at somatic variants with 3 samples, each with a normal and 4 time-points of a tumor:
#normal tumor1 tumor2 tumor3 tumor4
ss1 ss8 ss9 ss10 ss11
ss2 ss12 ss13 ss14 ss15
ss3 ss16 ss17 ss18 ss19
where, again each row is a sample and the ID's (starting with "ss") will be injected for each sample to allow a single expression like:
normal.hom_ref && normal.DP > 10 \
&& tumor1.AB > 0 \
&& tumor1.AB < tumor2.AB \
&& tumor2.AB < tumor3.AB \
&& tumor3.AB < tumor4.AB
to find a somatic variant that has increasing frequency (AB is allele balance) along the tumor time-points. More detail on groups is provided here
Users can specify a boolean expression that is tested against each sample
using e.g.:
--sample-expr "hi_quality:sample.DP && sample.GQ > 10"
Each sample that passes this expression will be have its sample id appended to the INFO field of hi_quality
which
is added to the output VCF.
Users can make their own gnotate
files like:
slivar make-gnotate --prefix gnomad \
--field AF_popmax:gnomad_popmax_af \
--field nhomalt:gnomad_num_homalt \
gnomad.exomes.r2.1.sites.vcf.gz gnomad.genomes.r2.1.sites.vcf.gz
this will pull AF_popmax
and nhomalt
from the INFO field and put them into gnomad.zip
as gnomad_popmax_af
and gnomad_num_homalt
respectively.
The resulting zip file will contain the union of values seen in the exome and genomes files with the maximum value for any intersection.
Note that the names (gnomad_popmax_af
and gnomad_num_homalt
in this case) should be chosen carefully as those will be the names added to the INFO of any file to be annotated with the resulting gnomad.zip
More information on make-gnotate
is in the wiki
This command is used to find compound heterozygous variants (with phasing-by-inheritance) in trios. It is used after filtering to rare(-ish) heterozygotes.
See a full description of use here
NOTE that by default, this command limits to a subset of impacts; this is
adjustable with the --skip
flag. See more on the
wiki
This command is used to convert a filtered and annotated VCF to a TSV (tab-separated value file) for final examination. An example use is:
slivar tsv -p $ped \
-s denovo -s x_recessive \
-c CSQ \
-i gnomad_popmax_af -i gnomad_nhomalt \
-g gene_desc.txt -g clinvar_gene_desc.txt \
$vcf > final.tsv
where denovo
and x_recessive
indicate the INFO fields that contain lists of samples (as added by slivar) that should be extracted.
and gnomad_popmax_af
and gnomad_nhomalt
are pulled from the INFO field.
The -c
arugment (CSQ) tells slivar
that it can get gene, transcript and impact information from the CSQ field in the INFO.
And the -g
arguments are tab-delimited files of gene -> description where the description is added to the text output for quick inspection.
Run slivar tsv
without any arguments for examples on how to create these for pLI and clinvar.
Also see the wiki
slivar duo-del finds structural deletions in parent-child duos using non-transmission of alleles. this can work to find deletions in exome data using genotypes, thereby avoiding the problems associated with depth-based CNV calling in exomes.
see: https://github.com/brentp/slivar/wiki/finding-deletions-in-parent-child-duos
slivar ddc
is a tool to discover data-driven cutoffs from a VCF and pedigree information.
It generates an interative VCF so a user can see how mendelian violation and transmissions
are effected by varying cutoffs for values in the INFO and FORMAT fields.
See the wiki for more details.
-
anything in the INFO is available as e.g. INFO.DP
-
INFO.impactful which, if CSQ (VEP), BCSQ (bcftools), or ANN (snpEff) is present indicates if the highest impact is "impactful". see wiki and
INFO.genic
which includes other gene impacts likesynonymous
. AlsoINFO.highest_impact_order
explained in the wiki -
variant consequences such as in INFO.CSQ can be parsed and used as object as described here
-
if FORMAT.AB is not present, it is added so one can filter with kid.AB > 0.25 && kid.AB < 0.75
-
variant attributes are:
CHROM
,POS
,start
,end
,ID
,REF
,ALT
,QUAL
,FILTER
,is_multiallelic
-
calculated variant attributes include:
aaf
,hwe_score
,call_rate
,num_hom_ref
,num_het
,num_hom_alt
,num_unknown
-
numeric and flag sample attributes (via
kid
,mom
,dad
) included in the FORMAT. available as e.g.kid.AD[1]
,mom.DP
, etc. -
if the environment variable
SLIVAR_FORMAT_STRINGS
is not empty, then string sample fields will be available. these are not populated by default as they are used less often and impact performance. -
sample attributes for
hom_ref
,het
,hom_alt
,unknown
which are synonums forsample.alts
of 0, 1, 2, -1 respectively. -
sample attributes from the ped for
affected
,phenotype
,sex
,id
are available as, e.g. kid.sex. phenotype is a string taken directly from the pedigree file while affected is a boolean. -
sample relations are available as
mom
,dad
,kids
.mom
anddad
will be undefined if not available and kids will be an empty array. -
a
VCF
object containsCSQ
,BCSQ
,ANN
if those are present in the header (from VEP, BCFTOOLS, SnpEFF). The content is a list indicating the order of entries in the field e.g.["CONSEQUENCE", "CODONS","AMINO_ACIDS", "GENE", ...]
slivar
embeds the duktape javascript engine to allow the user to specify expressions.
For each variant, each trio (and each sample), it fills the appropriate attributes
. This can be intensive for
VCFs with many samples, but this is done as efficiently as possible such that slivar
can evaluate 10's of
thousand of variants per second even with dozens of trios.
slivar outputs a summary table with rows of samples and columns of expression where each value
indicates the number of variants that passed the expression in each sample. By default, this goes to STDOUT
but if the environment variable SLIVAR_SUMMARY_FILE
is set, slivar
will write the summary to that file
instead.
Users can create their own gnotation files with slivar make-gnotate
, but we provide:
-
gnomad for hg37 with AF popmax, numhomalts (total and controls only) here
-
gnomad for hg38 (v3) genomes here
-
lifted gnomad exomes+genomes for hg38 with AF popmax, numhomalts (updated in release v0.1.2) here
-
spliceai scores (maximum value of the 4 scores in spliceai) here
-
topmed allele frequencies (via dbsnp) these can be used with
INFO.topmed_af
. Useful when analyzing data in hg38 because some variants in hg38 are not visible in GRCh37
The available fields can be seen with, for example:
$ unzip -l gnomad.hg38.v2.zip | grep -oP "gnotate-[^.]+" | sort -u
gnotate-gnomad_nhomalt
gnotate-gnomad_nhomalt_controls
gnotate-gnomad_popmax_af
gnotate-gnomad_popmax_af_controls
gnotate-variant
indicating that INFO.gnomad_nhomalt
, INFO.gnomad_nhomalt_controls
, INFO.gnomad_popmax_af
and INFO.gnomad_popmax_af_controls
will be
the fields after they are added to the INFO.