scripts

Subset dbVar variant to one chromosome

We used a subset of the data to develop the app: variants and genes in chr21. The different dbVar versions (GRCh37 and GRCh38) and genes were subset as shown in the extract-chr21-genes-variants.ipynb notebook.

Allele frequency

Extract allele frequency from gnomAD-SV

The AF_extract.py script reads a gnomAd_SV vcf file and extracts the allele frequencies of all variants and outputs them into a CSV file

Usage:

python AF_extract.py -vcf <path to the gnomAD_SV vcf file> -out <path to the output file>

Match allele frequencies with dbVar SVs

The gnomad-variants-af.ipynb notebook shows how we matched variants in dbVar (GRCh37) and the gnomAD-SV. Briefly: 50% reciprocal overlap per SV type.

R/Bioconductor packages used include:

• GenomicRanges
• dplyr

Variants overlapping genes and gene impact

Script to extract information for one gene

We used annotGeneSV.R (at first linkGeneWithSV.R) to read variants from dbVar and Gencode annotation and extract relevant information.

Overlapping all genes with all variants in chr21

The variant-gene-overlap.ipynb notebook shows how we overlapped variants in chr21 with Gencode to extract gene impact information.

R/Bioconductor packages used include:

• rtracklayer
• GenomicRanges
• dplyr

Overlap dbVar SVs with SNVs of known clinical significance

We overlapped SVs with ClinVar using bedtools. The overlaps were then summarize in a TSV file using code in the make-misc-tsvs.ipynb notebook.

Annotate dbVar SVs with clinical significance

We used study nstd102 that contain clinical SVs. The code to make the TSV for this annotation is part of the make-misc-tsvs.ipynb notebook.