slicing: Query GDC for data slices

In GenomicDataCommons: NIH / NCI Genomic Data Commons Access

Description

This function returns a BAM file representing reads overlapping regions specified either as chromosomal regions or as gencode gene symbols.

Usage

slicing(uuid, regions, symbols, destination = file.path(tempdir(),
  paste0(uuid, ".bam")), overwrite = FALSE, progress = interactive(),
  token = gdc_token(), legacy = FALSE)

Arguments

uuid	character(1) identifying the BAM file resource
regions	character() vector describing chromosomal regions, e.g., c("chr1", "chr2:10000", "chr3:10000-20000") (all of chromosome 1, chromosome 2 from position 10000 to the end, chromosome 3 from 10000 to 20000).
symbols	character() vector of gencode gene symbols, e.g., c("BRCA1", "PTEN")
destination	character(1) default tempfile() file path for BAM file slice
overwrite	logical(1) default FALSE can destination be overwritten?
progress	logical(1) default interactive() should a progress bar be used?
token	character(1) security token allowing access to restricted data. Almost all BAM data is restricted, so a token is usually required. See https://gdc-docs.nci.nih.gov/API/Users_Guide/Authentication_and_Authorization/.
legacy	logical(1) whether or not to use the "legacy" archive, containing older, non-harmonized data.

Details

This function uses the Genomic Data Commons "slicing" API to get portions of a BAM file specified either using "regions" or using HGNC gene symbols.

Value

character(1) destination to the downloaded BAM file

Examples

 slicing("df80679e-c4d3-487b-934c-fcc782e5d46e",
        regions="chr17:75000000-76000000",
        token=gdc_token())

# Get 10 BAM files.
bamfiles = files() %>% 
           filter(data_format=='BAM') %>%
           results(size=10) %>% ids()

# Current alignments at the GDC are to GRCh38
library('TxDb.Hsapiens.UCSC.hg38.knownGene')
all_genes = genes(TxDb.Hsapiens.UCSC.hg38.knownGene)

first3genes = all_genes[1:3]
# remove strand info
strand(first3genes) = '*'

# We can get our regions easily now
as.character(first3genes)

# Use parallel downloads to speed processing
library(BiocParallel)
register(MulticoreParam())

fnames = bplapply(bamfiles, slicing, overwrite = TRUE,
                regions=as.character(first3genes))

# 10 BAM files
fnames

library(GenomicAlignments)
lapply(unlist(fnames), readGAlignments)

GenomicDataCommons documentation built on Nov. 8, 2020, 11:08 p.m.