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readlen
and (if the
variant calling should consider quality) an appropriate
high_base_quality
cutoff. Passing a which
argument
allows computing on only a subregion of the genome.
"tallyVariants"(x, param = TallyVariantsParam(...), ..., BPPARAM = defaultBPPARAM())
"tallyVariants"(x, ...)
"tallyVariants"(x, ...)
TallyVariantsParam(genome, read_pos_breaks = NULL, high_base_quality = 0L, minimum_mapq = 13L, variant_strand = 1L, ignore_query_Ns = TRUE, ignore_duplicates = TRUE, mask = GRanges(), keep_extra_stats = TRUE, read_length = NA_integer_, read_pos = !is.null(read_pos_breaks), high_nm_score = NA_integer_, ...)
BamFile
or
BamFileList
object. If the latter, the tallies are computed
separately for each file, and the results are stacked with
stackSamples
into a single
VRanges
.
BamTallyParam
, typically constructed with
TallyVariantsParam
, see arguments below.
tallyVariants
, arguments to pass to
TallyVariantsParam
, listed below. For
TallyVariantsParam
, arguments to pass to
BamTallyParam
.
GmapGenome
or
something coercible to one.
NULL
), qaVariants
will use it during filtering.
callVariants
will
use the high quality counts in the likelihood ratio test. Note that
bam_tally
will shift your quality scores by 33 no matter what
type they are. If Illumina (pre 1.8) this will result in a range of
31-71. If Sanger/Illumina1.8 this will result in a range of
0-40/41. The default counts all bases as high quality. We typically
use 56 for old Illumina, 23 for Sanger/Illumina1.8.
gsnap
.
FALSE
. If
it is FALSE
, beware of low quality datasets returning
enormous results.
GRanges
specifyin a mask; all variants falling
within the mask are discarded.
NA
,
counts of reads with NM (mismatch count)
score equal to or greater are returned in the
count.high.nm
and count.high.nm.ref
columns.
BiocParallelParam
object specifying the resources and strategy for parallelizing the
tally operation over the chromosomes.
tallyVariants
, the tally GRanges
.For TallyVariantsParam
, an object with parameters suitable for
variant calling.
tally.param <- TallyVariantsParam(gmapR::TP53Genome(),
high_base_quality = 23L,
which = gmapR::TP53Which())
bams <- LungCancerLines::LungCancerBamFiles()
raw.variants <- tallyVariants(bams$H1993, tally.param)
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