`generateBedReport`, `generateAmpliconReport`, `generateCaptureReport` -- these functions match BAM reads to the set of genomic locations and return the fraction of reads with an average methylation level passing an arbitrary threshold.
generateAmpliconReport(
bam,
bed,
report.file = NULL,
zero.based.bed = FALSE,
match.tolerance = 1,
threshold.reads = TRUE,
threshold.context = c("CG", "CHG", "CHH", "CxG", "CX"),
min.context.sites = 2,
min.context.beta = 0.5,
max.outofcontext.beta = 0.1,
...,
gzip = FALSE,
verbose = TRUE
)
generateCaptureReport(
bam,
bed,
report.file = NULL,
zero.based.bed = FALSE,
match.min.overlap = 1,
threshold.reads = TRUE,
threshold.context = c("CG", "CHG", "CHH", "CxG", "CX"),
min.context.sites = 2,
min.context.beta = 0.5,
max.outofcontext.beta = 0.1,
...,
gzip = FALSE,
verbose = TRUE
)
generateBedReport(
bam,
bed,
report.file = NULL,
zero.based.bed = FALSE,
bed.type = c("amplicon", "capture"),
match.tolerance = 1,
match.min.overlap = 1,
threshold.reads = TRUE,
threshold.context = c("CG", "CHG", "CHH", "CxG", "CX"),
min.context.sites = 2,
min.context.beta = 0.5,
max.outofcontext.beta = 0.1,
...,
gzip = FALSE,
verbose = TRUE
)BAM file location string OR preprocessed output of
preprocessBam function. Read more about BAM file
requirements and BAM preprocessing at preprocessBam.
Browser Extensible Data (BED) file location string OR object of
class GRanges holding genomic coordinates for
regions of interest. The style of seqlevels of BED file/object must be the
same as the style of seqlevels of BAM file/object used.
file location string to write the BED report. If NULL
(the default) then report is returned as a
data.table object.
boolean defining if BED coordinates are zero based (default: FALSE).
integer for the largest difference between read's and
BED GRanges start or end positions during
matching of amplicon-based NGS reads (default: 1).
boolean defining if sequence reads should be thresholded before counting reads belonging to variant epialleles (default: TRUE). Disabling thresholding is possible but makes no sense in the context of this function, because all the reads will be assigned to the variant epiallele, which will result in VEF==1 (in such case `NA` VEF values are returned in order to avoid confusion). As thresholding is not recommended for long-read sequencing data, this function is not recommended for such data either.
string defining cytosine methylation context used for thresholding the reads:
"CG" (the default) -- within-the-context: CpG cytosines (called as zZ), out-of-context: all the other cytosines (hHxX)
"CHG" -- within-the-context: CHG cytosines (xX), out-of-context: hHzZ
"CHH" -- within-the-context: CHH cytosines (hH), out-of-context: xXzZ
"CxG" -- within-the-context: CG and CHG cytosines (zZxX), out-of-context: CHH cytosines (hH)
"CX" -- all cytosines are considered within-the-context, this effectively results in no thresholding
This option has no effect when read thresholding is disabled.
non-negative integer for minimum number of cytosines within the `threshold.context` (default: 2). Reads containing fewer within-the-context cytosines are considered completely unmethylated (thus belonging to the reference epiallele). This option has no effect when read thresholding is disabled.
real number in the range [0;1] (default: 0.5). Reads with average beta value for within-the-context cytosines below this threshold are considered completely unmethylated (thus belonging to the reference epiallele). This option has no effect when read thresholding is disabled.
real number in the range [0;1] (default: 0.1). Reads with average beta value for out-of-context cytosines above this threshold are considered completely unmethylated (thus belonging to the reference epiallele). This option has no effect when read thresholding is disabled.
other parameters to pass to the
preprocessBam function.
Options have no effect if preprocessed BAM data was supplied as an input.
boolean to compress the report (default: FALSE).
boolean to report progress and timings (default: TRUE).
integer for the smallest overlap between read's and
BED GRanges start or end positions during
matching of capture-based NGS reads (default: 1). If read matches two or more
BED genomic regions, only the first match is taken (input
GRanges are not sorted internally).
character string for the type of assay that was used to produce sequencing reads:
"amplicon" (the default) -- used for amplicon-based next-generation
sequencing when exact coordinates of sequenced fragments are known.
Matching of reads to genomic ranges are then performed by the read's start
or end positions, either of which should be no further than
`match.tolerance` bases away from the start or end position of genomic
ranges given in BED file/GRanges object
"capture" -- used for capture-based next-generation sequencing when
reads partially overlap with the capture target regions. Read is considered
to match the genomic range when their overlap is more or equal to
`match.min.overlap`. If read matches two or more BED genomic regions, only
the first match is taken (input GRanges are
not sorted internally)
data.table object containing VEF report for
BED GRanges or NULL if report.file was
specified. If BAM file contains reads that would not match to any of BED
GRanges, the last row in the report will
contain information on such reads (with seqnames, start and end equal to NA).
The report columns are:
seqnames -- reference sequence name
start -- start of genomic region
end -- end of genomic region
width -- width of genomic region
strand -- strand
... -- other columns that were present in BED or metadata columns of
GRanges object
nreads+ -- number of reads (pairs) mapped to the forward ("+") strand
nreads- -- number of reads (pairs) mapped to the reverse ("-") strand
VEF -- frequency of reads passing the threshold
Functions report hypermethylated variant epiallele frequencies (VEF) per genomic region of interest using BAM and BED files as input. Reads (for paired-end sequencing alignment files - read pairs as a single entity) are matched to genomic locations by exact coordinates (`generateAmpliconReport` or `generateBedReport` with an option bed.type="amplicon") or minimum overlap (`generateCaptureReport` or `generateBedReport` with an option bed.type="capture") -- the former to be used for amplicon-based NGS data, while the latter -- for the capture-based NGS data. The function's logic is explained below.
Let's suppose we have a BAM file with four reads, all mapped to the "+" strand of chromosome 1, positions 1-16. The genomic range is supplied as a parameter `bed = as("chr1:1-100", "GRanges")`. Assuming the default values for the thresholding parameters (threshold.reads = TRUE, threshold.context = "CG", min.context.sites = 2, min.context.beta = 0.5, max.outofcontext.beta = 0.1), the input and results will look as following:
| methylation string | threshold | explained |
| ...Z..x+.h..x..h. | below | min.context.sites < 2 (only one zZ base) |
| ...Z..z.h..x..h. | above | pass all criteria |
| ...Z..z.h..X..h. | below | max.outofcontext.beta > 0.1 (1XH / 3xXhH = 0.33) |
| ...Z..z.h..z-.h. | below | min.context.beta < 0.5 (1Z / 3zZ = 0.33) |
Only the second read will satisfy all of the thresholding criteria, leading to the following BED report (given that all reads map to chr1:+:1-16):
| seqnames | start | end | width | strand | nreads+ | nreads- | VEF |
| chr1 | 1 | 100 | 100 | * | 4 | 0 | 0.25 |
Please note, that read thresholding by an average methylation level
(as explained above) makes little sense for long-read sequencing alignments,
as such reads can cover multiple regions with very different DNA methylation
properties. Instead, please use extractPatterns, limiting
pattern output to the region of interest only.
preprocessBam for preloading BAM data,
generateCytosineReport for methylation statistics at the level
of individual cytosines, generateVcfReport for evaluating
epiallele-SNV associations, extractPatterns for exploring
methylation patterns, generateBedEcdf for analysing the
distribution of per-read beta values, and `epialleleR` vignettes for the
description of usage and sample data.
GRanges class for working with genomic ranges,
seqlevelsStyle function for getting or setting
the seqlevels style.
# amplicon data
amplicon.bam <- system.file("extdata", "amplicon010meth.bam",
package="epialleleR")
amplicon.bed <- system.file("extdata", "amplicon.bed",
package="epialleleR")
amplicon.report <- generateAmpliconReport(bam=amplicon.bam,
bed=amplicon.bed)
#> Reading BED file
#> [0.007s]
#> Checking BAM file:
#> short-read, paired-end, name-sorted alignment detected
#> Reading paired-end BAM file
#> [0.004s]
#> Thresholding reads
#> [0.000s]
#> Preparing amplicon report
#> [0.014s]
# capture NGS
capture.bam <- system.file("extdata", "capture.bam",
package="epialleleR")
capture.bed <- system.file("extdata", "capture.bed",
package="epialleleR")
capture.report <- generateCaptureReport(bam=capture.bam, bed=capture.bed)
#> Reading BED file
#> [0.008s]
#> Checking BAM file:
#> short-read, paired-end, name-sorted alignment detected
#> Reading paired-end BAM file
#> [0.013s]
#> Thresholding reads
#> [0.001s]
#> Preparing capture report
#> [0.013s]
# generateAmpliconReport and generateCaptureReport are just aliases
# of the generateBedReport
bed.report <- generateBedReport(bam=capture.bam, bed=capture.bed,
bed.type="capture")
#> Reading BED file
#> [0.007s]
#> Checking BAM file:
#> short-read, paired-end, name-sorted alignment detected
#> Reading paired-end BAM file
#> [0.013s]
#> Thresholding reads
#> [0.001s]
#> Preparing capture report
#> [0.013s]
identical(capture.report, bed.report)
#> [1] TRUE