Summarize information over genomic regions from any BED file
Source:R/summarize_regions.R
summarize_regions.RdRun summarizing functions on bedfile records across genomic regions.
Parallelized across files using threads from the "iscream.threads" option.
Usage
summarize_regions(
bedfiles,
regions,
columns,
col_names,
fun = "all",
feature_col = NULL,
set_region_rownames = FALSE,
nthreads = NULL
)Arguments
- bedfiles
A vector of bedfile paths
- regions
A vector, data frame or GenomicRanges of genomic regions. See details.
- columns
A vector of indices of the numeric columns to be summarized
- col_names
A vector of names to use for
columnsin the output- fun
Function(s) to apply over the region. See details.
- feature_col
If the input is a dataframe, the column to use as the feature label instead of the genomic region string
- set_region_rownames
Use the region strings as the returned data frame's rownames. Can be useful if you have a named regions and want both the regions strings rownames and the feature names.
- nthreads
Set number of threads to use overriding the
"iscream.threads"option. See?set_threadsfor more information.
Details
The input regions may be string vector in the form "chr:start-end"
or a GRanges object. If a data frame is provided, they must have "chr",
"start", and "end" columns. If the string vector and GenomicRanges inputs
are named, the names will be used to describe each feature in the output
dataframe. If input dataframes have a feature column, set feature_col to
that column name to populate the output's feature column.
Supported fun arguments are given below.
Sum:
"sum"Mean:
"mean"Median:
"median"Standard deviation:
"stddev"Variance:
"variance"Minimum:
"min"Maximum:
"max"Range:
"range"No. of records in the region:
"count"
The summarizing computations are backed by the Armadillo library. See https://arma.sourceforge.net/docs.html#stats_fns for futher details on the supported functions
Examples
bedfiles <- system.file("extdata", package = "iscream") |>
list.files(pattern = "[a|b|c|d].bed.gz$", full.names = TRUE)
# examine the bedfiles
colnames <- c("chr", "start", "end", "beta", "coverage")
lapply(bedfiles, function(i) knitr::kable(read.table(i, col.names = colnames)))
#> [[1]]
#>
#>
#> |chr | start| end| beta| coverage|
#> |:----|-----:|---:|----:|--------:|
#> |chr1 | 0| 2| 1.0| 1|
#> |chr1 | 2| 4| 1.0| 1|
#> |chr1 | 4| 6| 0.0| 2|
#> |chr1 | 6| 8| 0.0| 1|
#> |chr1 | 8| 10| 0.5| 2|
#> |chr1 | 10| 12| 1.0| 2|
#> |chr1 | 12| 14| 1.0| 3|
#>
#> [[2]]
#>
#>
#> |chr | start| end| beta| coverage|
#> |:----|-----:|---:|----:|--------:|
#> |chr1 | 0| 2| 0| 2|
#> |chr1 | 4| 6| 1| 2|
#> |chr1 | 6| 8| 1| 1|
#> |chr1 | 10| 12| 0| 2|
#> |chr1 | 12| 14| 1| 1|
#>
#> [[3]]
#>
#>
#> |chr | start| end| beta| coverage|
#> |:----|-----:|---:|----:|--------:|
#> |chr1 | 2| 4| 1| 2|
#> |chr1 | 6| 8| 0| 2|
#> |chr1 | 8| 10| 1| 1|
#>
#> [[4]]
#>
#>
#> |chr | start| end| beta| coverage|
#> |:----|-----:|---:|----:|--------:|
#> |chr1 | 0| 2| 1.0| 1|
#> |chr1 | 2| 4| 1.0| 2|
#> |chr1 | 6| 8| 0.0| 1|
#> |chr1 | 8| 10| 0.5| 2|
#> |chr1 | 12| 14| 1.0| 1|
#>
# make a vector of regions
regions <- c("chr1:1-6", "chr1:7-10", "chr1:11-14")
summarize_regions(bedfiles, regions, columns = c(4, 5), col_names = c("beta", "cov"))
#> [17:51:29.743474] [iscream::summarize_regions] [info] Summarizing 3 regions from 4 bedfiles
#> [17:51:29.743489] [iscream::summarize_regions] [info] using sum, mean, median, stddev, variance, min, max, range, count
#> [17:51:29.743493] [iscream::summarize_regions] [info] with columns 4, 5 as beta, cov
#> Feature Sample beta.sum cov.sum beta.mean cov.mean beta.median cov.median
#> 1 chr1:1-6 a 2.0 4 0.6666667 1.333333 1.00 1.0
#> 2 chr1:7-10 a 0.5 3 0.2500000 1.500000 0.25 1.5
#> 3 chr1:11-14 a 2.0 5 1.0000000 2.500000 1.00 2.5
#> 4 chr1:1-6 b 1.0 4 0.5000000 2.000000 0.50 2.0
#> 5 chr1:7-10 b 1.0 1 1.0000000 1.000000 1.00 1.0
#> 6 chr1:11-14 b 1.0 3 0.5000000 1.500000 0.50 1.5
#> 7 chr1:1-6 c 1.0 2 1.0000000 2.000000 1.00 2.0
#> 8 chr1:7-10 c 1.0 3 0.5000000 1.500000 0.50 1.5
#> 9 chr1:11-14 c NA NA NA NA NA NA
#> 10 chr1:1-6 d 2.0 3 1.0000000 1.500000 1.00 1.5
#> 11 chr1:7-10 d 0.5 3 0.2500000 1.500000 0.25 1.5
#> 12 chr1:11-14 d 1.0 1 1.0000000 1.000000 1.00 1.0
#> beta.stddev cov.stddev beta.variance cov.variance beta.min cov.min beta.max
#> 1 0.5773503 0.5773503 0.3333333 0.3333333 0 1 1.0
#> 2 0.3535534 0.7071068 0.1250000 0.5000000 0 1 0.5
#> 3 0.0000000 0.7071068 0.0000000 0.5000000 1 2 1.0
#> 4 0.7071068 0.0000000 0.5000000 0.0000000 0 2 1.0
#> 5 0.0000000 0.0000000 0.0000000 0.0000000 1 1 1.0
#> 6 0.7071068 0.7071068 0.5000000 0.5000000 0 1 1.0
#> 7 0.0000000 0.0000000 0.0000000 0.0000000 1 2 1.0
#> 8 0.7071068 0.7071068 0.5000000 0.5000000 0 1 1.0
#> 9 NA NA NA NA NA NA NA
#> 10 0.0000000 0.7071068 0.0000000 0.5000000 1 1 1.0
#> 11 0.3535534 0.7071068 0.1250000 0.5000000 0 1 0.5
#> 12 0.0000000 0.0000000 0.0000000 0.0000000 1 1 1.0
#> cov.max beta.range cov.range count
#> 1 2 1.0 1 3
#> 2 2 0.5 1 2
#> 3 3 0.0 1 2
#> 4 2 1.0 0 2
#> 5 1 0.0 0 1
#> 6 2 1.0 1 2
#> 7 2 0.0 0 1
#> 8 2 1.0 1 2
#> 9 NA NA NA NA
#> 10 2 0.0 1 2
#> 11 2 0.5 1 2
#> 12 1 0.0 0 1
summarize_regions(
bedfiles,
regions,
fun = c("mean", "stddev"),
columns = c(4, 5),
col_names = c("beta", "cov")
)
#> [17:51:29.756767] [iscream::summarize_regions] [info] Summarizing 3 regions from 4 bedfiles
#> [17:51:29.756782] [iscream::summarize_regions] [info] using mean, stddev
#> [17:51:29.756785] [iscream::summarize_regions] [info] with columns 4, 5 as beta, cov
#> Feature Sample beta.mean cov.mean beta.stddev cov.stddev
#> 1 chr1:1-6 a 0.6666667 1.333333 0.5773503 0.5773503
#> 2 chr1:7-10 a 0.2500000 1.500000 0.3535534 0.7071068
#> 3 chr1:11-14 a 1.0000000 2.500000 0.0000000 0.7071068
#> 4 chr1:1-6 b 0.5000000 2.000000 0.7071068 0.0000000
#> 5 chr1:7-10 b 1.0000000 1.000000 0.0000000 0.0000000
#> 6 chr1:11-14 b 0.5000000 1.500000 0.7071068 0.7071068
#> 7 chr1:1-6 c 1.0000000 2.000000 0.0000000 0.0000000
#> 8 chr1:7-10 c 0.5000000 1.500000 0.7071068 0.7071068
#> 9 chr1:11-14 c NA NA NA NA
#> 10 chr1:1-6 d 1.0000000 1.500000 0.0000000 0.7071068
#> 11 chr1:7-10 d 0.2500000 1.500000 0.3535534 0.7071068
#> 12 chr1:11-14 d 1.0000000 1.000000 0.0000000 0.0000000
summarize_regions(bedfiles, regions, fun = "sum", columns = 5, col_names = "coverage")
#> [17:51:29.760067] [iscream::summarize_regions] [info] Summarizing 3 regions from 4 bedfiles
#> [17:51:29.760075] [iscream::summarize_regions] [info] using sum
#> [17:51:29.760078] [iscream::summarize_regions] [info] with columns 5 as coverage
#> Feature Sample coverage.sum
#> 1 chr1:1-6 a 4
#> 2 chr1:7-10 a 3
#> 3 chr1:11-14 a 5
#> 4 chr1:1-6 b 4
#> 5 chr1:7-10 b 1
#> 6 chr1:11-14 b 3
#> 7 chr1:1-6 c 2
#> 8 chr1:7-10 c 3
#> 9 chr1:11-14 c NA
#> 10 chr1:1-6 d 3
#> 11 chr1:7-10 d 3
#> 12 chr1:11-14 d 1