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Read a NIPTeR-format BED file into a NIPTeRSample

bed_to_nipter_sample.Rd

Reads a 5-column or 9-column bgzipped BED file (as written by nipter_bin_bam_bed()) and returns a NIPTeRSample object suitable for all NIPTeR statistical functions: nipter_gc_correct(), nipter_chi_correct(), nipter_z_score(), nipter_ncv_score(), nipter_regression(), and nipter_predict_sex().

Usage

bed_to_nipter_sample(bed, name = NULL, binsize = NULL, con = NULL)

Arguments

bed

Path to a bgzipped (or plain) BED file with a .tbi index.

name

Optional sample name. If NULL (default), derived from the BED file basename (e.g. "sample" from "sample.bed.gz").

binsize

Optional integer; bin size in base pairs. If NULL (default), inferred from the first row of the BED file.

con

Optional open DBI connection with duckhts already loaded.

Value

An object of class c("NIPTeRSample", <strand_type>):

CombinedStrands (from 5-column BED): same structure as nipter_bin_bam() with separate_strands = FALSE.

SeparatedStrands (from 9-column BED): same structure as nipter_bin_bam() with separate_strands = TRUE.

Details

A 5-column BED (chrom, start, end, count, corrected_count) produces a CombinedStrands sample. A 9-column BED (chrom, start, end, count, count_fwd, count_rev, corrected_count, corrected_fwd, corrected_rev) produces a SeparatedStrands sample with independent forward/reverse count matrices. The number of columns is detected automatically.

When the corrected columns contain non-NA values (i.e. the BED was written with a GC-corrected corrected argument), the returned sample's count matrices are replaced with the corrected values and the correction status is set to "GC Corrected". For SeparatedStrands, the per-strand corrected values (corrected_fwd, corrected_rev) are used to populate the forward and reverse matrices independently.

See also

nipter_bin_bam_bed(), nipter_bin_bam(), bed_to_sample(), nipter_gc_correct(), nipter_z_score()

Examples

if (FALSE) { # \dontrun{
# Write NIPTeR-style bin counts to BED, then read back
nipter_bin_bam_bed("sample.bam", "sample.bed.gz")
sample <- bed_to_nipter_sample("sample.bed.gz")

# Use with NIPTeR scoring
samples <- lapply(bed_files, bed_to_nipter_sample)
cg <- nipter_as_control_group(samples)
z21 <- nipter_z_score(samples[[1]], cg, chromo_focus = 21)
} # }