gseq.kmer: Score DNA sequences with a k-mer over a region of interest

In misha: Toolkit for Analysis of Genomic Data

Score DNA sequences with a k-mer over a region of interest

Description

Counts exact matches of a k-mer in DNA sequences over a specified region of interest (ROI). The ROI is defined by start_pos and end_pos (1-based, inclusive), with optional extension controlled by extend.

Usage

gseq.kmer(
  seqs,
  kmer,
  mode = c("count", "frac"),
  strand = 0L,
  start_pos = NULL,
  end_pos = NULL,
  extend = FALSE,
  skip_gaps = TRUE,
  gap_chars = c("-", ".")
)

Arguments

seqs	character vector of DNA sequences (A/C/G/T/N; case-insensitive)
kmer	single character string containing the k-mer to search for (A/C/G/T only)
mode	character; one of "count" or "frac"
strand	integer; 1=forward, -1=reverse, 0=both strands (default: 0)
start_pos	integer or NULL; 1-based inclusive start of ROI (default: 1)
end_pos	integer or NULL; 1-based inclusive end of ROI (default: sequence length)
extend	logical or integer; extension of allowed window starts (default: FALSE)
skip_gaps	logical; if TRUE, treat gap characters as holes and skip them while scanning. Windows are k consecutive non-gap bases (default: TRUE)
gap_chars	character vector; which characters count as gaps (default: c("-", "."))

Details

This function counts k-mer occurrences in DNA sequences directly without requiring a genomics database. For detailed documentation on k-mer counting parameters, see gvtrack.create (functions "kmer.count" and "kmer.frac").

The ROI (region of interest) is defined by start_pos and end_pos. The extend parameter controls whether k-mer matches can extend beyond the ROI boundaries. For palindromic k-mers, use strand=1 or -1 to avoid double counting.

When skip_gaps=TRUE, characters specified in gap_chars are treated as gaps. Windows are defined as k consecutive non-gap bases. The frac denominator counts the number of possible logical starts (non-gap windows) in the region. start_pos and end_pos are interpreted as physical coordinates on the full sequence.

Value

Numeric vector with counts (for "count" mode) or fractions (for "frac" mode). Returns 0 when sequence is too short or ROI is invalid.

See Also

gvtrack.create for detailed k-mer parameter documentation

Examples

## Not run: 
# Example sequences
seqs <- c("CGCGCGCGCG", "ATATATATAT", "ACGTACGTACGT")

# Count CG dinucleotides on both strands
gseq.kmer(seqs, "CG", mode = "count", strand = 0)

# Count on forward strand only
gseq.kmer(seqs, "CG", mode = "count", strand = 1)

# Get CG fraction
gseq.kmer(seqs, "CG", mode = "frac", strand = 0)

# Count in a specific region
gseq.kmer(seqs, "CG", mode = "count", start_pos = 2, end_pos = 8)

# Allow k-mer to extend beyond ROI boundaries
gseq.kmer(seqs, "CG", mode = "count", start_pos = 2, end_pos = 8, extend = TRUE)

# Calculate GC content by summing G and C fractions
g_frac <- gseq.kmer(seqs, "G", mode = "frac", strand = 1)
c_frac <- gseq.kmer(seqs, "C", mode = "frac", strand = 1)
gc_content <- g_frac + c_frac
gc_content

# Compare AT counts on different strands
at_forward <- gseq.kmer(seqs, "AT", mode = "count", strand = 1)
at_reverse <- gseq.kmer(seqs, "AT", mode = "count", strand = -1)
at_both <- gseq.kmer(seqs, "AT", mode = "count", strand = 0)
data.frame(forward = at_forward, reverse = at_reverse, both = at_both)

## End(Not run)

misha documentation built on Dec. 14, 2025, 9:06 a.m.