Molecular biology enzymes have nucleic acid preferences for their substrates; the preference of an enzyme is typically dictated by the sequence at or near the active site of the enzyme. This bias may result in spurious read count patterns when used to interpret high-resolution molecular genomics data. The seqOutBias program aims to correct this issue by scaling the aligned read counts by the ratio of genome-wide observed read counts to the expected sequence based counts for each k-mer. The sequence based k-mer counts take into account mappability at a given read length using Genome Tools’ Tallymer program. The seqOutBias program allows for flexibility in specifying the k-mer, including varying the k-mer size, k-mer information spacing, and specifying strand-specific offsets for the start of the sequence reads. Due to the large size of some datasets, seqOutBias reads compressed files (FASTA, mappability information, and BAM files), and reuses intermediate results as much as possible.
Requirements
- Platform: OS X or Linux
- Compiler: rust >= 1.32.0 + cargo ( http://www.rust-lang.org )
- Genome tools ( http://genometools.org )
- wigToBigWig ( UCSC Git Repository or Precompiled binaries )