Choros: correction of sequence-based biases for accurate quantification of ribosome profiling data.

ABSTRACT: Ribosome profiling quantifies translation genome-wide by sequencing ribosome-protected fragments, or footprints. Its single-codon resolution allows identification of translation regulation, such as ribosome stalls or pauses, on individual genes. However, enzyme preferences during library preparation lead to pervasive sequence artifacts that obscure translation dynamics. Widespread over- and under-representation of ribosome footprints can dominate local footprint densities and skew estimates of elongation rates by up to five fold. To address these biases and uncover true patterns of translation, we present choros, a computational method that models ribosome footprint distributions to provide bias-corrected footprint counts. choros uses negative binomial regression to accurately estimate two

SUBMITTER: Mok A 

PROVIDER: S-EPMC9980091 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature