Nature Communications (Sep 2022)

Intrinsic bias estimation for improved analysis of bulk and single-cell chromatin accessibility profiles using SELMA

  • Shengen Shawn Hu,
  • Lin Liu,
  • Qi Li,
  • Wenjing Ma,
  • Michael J. Guertin,
  • Clifford A. Meyer,
  • Ke Deng,
  • Tingting Zhang,
  • Chongzhi Zang

DOI
https://doi.org/10.1038/s41467-022-33194-z
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 17

Abstract

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Genome-wide profiling of chromatin accessibility by DNase-seq or ATAC-seq has been widely used to identify regulatory DNA elements and transcription factor binding sites. Here the authors develop a computational model, SELMA, to estimate and correct enzymatic cleavage biases in chromatin accessibility profiling data.