RT Journal Article
SR Electronic
T1 Single-cell ChIP-seq imputation with SIMPA by leveraging bulk ENCODE data
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2019.12.20.883983
DO 10.1101/2019.12.20.883983
A1 Steffen Albrecht
A1 Tommaso Andreani
A1 Miguel A. Andrade-Navarro
A1 Jean-Fred Fontaine
YR 2020
UL http://biorxiv.org/content/early/2020/01/14/2019.12.20.883983.abstract
AB Single-cell ChIP-seq analysis is challenging due to data sparsity. We present SIMPA (https://github.com/salbrec/SIMPA), a single-cell ChIP-seq data imputation method leveraging predictive information within bulk ENCODE data to impute missing protein-DNA interacting regions of target histone marks or transcription factors. Machine learning models trained for each single cell, each target, and each genomic region enable drastic improvement in cell types clustering and genes identification.