FITs: forest of imputation trees for recovering true signals in single-cell open chromatin profiles.

ABSTRACT: The advent of single-cell open-chromatin profiling technology has facilitated the analysis of heterogeneity of activity of regulatory regions at single-cell resolution. However, stochasticity and availability of low amount of relevant DNA, cause high drop-out rate and noise in single-cell open-chromatin profiles. We introduce here a robust method called as forest of imputation trees (FITs) to recover original signals from highly sparse and noisy single-cell open-chromatin profiles. FITs makes multiple imputation trees to avoid bias during the restoration of read-count matrices. It resolves the challenging issue of recovering open chromatin signals without blurring out information at genomic sites with cell-type-specific activity. Besides visualization and classification, FITs-based imputat

SUBMITTER: Sharma R 

PROVIDER: S-EPMC7676476 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature