RT Journal
A1 Mishra, Shreya
A1 Pandey, Neetesh
A1 Chawla, Smriti
A1 Sharma, Madhu
A1 Chandra, Omkar
A1 Jha, Indra Prakash
A1 SenGupta, Debarka
A1 Natarajan, Kedar Nath
A1 Kumar, Vibhor
T1 Matching queried single-cell open-chromatin profiles to large pools of single-cell transcriptomes and epigenomes for reference supported analysis
JF Genome Research 
JO Genome Research 
YR 2023 
FD February 01 
VO 33 
IS 2 
SP 218 
OP 231 
DO 10.1101/gr.277015.122 
UL http://genome.cshlp.org/content/33/2/218.abstract 
AB The true benefits of large single-cell transcriptome and epigenome data sets can be realized only with the development of new approaches and search tools for annotating individual cells. Matching a single-cell epigenome profile to a large pool of reference cells remains a major challenge. Here, we present scEpiSearch, which enables searching, comparison, and independent classification of single-cell open-chromatin profiles against a large reference of single-cell expression and open-chromatin data sets. Across performance benchmarks, scEpiSearch outperformed multiple methods in accuracy of search and low-dimensional coembedding of single-cell profiles, irrespective of platforms and species. Here we also demonstrate the unconventional utilities of scEpiSearch by applying it on single-cell epigenome profiles of K562 cells and samples from patients with acute leukaemia to reveal different aspects of their heterogeneity, multipotent behavior, and dedifferentiated states. Applying scEpiSearch on our single-cell open-chromatin profiles from embryonic stem cells (ESCs), we identified ESC subpopulations with more activity and poising for endoplasmic reticulum stress and unfolded protein response. Thus, scEpiSearch solves the nontrivial problem of amalgamating information from a large pool of single cells to identify and study the regulatory states of cells using their single-cell epigenomes.