TY  - JOUR
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
Y1  - 2023/02/01 
JF  - Genome Research 
JO  - Genome Research 
SP  - 218 
EP  - 231 
DO  - 10.1101/gr.277015.122 
VL  - 33 
IS  - 2 
UR  - http://genome.cshlp.org/content/33/2/218.abstract 
N2  - 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. 
ER  -