Journal
GENOME BIOLOGY
Volume 18, Issue -, Pages -Publisher
BIOMED CENTRAL LTD
DOI: 10.1186/s13059-017-1269-0
Keywords
Single cell RNA-seq; Single cell epigenomics; Manifold learning; Manifold alignment
Funding
- National Institutes of Health (NIH) [HG06272]
- NIH BD2K Fellowship [T32 CA201159]
- NIH F31 Fellowship [HG008912]
- NIH grants [U01 HG007900-01, R01 GM118551-01]
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Single cell experimental techniques reveal transcriptomic and epigenetic heterogeneity among cells, but how these are related is unclear. We present MATCHER, an approach for integrating multiple types of single cell measurements. MATCHER uses manifold alignment to infer single cell multi-omic profiles from transcriptomic and epigenetic measurements performed on different cells of the same type. Using scM&T-seq and sc-GEM data, we confirm that MATCHER accurately predicts true single cell correlations between DNA methylation and gene expression without using known cell correspondences. MATCHER also reveals new insights into the dynamic interplay between the transcriptome and epigenome in single embryonic stem cells and induced pluripotent stem cells.
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