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• W3208183178 abstract "Recent advances in genome-wide technologies have enabled analyses using small cell numbers of even single cells. However, obtaining tissue epigenomes with cell-type resolution from large organs and tissues still remains challenging, especially when the available material is limited. Here, we present a ChIL-based approach for analyzing the diverse cellular dynamics at the tissue level using high-depth epigenomic data. ChIL for tissues allows the analysis of a single tissue section and can reproducibly generate epigenomic profiles from several tissue types, based on the distribution of target epigenomic states, tissue morphology, and number of cells. The proposed method enabled the independent evaluation of changes in cell populations and gene activation in cells from regenerating skeletal muscle tissues, using a statistical model of RNA polymerase II distribution on gene loci. Thus, the integrative analyses performed using ChIL can elucidate in vivo cell-type dynamics of tissues." @default.
• W3208183178 created "2021-11-08" @default.
• W3208183178 creator A5007651537 @default.
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• W3208183178 date "2021-11-01" @default.
• W3208183178 modified "2023-10-18" @default.
• W3208183178 title "Modeling population size independent tissue epigenomes by ChIL‐seq with single thin sections" @default.
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• W3208183178 doi "https://doi.org/10.15252/msb.202110323" @default.
• W3208183178 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/8564819" @default.
• W3208183178 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34730297" @default.

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