2020
DOI: 10.1101/gr.263228.120
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Identification of determinants of differential chromatin accessibility through a massively parallel genome-integrated reporter assay

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Cited by 16 publications
(8 citation statements)
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“…To identify putative regulators of maturation, we performed motifenrichment analysis on accessible regions using two distinct but complementary approaches. We used a newly developed convolutional neural network-based method called DeepAccess 65,66 which learns the relationship between primary DNA sequence and chromatin accessibility at different ages and then predicts transcription factor motifs that drive differential chromatin accessibility at one age compared to another. In addition, we used HOMER, a de novo motif discovery method that identifies enriched motifs in provided sets of age-specific accessible peaks 67 (Methods).…”
Section: Motif Analysis Identifies Putative Regulators Of Maturationmentioning
confidence: 99%
“…To identify putative regulators of maturation, we performed motifenrichment analysis on accessible regions using two distinct but complementary approaches. We used a newly developed convolutional neural network-based method called DeepAccess 65,66 which learns the relationship between primary DNA sequence and chromatin accessibility at different ages and then predicts transcription factor motifs that drive differential chromatin accessibility at one age compared to another. In addition, we used HOMER, a de novo motif discovery method that identifies enriched motifs in provided sets of age-specific accessible peaks 67 (Methods).…”
Section: Motif Analysis Identifies Putative Regulators Of Maturationmentioning
confidence: 99%
“…Chromatin accessibility is regulated by numerous epigenetic regulators 27 , 28 . Previous studies have proven that SIRT6, as a key chromatin regulator, remodels chromatin by promoting chromatin relaxation, although it has diverse biological functions, such as genome stability, glucose metabolism, and tumor suppression, through multiple pathways 29 34 .…”
Section: Resultsmentioning
confidence: 99%
“…Hammelman and Gifford created such a deep learning approach and used it for the identification of cell state‐specific TFs in chromatin accessibility data [79, 80]. Their method is part of the framework DeepAccess and is based on an ensemble of convolutional neural networks.…”
Section: Computational Tools For Tfa Inferencementioning
confidence: 99%