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StripeDiff: Model-based algorithm for differential analysis of chromatin stripe.

Krishan GuptaGuangyu WangShuo ZhangXinlei GaoRongbin ZhengYanchun ZhangQingshu MengLili ZhangQi CaoKaifu Chen
Published in: Science advances (2022)
Multiple recent studies revealed stripes as an architectural feature of three-dimensional chromatin and found stripes connected to epigenetic regulation of transcription. Whereas a couple of tools are available to define stripes in a single sample, there is yet no reported method to quantitatively measure the dynamic change of each stripe between samples. Here, we developed StripeDiff, a bioinformatics tool that delivers a set of statistical methods to detect differential stripes between samples. StripeDiff showed optimal performance in both simulation data analysis and real Hi-C data analysis. Applying StripeDiff to 12 sets of Hi-C data revealed new insights into the connection between change of chromatin stripe and change of chromatin modification, transcriptional regulation, and cell differentiation. StripeDiff will be a robust tool for the community to facilitate understanding of stripes and their function in numerous biological models.
Keyphrases
  • data analysis
  • transcription factor
  • dna damage
  • gene expression
  • genome wide
  • machine learning
  • deep learning
  • healthcare
  • single cell
  • mental health
  • dna methylation
  • big data
  • neural network