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Accelerating 3D genomics data analysis with Microcket.

Yu ZhaoMengqi YangFanglei GongYuqi PanMinghui HuQin PengLeina LuXiaowen LyuKun Sun
Published in: Communications biology (2024)
The three-dimensional (3D) organization of genome is fundamental to cell biology. To explore 3D genome, emerging high-throughput approaches have produced billions of sequencing reads, which is challenging and time-consuming to analyze. Here we present Microcket, a package for mapping and extracting interacting pairs from 3D genomics data, including Hi-C, Micro-C, and derivant protocols. Microcket utilizes a unique read-stitch strategy that takes advantage of the long read cycles in modern DNA sequencers; benchmark evaluations reveal that Microcket runs much faster than the current tools along with improved mapping efficiency, and thus shows high potential in accelerating and enhancing the biological investigations into 3D genome. Microcket is freely available at https://github.com/hellosunking/Microcket .
Keyphrases
  • single cell
  • data analysis
  • high throughput
  • single molecule
  • genome wide
  • high resolution
  • high density
  • dna methylation
  • circulating tumor
  • stem cells
  • machine learning
  • bone marrow
  • cell therapy
  • human health