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FAN-C: a feature-rich framework for the analysis and visualisation of chromosome conformation capture data.

Kai KruseClemens B HugJuan M Vaquerizas
Published in: Genome biology (2020)
Chromosome conformation capture data, particularly from high-throughput approaches such as Hi-C, are typically very complex to analyse. Existing analysis tools are often single-purpose, or limited in compatibility to a small number of data formats, frequently making Hi-C analyses tedious and time-consuming. Here, we present FAN-C, an easy-to-use command-line tool and powerful Python API with a broad feature set covering matrix generation, analysis, and visualisation for C-like data ( https://github.com/vaquerizaslab/fanc ). Due to its compatibility with the most prevalent Hi-C storage formats, FAN-C can be used in combination with a large number of existing analysis tools, thus greatly simplifying Hi-C matrix analysis.
Keyphrases
  • high throughput
  • electronic health record
  • machine learning
  • gene expression
  • crystal structure