Bacon: a comprehensive computational benchmarking framework for evaluating targeted chromatin conformation capture-specific methodologies.
Li TangMatthew C HillPatrick T EllinorMin LiPublished in: Genome biology (2022)
Chromatin conformation capture (3C)-based technologies have enabled the accurate detection of topological genomic interactions, and the adoption of ChIP techniques to 3C-based protocols makes it possible to identify long-range interactions. To analyze these large and complex datasets, computational methods are undergoing rapid and expansive evolution. Thus, a thorough evaluation of these analytical pipelines is necessary to identify which commonly used algorithms and processing pipelines need to be improved. Here we present a comprehensive benchmark framework, Bacon, to evaluate the performance of several computational methods. Finally, we provide practical recommendations for users working with HiChIP and/or ChIA-PET analyses.
Keyphrases
- loop mediated isothermal amplification
- dna damage
- gene expression
- transcription factor
- machine learning
- genome wide
- molecular dynamics simulations
- computed tomography
- high throughput
- pet ct
- crystal structure
- deep learning
- cancer therapy
- electronic health record
- label free
- quantum dots
- sensitive detection
- single cell
- liquid chromatography