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Identifying high-confidence capture Hi-C interactions using CHiCANE.
Holgersen, Erle M; Gillespie, Andrea; Leavy, Olivia C; Baxter, Joseph S; Zvereva, Alisa; Muirhead, Gareth; Johnson, Nichola; Sipos, Orsolya; Dryden, Nicola H; Broome, Laura R; Chen, Yi; Kozin, Igor; Dudbridge, Frank; Fletcher, Olivia; Haider, Syed.
Afiliação
  • Holgersen EM; The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK.
  • Gillespie A; The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK.
  • Leavy OC; Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK.
  • Baxter JS; Department of Health Sciences, University of Leicester, Leicester, UK.
  • Zvereva A; The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK.
  • Muirhead G; The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK.
  • Johnson N; The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK.
  • Sipos O; The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK.
  • Dryden NH; The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK.
  • Broome LR; The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK.
  • Chen Y; The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK.
  • Kozin I; Scientific Computing, The Institute of Cancer Research, London, UK.
  • Dudbridge F; Scientific Computing, The Institute of Cancer Research, London, UK.
  • Fletcher O; Department of Health Sciences, University of Leicester, Leicester, UK.
  • Haider S; The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, UK. Olivia.Fletcher@icr.ac.uk.
Nat Protoc ; 16(4): 2257-2285, 2021 04.
Article em En | MEDLINE | ID: mdl-33837305
ABSTRACT
The ability to identify regulatory interactions that mediate gene expression changes through distal elements, such as risk loci, is transforming our understanding of how genomes are spatially organized and regulated. Capture Hi-C (CHi-C) is a powerful tool to delineate such regulatory interactions. However, primary analysis and downstream interpretation of CHi-C profiles remains challenging and relies on disparate tools with ad-hoc input/output formats and specific assumptions for statistical modeling. Here we present a data processing and interaction calling toolkit (CHiCANE), specialized for the analysis and meaningful interpretation of CHi-C assays. In this protocol, we demonstrate applications of CHiCANE to region capture Hi-C (rCHi-C) and promoter capture Hi-C (pCHi-C) libraries, followed by quality assessment of interaction peaks, as well as downstream analysis specific to rCHi-C and pCHi-C to aid functional interpretation. For a typical rCHi-C/pCHi-C dataset this protocol takes up to 3 d for users with a moderate understanding of R programming and statistical concepts, although this is dependent on dataset size and compute power available. CHiCANE is freely available at https//cran.r-project.org/web/packages/chicane .
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Sequências Reguladoras de Ácido Nucleico / Genômica Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Sequências Reguladoras de Ácido Nucleico / Genômica Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article