Literature DB >> 28398543

FunChIP: an R/Bioconductor package for functional classification of ChIP-seq shapes.

Alice C L Parodi1, Laura M Sangalli1, Simone Vantini1, Bruno Amati2,3, Piercesare Secchi1, Marco J Morelli2.   

Abstract

SUMMARY: Chromatin Immunoprecipitation followed by sequencing (ChIP-seq) generates local accumulations of sequencing reads on the genome ("peaks"), which correspond to specific protein-DNA interactions or chromatin modifications. Peaks are detected by considering their total area above a background signal, usually neglecting their shapes, which instead may convey additional biological information. We present FunChIP, an R/Bioconductor package for clustering peaks according to a functional representation of their shapes: after approximating their profiles with cubic B-splines, FunChIP minimizes their functional distance and classifies the peaks applying a k-mean alignment and clustering algorithm. The whole pipeline is user-friendly and provides visualization functions for a quick inspection of the results. An application to the transcription factor Myc in 3T9 murine fibroblasts shows that clusters of peaks with different shapes are associated with different genomic locations and different transcriptional regulatory activity.
AVAILABILITY AND IMPLEMENTATION: The package is implemented in R and is available under Artistic Licence 2.0 from the Bioconductor website (http://bioconductor.org/packages/FunChIP). CONTACT: marco.morelli@iit.it. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Entities:  

Mesh:

Year:  2017        PMID: 28398543     DOI: 10.1093/bioinformatics/btx201

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  4 in total

1.  Functional data analysis for computational biology.

Authors:  Marzia A Cremona; Hongyan Xu; Kateryna D Makova; Matthew Reimherr; Francesca Chiaromonte; Pedro Madrigal
Journal:  Bioinformatics       Date:  2019-09-01       Impact factor: 6.937

2.  Expression of E93 provides an instructive cue to control dynamic enhancer activity and chromatin accessibility during development.

Authors:  Spencer L Nystrom; Matthew J Niederhuber; Daniel J McKay
Journal:  Development       Date:  2020-03-16       Impact factor: 6.868

3.  StoatyDive: Evaluation and classification of peak profiles for sequencing data.

Authors:  Florian Heyl; Rolf Backofen
Journal:  Gigascience       Date:  2021-06-18       Impact factor: 6.524

4.  Image Representational Path of Regional Cultural and Creative Products Based on Genetic Algorithm.

Authors:  Baiying Wu; Ruiting Han
Journal:  Comput Intell Neurosci       Date:  2022-03-15
  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.