2017
DOI: 10.1101/220079
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

ChIPdig: a comprehensive user-friendly tool for mining multi-sample ChIP-seq data

Abstract: Summary: In this article we present ChIPdig, a tool for analyzing and comparing multiple ChIP-seq data sets. ChIPdig is written in R and enables access to powerful R-based functions and packages through a simple user interface powered by the shiny package. It allows users to align reads to a reference genome, perform peak calling and differential enrichment analysis on regions of interest, annotate such regions based on available coordinates of transcription start and termination sites, exons, introns, 5' UTRs… Show more

Help me understand this report
View published versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1

Citation Types

0
2
0

Year Published

2018
2018
2018
2018

Publication Types

Select...
2

Relationship

1
1

Authors

Journals

citations
Cited by 2 publications
(2 citation statements)
references
References 20 publications
0
2
0
Order By: Relevance
“…However, they do not collect the data to a single-click loadable visualisation, including all the metrics and analysis reports (for tool comparisons, see Supplementary Table 1) and therefore are more time consuming and require higher levels of computational expertise of the user. Other solutions provide GUI-based analysis, where modifying the source code is more time consuming [9][10][11] . Promising database-based all-inclusive data analysis platforms have been developed 12,13 , but these are feasible for only large core facilities, where the time and effort necessary for system administration and database management becomes cost-effective.…”
Section: Introduction and Resultsmentioning
confidence: 99%
“…However, they do not collect the data to a single-click loadable visualisation, including all the metrics and analysis reports (for tool comparisons, see Supplementary Table 1) and therefore are more time consuming and require higher levels of computational expertise of the user. Other solutions provide GUI-based analysis, where modifying the source code is more time consuming [9][10][11] . Promising database-based all-inclusive data analysis platforms have been developed 12,13 , but these are feasible for only large core facilities, where the time and effort necessary for system administration and database management becomes cost-effective.…”
Section: Introduction and Resultsmentioning
confidence: 99%
“…GRO-seq data was obtained from the NCBI GEO database (GSE47132) and the reads were mapped to the C. elegans genome (ce10 assembly) using ChIPdig, a software application to analyze ChIP-seq data (Esse and Grishok 2017). Then, reads matching ribosomal RNA loci were removed, as described before (Cecere et al 2013).…”
Section: Analysis Of Gro-seq Datamentioning
confidence: 99%