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CSAR specifications

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Unique identifier OMICS_00435
Name CSAR
Alternative name ChIP-Seq Analysis in R
Software type Package/Module
Interface Command line interface
Restrictions to use None
Input data For each DNA mapped read: chromosome, location (bp), strand (+/-), read length (bp), and number of times mapped on the genome.
Input format Plain text, tabular data format
Output data Tables of genomic coordinates of significantly enriched region locations, level of enrichment per nucleotide position and the distance of enriched regions to annotated genomic features
Output format Tabular data format
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License Artistic License version 2.0
Computer skills Advanced
Version 1.32.0
Stability Stable
Requirements
stats, IRanges, GenomicRanges, utils, R(>=2.15.0), S4Vectors, GenomeInfoDb, ShortRead, Biostrings
Maintained Yes

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Publication for ChIP-Seq Analysis in R

CSAR citations

 (5)
library_books

Combinatorial activities of SHORT VEGETATIVE PHASE and FLOWERING LOCUS C define distinct modes of flowering regulation in Arabidopsis

2015
PMCID: 4378019
PMID: 25853185
DOI: 10.1186/s13059-015-0597-1

[…] bioconductor package narrowpeaks []. only macs peaks also detected by narrowpeaks were considered for further processing. final sets of peaks were annotated to tair10 using the bioconductor package csar []. analysis of peak distribution over exon, intron, enhancer, proximal promoter, 5’ utr and 3’ utr was done in r using chippeakanno []. proximal promoter and immediate downstream […]

library_books

Genome wide data (ChIP seq) enabled identification of cell wall related and aquaporin genes as targets of tomato ASR1, a drought stress responsive transcription factor

2014
PMCID: 3923394
PMID: 24423251
DOI: 10.1186/1471-2229-14-29

[…] were manually visualized using the integrative genomics viewer (igv) genome browser [] (figure a). analysis was also performed with the software program cisgenome [] and the statistical package csar [], but these programs yielded false-positive peaks (present in both precipitated and input samples) and were thus not used for further analysis. the software program readingextension was used […]

library_books

Structural determinants of DNA recognition by plant MADS domain transcription factors

2013
PMCID: 3936718
PMID: 24275492
DOI: 10.1093/nar/gkt1172

[…] reads were mapped to the arabidopsis thaliana (tair9) genome using soapv2 (). reads mapped to multiple regions or to the mitochondria or chloroplast genome were discarded. we modified the r package csar () to generate read-enrichment score values at each single-nucleotide position, without performing peak calling. this score represents the ratio between density of reads overlapping a given […]

library_books

Practical Guidelines for the Comprehensive Analysis of ChIP seq Data

2013
PMCID: 3828144
PMID: 24244136
DOI: 10.1371/journal.pcbi.1003326

[…] such as gc content or mappability (beads ). peaks are finally called above a user-defined snr level. models used for the statistical assessment of enriched regions (peaks) range from poisson (csar ), local poisson (macs), negative binomial (cisgenome ) to zero-inflated negative binomial (zinba ), or even extend to more sophisticated machine learning modeling techniques such as hidden […]

library_books

Identification of pathways directly regulated by SHORT VEGETATIVE PHASE during vegetative and reproductive development in Arabidopsis

2013
PMCID: 3706845
PMID: 23759218
DOI: 10.1186/gb-2013-14-6-r56

[…] by quantitative real-time polymerase chain reaction; chip-seq: chromatin immunoprecipitation combined with high throughput dna sequencing; chip: chromatin immunoprecipitation; ck: cytokinin; csar: chip-seq analysis in r; fm: floral meristem; ga: gibberellin; geo: gene expression omnibus; go: gene ontology; gr: glucocorticoid receptor; im: inflorescence meristem; qrt-pcr: quantitative real-time […]


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CSAR institution(s)
Applied Bioinformatics, Plant Research International, Wageningen, Netherlands; Netherlands Bioinformatics Centre, Wageningen, Netherlands; Laboratory of Molecular Biology, Wageningen University, Wageningen, Netherlands; Bioscience, Plant Research International, Wageningen, Netherlands; Institute of Plant Genetics, Polish Academy of Sciences, Poznan, Poland
CSAR funding source(s)
This project was supported by grants from the Netherlands Bioinformatics Centre (NBIC), which is part of the Netherlands Genomics Initiative, and from the Netherlands Organization for Scientific Research (NWO; Horizon grant #93519020).

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