Package: CSAR 1.64.0
Jose M Muino
CSAR: Statistical tools for the analysis of ChIP-seq data
Statistical tools for ChIP-seq data analysis. The package includes the statistical method described in Kaufmann et al. (2009) PLoS Biology: 7(4):e1000090. Briefly, Taking the average DNA fragment size subjected to sequencing into account, the software calculates genomic single-nucleotide read-enrichment values. After normalization, sample and control are compared using a test based on the Poisson distribution. Test statistic thresholds to control the false discovery rate are obtained through random permutation.
Authors:
CSAR_1.64.0.tar.gz
CSAR_1.64.0.zip(r-4.7)CSAR_1.64.0.zip(r-4.6)CSAR_1.64.0.zip(r-4.5)
CSAR_1.64.0.tgz(r-4.6-x86_64)CSAR_1.64.0.tgz(r-4.6-arm64)CSAR_1.64.0.tgz(r-4.5-x86_64)CSAR_1.64.0.tgz(r-4.5-arm64)
CSAR_1.64.0.tar.gz(r-4.7-arm64)CSAR_1.64.0.tar.gz(r-4.7-x86_64)CSAR_1.64.0.tar.gz(r-4.6-arm64)CSAR_1.64.0.tar.gz(r-4.6-x86_64)
CSAR_1.64.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
CSAR/json (API)
| # Install 'CSAR' in R: |
| install.packages('CSAR', repos = c('https://bioc-release.r-universe.dev', 'https://cloud.r-project.org')) |
- controlSEP3_test - Partial dataset of a ChIP-seq experiment
- sampleSEP3_test - Partial dataset of a ChIP-seq experiment
- TAIR8_genes_test - Partial dataset of a ChIP-seq experiment
On BioConductor:CSAR-1.65.0(bioc 3.24)CSAR-1.64.0(bioc 3.23)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:ee5e58c3ce (on RELEASE_3_23). Checks:1 ERROR, 11 NOTE, 2 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | ERROR | 147 | ||
| linux-devel-arm64 | NOTE | 222 | ||
| linux-devel-x86_64 | NOTE | 268 | ||
| source / vignettes | OK | 192 | ||
| linux-release-arm64 | NOTE | 215 | ||
| linux-release-x86_64 | NOTE | 224 | ||
| macos-release-arm64 | NOTE | 139 | ||
| macos-release-x86_64 | NOTE | 359 | ||
| macos-oldrel-arm64 | NOTE | 140 | ||
| macos-oldrel-x86_64 | NOTE | 346 | ||
| windows-devel | NOTE | 161 | ||
| windows-release | NOTE | 185 | ||
| windows-oldrel | NOTE | 171 | ||
| wasm-release | OK | 122 |
Exports:ChIPseqScoredistance2GenesgenesWithPeaksgetPermutatedWinScoresgetThresholdLoadBinCSARloadMappedReadsmappedReads2NhitsmappedReads2Nhits_chrpermutatedWinScorespos2Nhitsscore_chrscore2wigsigWinsigWin_chr
Dependencies:BiocGenericsgenericsGenomicRangesIRangesS4VectorsSeqinfo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Statistical tools for the analysis of ChIP-seq data | CSAR-package |
| Calculate read-enrichment scores for each nucleotide position | ChIPseqScore score_chr |
| Calculate relative positions of read-enriched regions regarding gene position | distance2Genes |
| Provide table of genes with read-enriched regions, and their location | genesWithPeaks |
| Obtain the read-enrichment score distribution under the null hypothesis | getPermutatedWinScores |
| Calculate the threshold value corresponding to control FDR at a desired level | getThreshold |
| Load mapped reads | loadMappedReads |
| Calculate number of overlapped extended reads per nucleotide position | mappedReads2Nhits mappedReads2Nhits_chr pos2Nhits pos2Nhits_old |
| Calculate scores for permutated read-enriched regions | permutatedWinScores |
| Partial dataset of a ChIP-seq experiment | controlSEP3_test sampleSEP3_test TAIR8_genes_test |
| Save the read-enrichment scores at each nucleotide position in a .wig file format | LoadBinCSAR score2wig |
| Calculate regions of read-enrichment | sigWin sigWin_chr |
