Science Score: 23.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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○codemeta.json file
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○.zenodo.json file
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✓DOI references
Found 4 DOI reference(s) in README -
○Academic publication links
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✓Committers with academic emails
1 of 3 committers (33.3%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (8.2%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: emilygoren
- Default Branch: master
- Size: 33.5 MB
Statistics
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
BinQuasi
This package provides code to call peaks in ChIP-seq data with biological replicates using the BinQuasi algorithm of Goren, Liu, Wang, and Wang (2018) doi.org/10.1093/bioinformatics/bty227.
Installation
The BinQuasi package for R can be installed from Github using devtools following the code below.
R
devtools::install_github("emilygoren/BinQuasi", args = "--preclean", build_vignettes = TRUE)
library(BinQuasi)
Data Preprocessing
BinQuasi accepts sorted and indexed BAM files (note that it does not perform genome alignment of raw reads). If your BAM files are not indexed and sorted, we recommend using samtools.
Peak Calling
Once installed, BinQuasi calls peaks with the function "BQ()." Below is code to run BinQuasi with all default settings, where the sorted and indexed BAM files are stored in the directory specified by "fpath" under the file names "C1.bam", " C2.bam" and "I1.bam", "I2.bam" for ChIP and input files, respectively.
R
fpath <- paste0(system.file(package = 'BinQuasi'), '/extdata/')
results <- BQ(fpath,
ChIP.files = c('C1.bam', 'C2.bam'),
control.files = c('I1.bam', 'I2.bam'))
head(results$peaks)
See the package documentation for information on changing the default settings.
R
?BQ
Exporting Results
The code below saves the called peaks in BED format in the file "BinQuasiPeaks.bed". ```R
Sort peaks by p-value
opeaks <- results$peaks[order(results$peaks$P.val),]
Name the peaks by rank
opeaks$name <- paste0('BQPeak', 1:nrow(opeaks))
Save as .bed file, setting the scores to be -log10(p-value)
bedout <- data.frame(chrom = opeaks$chr, chromStart = opeaks$start, chromEnd = opeaks$end, name = opeaks$name, score = -log10(opeaks$P.val), strand = c(rep(".", nrow(opeaks)))) head(bedout) write.table(bedout, file="BinQuasiPeaks.bed", quote = FALSE, sep = "\t", row.names = FALSE, col.names = FALSE) ```
Owner
- Name: Emily Goren
- Login: emilygoren
- Kind: user
- Location: Seattle, WA
- Repositories: 7
- Profile: https://github.com/emilygoren
GitHub Events
Total
Last Year
Committers
Last synced: over 3 years ago
All Time
- Total Commits: 38
- Total Committers: 3
- Avg Commits per committer: 12.667
- Development Distribution Score (DDS): 0.053
Top Committers
| Name | Commits | |
|---|---|---|
| Emily Goren | e****n@g****m | 36 |
| Emily Goren | e****n@C****l | 1 |
| Emily Goren | e****n@t****u | 1 |
Committer Domains (Top 20 + Academic)
Packages
- Total packages: 1
- Total downloads: unknown
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 3
cran.r-project.org: BinQuasi
Analyzing Replicated ChIP Sequencing Data Using Quasi-Likelihood
- Homepage: https://github.com/emilygoren/BinQuasi
- Documentation: http://cran.r-project.org/web/packages/BinQuasi/BinQuasi.pdf
- License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
- Status: removed
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Latest release: 0.1-6
published almost 8 years ago