Science Score: 10.0%
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
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○Academic publication links
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✓Committers with academic emails
1 of 11 committers (9.1%) from academic institutions -
○Institutional organization owner
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○Scientific vocabulary similarity
Low similarity (12.9%) to scientific vocabulary
Keywords from Contributors
Repository
Quick Read Quality Control
Basic Info
- Host: GitHub
- Owner: vsbuffalo
- Language: R
- Default Branch: master
- Homepage: bioconductor.org/packages/release/bioc/html/qrqc.html
- Size: 757 KB
Statistics
- Stars: 20
- Watchers: 2
- Forks: 7
- Open Issues: 3
- Releases: 0
Metadata Files
README.md
qrqc - Quick Read Quality Control
qrqc and all supporting documentation Copyright (c) Vince Buffalo, 2011-2012
Contact: Vince Buffalo vsbuffaloAAAAA@gmail.com (with the poly-A tail removed)
If you wish to report a bug, please open an issue on Github (http://github.com/vsbuffalo/qrqc/issues) or post it on the Bioconductor support site (https://support.bioconductor.org/). You can contact me personally as well, but please open an issue first.
About
qrqc (short for "Quick Read Quality Control") is a fast and extensible package that reports basic quality and summary statistics on FASTQ and FASTA files, including base and quality distribution by position, sequence length distribution, and common sequences.
License
GNU General Public License, version 2.
FAQ
Why ggplot2?
I've had some feature requests for qrqc since its release, mostly
related to customizing the graphics. Since data accessibility and
custom graphics were the reason I created qrqc, I initially rewrote
qrqc to provide more graphics options through lattice. However,
all the graphics parameters I added led to large numbers of arguments
to functions and high complexity. This rewrite uses ggplot2, which
is a very excellent way to create graphics as any graphics object can
be further manipulated.
Why do you use Monte Carlo simulations to generate the smooth curve?
qrqc is fast because it bins the quality scores of bases by
positions; there is data summarization done by readSeqFile. To
create a smooth curve, the function needs multiple data points (not
binned data), which I simulate via Monte Carlo draws from the quality
distribution by position. This is an approximation, but it leads to a
smooth curve which can create a useful visual tool in assessing
quality drops.
What do I do about bad quality regions?
Illumina reads often have poor 3'-end qualities. I've noticed that
HiSeq machines also produce poor quality 5'-ends. For increased
mapping rates and better assmeblies, it is generally advisable that
these poor quality regions be trimmed off. Nik Joshi's took sickle
tool can do this; you can get it here
http://github.com/najoshi/sickle.
3'-end adapter contamination can be difficult to recognize (and thus
remove) due to poor quality and likely incorrect bases. I've developed
a tool called scythe that removes
Owner
- Name: Vince Buffalo
- Login: vsbuffalo
- Kind: user
- Location: Berkeley, CA
- Company: UC Berkeley
- Website: http://vincebuffalo.com
- Repositories: 129
- Profile: https://github.com/vsbuffalo
Evolutionary geneticist at UC Berkeley, former bioinformatician. ♥s probability, statistics. Author of book Bioinformatics Data Skills.
GitHub Events
Total
- Issues event: 1
Last Year
- Issues event: 1
Committers
Last synced: almost 3 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Vince Buffalo | v****o@u****u | 88 |
| Vince Buffalo | v****o@g****m | 69 |
| Dan Tenenbaum | d****a@f****g | 24 |
| Herve Pages | h****s@f****g | 6 |
| Hervé Pagès | h****s@f****g | 3 |
| Nathaniel Hayden | n****n@f****g | 3 |
| Sonali Arora | s****a@f****g | 2 |
| vobencha | v****n@r****g | 2 |
| vobencha | v****a@g****m | 2 |
| Chao-Jen Wong | c****2@f****g | 1 |
| Martin Morgan | m****n@f****g | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 11 months ago
All Time
- Total issues: 1
- Total pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Total issue authors: 1
- Total pull request authors: 0
- Average comments per issue: 0.0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 1
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 1
- Pull request authors: 0
- Average comments per issue: 0.0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- azcarriqui77 (1)
Pull Request Authors
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- bioconductor 38,974 total
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 2
- Total maintainers: 1
bioconductor.org: qrqc
Quick Read Quality Control
- Homepage: http://github.com/vsbuffalo/qrqc
- Documentation: https://bioconductor.org/packages/release/bioc/vignettes/qrqc/inst/doc/qrqc.pdf
- License: GPL (>=2)
- Status: removed
-
Latest release: 1.56.0
published over 2 years ago
Rankings
Maintainers (1)
Dependencies
- Biostrings * depends
- biovizBase * depends
- brew * depends
- ggplot2 * depends
- reshape * depends
- testthat * depends
- xtable * depends
- Biostrings * imports
- biovizBase * imports
- ggplot2 * imports
- graphics * imports
- methods * imports
- plyr * imports
- reshape * imports
- stats * imports