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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("qcmetrics")
In most cases, you don't need to download the package archive at all.
qcmetrics
A Framework for Quality Control
Bioconductor version: 3.0
The package provides a framework for generic quality control of data. It permits to create, manage and visualise individual or sets of quality control metrics and generate quality control reports in various formats.
Author: Laurent Gatto
Maintainer: Laurent Gatto <lg390 at cam.ac.uk>
Citation (from within R,
enter citation("qcmetrics")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("qcmetrics")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("qcmetrics")
| R Script | The 'qcmetrics' infrastructure for quality control and reporting | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | Bioinformatics, MassSpectrometry, Microarray, Proteomics, QualityControl, ReportWriting, Software, Visualisation |
| Version | 1.4.1 |
| In Bioconductor since | BioC 2.13 (R-3.0) |
| License | GPL-2 |
| Depends | R (>= 2.10) |
| Imports | Biobase, methods, knitr, tools, Nozzle.R1, xtable, pander, S4Vectors |
| LinkingTo | |
| Suggests | affy, MSnbase, ggplot2, lattice, yaqcaffy, MAQCsubsetAFX, RforProteomics, AnnotationDbi, mzR, hgu133plus2cdf |
| SystemRequirements | |
| Enhances | |
| URL | https://github.com/lgatto/qcmetrics |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | qcmetrics_1.4.1.tar.gz |
| Windows Binary | qcmetrics_1.4.1.zip |
| Mac OS X 10.6 (Snow Leopard) | qcmetrics_1.4.1.tgz |
| Mac OS X 10.9 (Mavericks) | qcmetrics_1.4.1.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
- RNA-Seq workflow: gene-level exploratory analysis and differential expression
- Changing genomic coordinate systems with rtracklayer::liftOver
- Mass spectrometry and proteomics data analysis
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