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HIVcDNAvantWout03
T cell line infections with HIV-1 LAI (BRU)
Bioconductor version: 3.0
The expression levels of approximately 4600 cellular RNA transcripts were assessed in CD4+ T cell lines at different times after infection with HIV-1BRU using DNA microarrays. This data corresponds to the first block of a 12 block array image (001030_08_1.GEL) in the first data set (2000095918 A) in the first experiment (CEM LAI vs HI-LAI 24hr). There are two data sets, which are part of a dye-swap experiment with replicates, representing the Cy3 (green) absorption intensities for channel 1 (hiv1raw) and the Cy5 (red) absorption intensities for channel 2 (hiv2raw).
Author: Dr. Angelique van't Wout, Department of Microbiology, University of Washington
Maintainer: Chris Fraley <fraley at stat.washington.edu>
Citation (from within R,
enter citation("HIVcDNAvantWout03")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("HIVcDNAvantWout03")
Documentation
| Reference Manual |
Details
| biocViews | ExperimentData, HIV |
| Version | 1.5.1 |
| License | GPL (>= 2) |
| Depends | |
| Imports | |
| LinkingTo | |
| Suggests | |
| SystemRequirements | |
| Enhances | |
| URL | http://expression.microslu.washington.edu/expression/vantwoutjvi2002.html |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | HIVcDNAvantWout03_1.5.1.tar.gz |
| Windows Binary | HIVcDNAvantWout03_1.5.1.zip |
| Mac OS X 10.6 (Snow Leopard) | HIVcDNAvantWout03_1.5.1.tgz |
| Mac OS X 10.9 (Mavericks) | HIVcDNAvantWout03_1.5.1.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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