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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("maPredictDSC")
In most cases, you don't need to download the package archive at all.
maPredictDSC
Phenotype prediction using microarray data: approach of the best overall team in the IMPROVER Diagnostic Signature Challenge
Bioconductor version: 2.14
This package implements the classification pipeline of the best overall team (Team221) in the IMPROVER Diagnostic Signature Challenge. Additional functionality is added to compare 27 combinations of data preprocessing, feature selection and classifier types.
Author: Adi Laurentiu Tarca <atarca at med.wayne.edu>
Maintainer: Adi Laurentiu Tarca <atarca at med.wayne.edu>
Citation (from within R,
enter citation("maPredictDSC")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("maPredictDSC")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("maPredictDSC")
| R Script | maPredictDSC | |
| Reference Manual |
Details
| biocViews | Classification, Microarray, Software |
| Version | 1.2.0 |
| In Bioconductor since | BioC 2.13 (R-3.0) |
| License | GPL-2 |
| Depends | R (>= 2.15.0), MASS, affy, limma, gcrma, ROC, class, e1071, caret, hgu133plus2.db, ROCR, AnnotationDbi, LungCancerACvsSCCGEO |
| Imports | |
| Suggests | parallel |
| System Requirements | |
| URL | http://bioinformaticsprb.med.wayne.edu/maPredictDSC |
| Depends On Me | |
| Imports Me | |
| Suggests Me |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | maPredictDSC_1.2.0.tar.gz |
| Windows Binary | maPredictDSC_1.2.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | maPredictDSC_1.2.0.tgz |
| Mac OS X 10.9 (Mavericks) | maPredictDSC_1.2.0.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
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