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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("hiReadsProcessor")
In most cases, you don't need to download the package archive at all.
hiReadsProcessor
Functions to process LM-PCR reads from 454/Illumina data.
Bioconductor version: 3.0
hiReadsProcessor contains set of functions which allow users to process LM-PCR products sequenced using any platform. Given an excel/txt file containing parameters for demultiplexing and sample metadata, the functions automate trimming of adaptors and identification of the genomic product. Genomic products are further processed for QC and abundance quantification.
Author: Nirav V Malani <malnirav at gmail.com>
Maintainer: Nirav V Malani <malnirav at gmail.com>
Citation (from within R,
enter citation("hiReadsProcessor")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("hiReadsProcessor")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("hiReadsProcessor")
| HTML | R Script | Introduction |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | Preprocessing, Sequencing, Software |
| Version | 1.0.0 |
| In Bioconductor since | BioC 3.0 (R-3.1) |
| License | GPL-3 |
| Depends | Biostrings, GenomicAlignments, xlsx, BiocParallel, hiAnnotator, R (>= 3.0) |
| Imports | sonicLength, plyr |
| LinkingTo | |
| Suggests | knitr, testthat, BiocGenerics, rSFFreader |
| SystemRequirements | BLAT, JRE, UCSC hg18 in 2bit format for BLAT |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | hiReadsProcessor_1.0.0.tar.gz |
| Windows Binary | hiReadsProcessor_1.0.0.zip |
| Mac OS X 10.6 (Snow Leopard) | hiReadsProcessor_1.0.0.tgz |
| Mac OS X 10.9 (Mavericks) | hiReadsProcessor_1.0.0.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
- 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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