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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("BSgenome.Drerio.UCSC.danRer5.masked")
In most cases, you don't need to download the package archive at all.
BSgenome.Drerio.UCSC.danRer5.masked
Full masked genome sequences for Danio rerio (UCSC version danRer5)
Bioconductor version: 3.0
Full genome sequences for Danio rerio (Zebrafish) as provided by UCSC (danRer5, Jul. 2007) and stored in Biostrings objects. The sequences are the same as in BSgenome.Drerio.UCSC.danRer5, except that each of them has the 4 following masks on top: (1) the mask of assembly gaps (AGAPS mask), (2) the mask of intra-contig ambiguities (AMB mask), (3) the mask of repeats from RepeatMasker (RM mask), and (4) the mask of repeats from Tandem Repeats Finder (TRF mask). Only the AGAPS and AMB masks are "active" by default.
Author: The Bioconductor Dev Team
Maintainer: Bioconductor Package Maintainer <maintainer at bioconductor.org>
Citation (from within R,
enter citation("BSgenome.Drerio.UCSC.danRer5.masked")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("BSgenome.Drerio.UCSC.danRer5.masked")
Documentation
| Reference Manual |
Details
| biocViews | AnnotationData, BSgenome, Danio_rerio, Genetics |
| Version | 1.3.99 |
| License | Artistic-2.0 |
| Depends | BSgenome(>= 1.31.8), BSgenome.Drerio.UCSC.danRer5 |
| Imports | BSgenome, BSgenome.Drerio.UCSC.danRer5 |
| LinkingTo | |
| Suggests | |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | BSgenome.Drerio.UCSC.danRer5.masked_1.3.99.tar.gz |
| Windows Binary | BSgenome.Drerio.UCSC.danRer5.masked_1.3.99.zip |
| Mac OS X 10.6 (Snow Leopard) | BSgenome.Drerio.UCSC.danRer5.masked_1.3.99.tgz |
| Mac OS X 10.9 (Mavericks) | BSgenome.Drerio.UCSC.danRer5.masked_1.3.99.tgz |
| 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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