Grape
Grape analyzes RNA sequencing (RNA-Seq) data from Next Generation Sequencing (NGS) platforms to perform alignment, gene and transcript expression quantification, exon inclusion estimation, and novel transcript discovery for transcriptome characterization.
Key Features:
- Versatile Input Support: Accepts raw reads in FASTA or FASTQ formats and prealigned reads in SAM/BAM format from various NGS platforms.
- Modular Pipeline Design: Performs quality control and, for non-prealigned reads, aligns to a reference genome using integrated mapping tools and supports integration of alternative mapping and quantification tools that use common data interchange formats.
- Comprehensive Analysis Capabilities: Estimates gene and transcript expression levels, calculates exon inclusion levels, and identifies novel transcripts.
- Scalability: Operates on single computers and parallel computing clusters to accommodate large-scale studies.
- Required Inputs: Accepts raw sequencing reads or prealigned reads, a reference genome, and corresponding gene and transcript annotations.
Scientific Applications:
- Differential expression analysis: Enables gene- and transcript-level quantification for differential expression studies.
- Alternative splicing studies: Provides exon inclusion level calculations to study alternative splicing events.
- Novel transcript discovery: Detects previously unannotated transcripts within RNA-Seq datasets.
Methodology:
Computational steps explicitly include quality control of raw reads; mapping reads to a reference genome for non-prealigned data using integrated mapping tools; quantification of gene and transcript expression using integrated tools; calculation of exon inclusion levels; and detection of novel transcripts.
Topics
Details
- Tool Type:
- command-line tool
- Operating Systems:
- Linux
- Programming Languages:
- R, Java, Perl, Python
- Added:
- 8/3/2017
- Last Updated:
- 11/24/2024
Operations
Publications
Knowles DG, Röder M, Merkel A, Guigó R. Grape RNA-Seq analysis pipeline environment. Bioinformatics. 2013;29(5):614-621. doi:10.1093/bioinformatics/btt016. PMID:23329413. PMCID:PMC3582270.