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Grouper: graph-based clustering and annotation for improved de novo transcriptome analysis
Author(s) -
Laraib Malik,
Fatemeh Almodaresi,
Rob Patro
Publication year - 2018
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bty378
Subject(s) - contig , sequence assembly , transcriptome , de novo transcriptome assembly , biology , annotation , computational biology , genome , pipeline (software) , cluster analysis , de bruijn graph , gene annotation , computer science , genetics , gene , graph , artificial intelligence , theoretical computer science , gene expression , programming language
De novo transcriptome analysis using RNA-seq offers a promising means to study gene expression in non-model organisms. Yet, the difficulty of transcriptome assembly means that the contigs provided by the assembler often represent a fractured and incomplete view of the transcriptome, complicating downstream analysis. We introduce Grouper, a new method for clustering contigs from de novo assemblies that are likely to belong to the same transcripts and genes; these groups can subsequently be analyzed more robustly. When provided with access to the genome of a related organism, Grouper can transfer annotations to the de novo assembly, further improving the clustering.

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