AGOUTI: improving genome assembly and annotation using transcriptome data.

ABSTRACT:

Background

Genomes sequenced using short-read, next-generation sequencing technologies can have many errors and may be fragmented into thousands of small contigs. These incomplete and fragmented assemblies lead to errors in gene identification, such that single genes spread across multiple contigs are annotated as separate gene models. Such biases can confound inferences about the number and identity of genes within species, as well as gene gain and loss between species.

Results

We present AGOUTI (Annotated Genome Optimization Using Transcriptome Information), a tool that uses RNA sequencing data to simultaneously combine contigs into scaffolds and fragmented gene models into single models. We show that AGOUTI improves both the contiguity of genome assemblies and the accurac

SUBMITTER: Zhang SV 

PROVIDER: S-EPMC4952227 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature