RT Journal Article
SR Electronic
T1 AGOUTI: improving genome assembly and annotation using transcriptome data
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 033019
DO 10.1101/033019
A1 Simo V. Zhang
A1 Luting Zhuo
A1 Matthew W. Hahn
YR 2015
UL http://biorxiv.org/content/early/2015/11/26/033019.abstract
AB Summary Current genome assemblies consist of thousands of 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. We present AGOUTI (Annotated Genome Optimization Using Transcriptome Information), a tool that uses RNA-seq 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 accuracy of gene annotation, providing updated versions of each as output.Availability The software is implemented in python and is available from github.com/svm-zhang/AGOUTI.Contact simozhan{at}indiana.eduSupplementary information Supplementary data are available at Bioinformatics online.