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AGOUTI: improving genome assembly and annotation using transcriptome data
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Abstract
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@indiana.edu
Supplementary information
Supplementary data are available at
Bioinformatics
online.
Title: AGOUTI: improving genome assembly and annotation using transcriptome data
Description:
Abstract
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@indiana.
edu
Supplementary information
Supplementary data are available at
Bioinformatics
online.
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