henhaobio
Sign in

bioRxivBioinformatics

AGOUTI: improving genome assembly and annotation using transcriptome data

Simo V Zhang, Luting Zhuo, Matthew W Hahn

PDFDOIPreprintCode

Abstract

SummaryCurrent 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.\n\nAvailabilityThe software is implemented in python and is available from github.com/svm-zhang/AGOUTI.\n\nContactsimozhan@indiana.edu\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISKosiński '23Venturini '18Zhang '23Orgeur '17Freedman '25Brown '25
61% semantic matchBioinformatics
Jan G. Kosiński, Marek Żywicki·PLoS Computational Biology·Oct 18, 2023