Evidence map›Paper›PMID 26559507›Full record

ArticleBioinformatics (Oxford, England)2016

BRAKER1: Unsupervised RNA-Seq-Based Genome Annotation with GeneMark-ET and AUGUSTUS.

Katharina J Hoff, Simone Lange, Alexandre Lomsadze, Mark Borodovsky, Mario Stanke

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 694 papers.

0numbers the graph read from it
0cells of the map it votes in
694citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

694 citing papers in PubMed.

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634 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

5 authors.

Katharina J HoffErnst Moritz Arndt Universität Greifswald, Institute for Mathematics and Computer Science, 17487 Greifswald, Germany.
Simone LangeErnst Moritz Arndt Universität Greifswald, Institute for Mathematics and Computer Science, 17487 Greifswald, Germany.
Alexandre LomsadzeJoint Georgia Tech and Emory University Wallace H Coulter Department of Biomedical Engineering, Atlanta, GA 30332, USA and.
Mark BorodovskySchool of Computational Science and Engineering, Atlanta, GA 30332, USA, Joint Georgia Tech and Emory University Wallace H Coulter Department of Biomedical Engineering, Atlanta, GA 30332, USA and Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russia.
Mario StankeErnst Moritz Arndt Universität Greifswald, Institute for Mathematics and Computer Science, 17487 Greifswald, Germany.

Funding

PREDICTION OF GENE LOCATIONS USING STOCHASTIC MODELSR01HG000783 · NHGRI · GEORGIA INSTITUTE OF TECHNOLOGY · PI BORODOVSKY, MARK · 1993 to 2014
$4.7M
NIGMS Administrative Supplements to Support Undergraduate Summer ResearchR01GM128145 · NIGMS · GEORGIA INSTITUTE OF TECHNOLOGY · PI BORODOVSKY, MARK · 2018 to 2021
$1.1M
NHGRI NIH HHS R01 HG000783NIGMS NIH HHS R01 GM128145
6 · The paper itself

Abstract

motivationGene finding in eukaryotic genomes is notoriously difficult to automate. The task is to design a work flow with a minimal set of tools that would reach state-of-the-art performance across a wide range of species. GeneMark-ET is a gene prediction tool that incorporates RNA-Seq data into unsupervised training and subsequently generates ab initio gene predictions. AUGUSTUS is a gene finder that usually requires supervised training and uses information from RNA-Seq reads in the prediction step. Complementary strengths of GeneMark-ET and AUGUSTUS provided motivation for designing a new combined tool for automatic gene prediction.

resultsWe present BRAKER1, a pipeline for unsupervised RNA-Seq-based genome annotation that combines the advantages of GeneMark-ET and AUGUSTUS. As input, BRAKER1 requires a genome assembly file and a file in bam-format with spliced alignments of RNA-Seq reads to the genome. First, GeneMark-ET performs iterative training and generates initial gene structures. Second, AUGUSTUS uses predicted genes for training and then integrates RNA-Seq read information into final gene predictions. In our experiments, we observed that BRAKER1 was more accurate than MAKER2 when it is using RNA-Seq as sole source for training and prediction. BRAKER1 does not require pre-trained parameters or a separate expert-prepared training step. AVAILABILITY AND IMPLEMENTATION: BRAKER1 is available for download at http://bioinf.uni-greifswald.de/bioinf/braker/ and http://exon.gatech.edu/GeneMark/ CONTACT: katharina.hoff@uni-greifswald.de or borodovsky@gatech.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

Sequence Analysis, RNAEukaryotaGenomeRNASoftwareRNA

Identifiers

PMID26559507
PMCPMC6078167

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.