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Combining RNA-seq data and homology-based gene prediction for plants, animals and fungi.

BMC bioinformatics | 2018

Genome annotation is of key importance in many research questions. The identification of protein-coding genes is often based on transcriptome sequencing data, ab-initio or homology-based prediction. Recently, it was demonstrated that intron position conservation improves homology-based gene prediction, and that experimental data improves ab-initio gene prediction.

Pubmed ID: 29843602 RIS Download

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This is a list of tools and resources that we have found mentioned in this publication.


WormBase (tool)

RRID:SCR_003098

Central data repository for nematode biology including complete genomic sequence, gene predictions and orthology assignments from range of related nematodes.Data concerning genetics, genomics and biology of C. elegans and related nematodes. Derived from initial ACeDB database of C. elegans genetic and sequence information, WormBase includes genomic, anatomical and functional information of C. elegans, other Caenorhabditis species and other nematodes. Maintains public FTP site where researchers can find many commonly requested files and datasets, WormBase software and prepackaged databases.

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Systems Transcriptional Activity Reconstruction (tool)

RRID:SCR_005622

A next-generation web-based application that aims to provide an integrated solution for both visualization and analysis of deep-sequencing data, along with simple access to public datasets.

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BLAT (tool)

RRID:SCR_011919

Software designed to quickly find sequences of 95% and greater similarity of length 25 bases or more.

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Trinity (tool)

RRID:SCR_013048

Software for the efficient and robust de novo reconstruction of transcriptomes from RNA-seq data.

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Cufflinks (tool)

RRID:SCR_014597

Software tool for transcriptome assembly and differential expression analysis for RNA-Seq. Includes script called cuffmerge that can be used to merge together several Cufflinks assemblies. It also handles running Cuffcompare as well as automatically filtering a number of transfrags that are likely to be artifacts. If the researcher has a reference GTF file, the researcher can provide it to the script to more effectively merge novel isoforms and maximize overall assembly quality.

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