Abstract
GeMoMa is a homology-based gene prediction program that predicts gene models in target species based on gene models in evolutionary related reference species. GeMoMa utilizes amino acid sequence conservation, intron position conservation, and RNA-seq data to accurately predict protein-coding transcripts. Furthermore, GeMoMa supports the combination of predictions based on several reference species allowing to transfer high-quality annotation of different reference species to a target species. Here, we present a detailed description of GeMoMa modules and the GeMoMa pipeline and how they can be used on the command line to address particular biological problems.
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Keilwagen, J., Hartung, F., Grau, J. (2019). GeMoMa: Homology-Based Gene Prediction Utilizing Intron Position Conservation and RNA-seq Data. In: Kollmar, M. (eds) Gene Prediction. Methods in Molecular Biology, vol 1962. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9173-0_9
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DOI: https://doi.org/10.1007/978-1-4939-9173-0_9
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