Orthograph: a versatile tool for mapping coding nucleotide sequences to clusters of orthologous genes

Published on Dec 1, 2017in BMC Bioinformatics2.51
· DOI :10.1186/s12859-017-1529-8
Malte Petersen11
Estimated H-index: 11
Karen Meusemann19
Estimated H-index: 19
(University of Freiburg)
+ 8 AuthorsOliver Niehuis22
Estimated H-index: 22
(University of Freiburg)
Background Orthology characterizes genes of different organisms that arose from a single ancestral gene via speciation, in contrast to paralogy, which is assigned to genes that arose via gene duplication. An accurate orthology assignment is a crucial step for comparative genomic studies. Orthologous genes in two organisms can be identified by applying a so-called reciprocal search strategy, given that complete information of the organisms’ gene repertoire is available. In many investigations, however, only a fraction of the gene content of the organisms under study is examined (e.g., RNA sequencing). Here, identification of orthologous nucleotide or amino acid sequences can be achieved using a graph-based approach that maps nucleotide sequences to genes of known orthology. Existing implementations of this approach, however, suffer from algorithmic issues that may cause problems in downstream analyses.
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