d2ac08231c388dcae68ce7031d5a7dddb91beb97 hiram Mon Sep 12 10:55:19 2022 -0700 expanded documentation from Michael refs #29982 diff --git src/hg/makeDb/trackDb/TOGAannotation.html src/hg/makeDb/trackDb/TOGAannotation.html index 839dafa..c201476 100644 --- src/hg/makeDb/trackDb/TOGAannotation.html +++ src/hg/makeDb/trackDb/TOGAannotation.html @@ -1,34 +1,82 @@

Description

-Tool to infer Orthologs from Genome Alignments +TOGA +(Tool to infer Orthologs from Genome Alignments) +is a homology-based method that integrates gene annotation, inferring +orthologs and classifying genes as intact or lost.

+ +

Methods

-TOGA is a new method that integrates gene annotation, inferring orthologs -and classifying genes as intact or lost. +As input, TOGA uses a gene annotation of a reference species +(human/hg38 for mammals, chicken/galGal6 for birds) and +a whole genome alignment between the reference and query genome.

-TOGA implements a novel machine learning based paradigm to infer -orthologous genes between related species and to accurately distinguish +TOGA implements a novel paradigm that relies on alignments of intronic +and intergenic regions and uses machine learning to accurately distinguish orthologs from paralogs or processed pseudogenes.

+

+To annotate genes, +CESAR 2.0 +is used to determine the positions and boundaries of coding exons of a +reference transcript in the orthologous genomic locus in the query species. +

+ +

Display Conventions and Configuration

+

+Each annotated transcript is shown in a color-coded classification as +

+

+

+Clicking on a transcript provides additional information about the orthology +classification, inactivating mutations, the protein sequence and protein/exon +alignments. +

Credits

This data was prepared by the Michael Hiller Lab

References

The TOGA software is available from github.com/hillerlab/TOGA

Kirilenko BM, Munegowda C, Osipova E, Jebb D, Sharma V, Blumer M, Morales A, Ahmed AW, Kontopoulos DG, Hilgers L, Zoonomia Consortium, Hiller M. Integrating gene annotation with orthology inference at scale. Under Review