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oggmap: a Python package to extract gene ages per orthogroup and link them with single-cell RNA data

Authors: Kristian K. Ullrich; Nikoleta E. Glynatsi;

oggmap: a Python package to extract gene ages per orthogroup and link them with single-cell RNA data

Abstract

Abstract Summary For model species, single-cell RNA-based cell atlases are available. A good cell atlas includes all major stages in a species’ ontogeny, and soon, they will be standard even for nonmodel species. Here, we propose a Python package called oggmap, which allows for the easy extraction of an orthomap (gene ages per orthogroup) for any given query species from OrthoFinder and other gene family data resources, like homologous groups from eggNOG or PLAZA. oggmap provides extracted gene ages for more than thousand eukaryotic species which can be further used to calculate gene age-weighted expression data from scRNA sequencing objects using the Python Scanpy toolkit. Not limited to one transcriptome evolutionary index, oggmap can visualize the individual gene category (e.g. age class, nucleotide diversity bin) and their corresponding expression profiles to investigate scRNA-based cell type assignments in an evolutionary context. Availability and implementation oggmap source code is available at https://github.com/kullrich/oggmap, documentation is available at https://oggmap.readthedocs.io/en/latest/. oggmap can be installed via PyPi or directly used via a docker container.

Keywords

Applications Note, Documentation, Software

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Top 10%
Average
Top 10%
Green
gold