orthomap is a python package to extract orthologous maps
(in other words the evolutionary age of a given orthologous group) from OrthoFinder results.
Orthomap results (gene ages per orthogroup) can be further used to calculate weigthed expression data
from scRNA sequencing objects.
The environment is created with conda create in which orthomap is installed.
If you do not have a working installation of Python 3.7 (or later), consider installing Miniconda (see Installing Miniconda). Then run:
$ conda env create --file environment.yml
$ conda activate orthomapInstall orthomap:
$ pip install orthomapInstall orthomap into your current python environment:
$ pip install orthomapOnline documentation can be found here.
The following command downloads or updates your local copy of the
NCBI's taxonomy database (~300MB). The database is saved at
~/.etetoolkit/taxa.sqlite.
>>> from orthomap import ncbitax
>>> ncbitax.update_ncbi()You can query a species lineage information based on its name or its
taxid. For example Danio rerio with taxid 7955:
>>> from orthomap import qlin
>>> qlin.get_qlin(q = 'Danio rerio')
>>> qlin.get_qlin(qt = '7955')You can get the query species topology as a tree.
For example for Danio rerio with taxid 7955:
>>> from orthomap import qlin
>>> query_topology = qlin.get_lineage_topo(qt = '7955')
>>> query_topology.write()The following code extracts the orthomap for Danio rerio based on the
OrthoFinder results and ensembl release-105:
OrthoFinder results files have been archived and can be found here.
>>> from orthomap import of2orthomap
>>> query_orthomap, orthofinder_species_list, of_species_abundance =\
... of2orthomap.get_orthomap(
... seqname='Danio_rerio.GRCz11.cds.longest',
... qt='7955',
... sl='ensembl_105_orthofinder_species_list.tsv',
... oc='ensembl_105_orthofinder_Orthogroups.GeneCount.tsv',
... og='ensembl_105_orthofinder_Orthogroups.tsv',
... continuity=True)The following code extracts the gene to transcript table for Danio rerio:
GTF file obtained from here.
>>> from orthomap import gtf2t2g
>>> query_species_t2g = gtf2t2g.parse_gtf(
... gtf='Danio_rerio.GRCz11.105.gtf.gz',
... g=True, b=True, p=True, v=True, s=True, q=True)>>> from orthomap import gtf2t2g
>>> file = 'examples/Mus_musculus.GRCm39.108.chr.gtf.gz'
>>> df = gtf2t2g.parse_gtf(file, g=True, p=True, s=True, q=True, v=True)
>>> df.head()
gene_id gene_id_version transcript_id transcript_id_version gene_name gene_type protein_id protein_id_version
0 ENSMUSG00000102628 ENSMUSG00000102628.2 ENSMUST00000193198 ENSMUST00000193198.2 Gm37671 None None None
1 ENSMUSG00000100595 ENSMUSG00000100595.2 ENSMUST00000191430 ENSMUST00000191430.2 Gm19087 None None Noneexample: Danio rerio - http://tome.gs.washington.edu (Qui et al. 2022)
AnnData file can be found here.
>>> from orthomap import orthomap2tei
>>> zebrafish_data = sc.read('zebrafish_data.h5ad')Check overlap of orthomap and scRNA data set:
orthomap2tei.geneset_overlap(zebrafish_data.var_names, query_orthomap['seqID'])Convert orthomap transcript IDs into GeneIDs and add them to orthomap:
>>> query_orthomap['geneID'] = orthomap2tei.replace_by(
... x_orig = query_orthomap['seqID'],
... xmatch = query_species_t2g['transcript_id_version'],
... xreplace = query_species_t2g['gene_id'])Add TEI values to existing adata object:
>>> tei_df = orthomap2tei.get_tei(adata=zebrafish_data,
... gene_id=query_orthomap['geneID'],
... gene_age=query_orthomap['PSnum'],
... add=True)Boxplot TEI per stage:
sc.pl.violin(zebrafish_data, ['tei'], groupby='stage')orthomap can also be used via the command line. To retrieve
the lineage information for Danio rerio run the following command:
$ python src/orthomap/qlin.py -q "Danio rerio"To retrieve the gene to transcript table for Danio rerio run the following command:
$ python src/orthomap/gtf2t2g.py -g -s -q -i "Danio_rerio.GRCz11.105.gtf.gz"To work with the latest version on GitHub: clone the repository and cd into its root directory.
$ git clone kullrich/orthomap
$ cd orthomapInstall orthomap into your current python environment:
$ pip install -e .After downloading Miniconda, in a unix shell (Linux, Mac), run
$ cd DOWNLOAD_DIR
$ chmod +x Miniconda3-latest-VERSION.sh
$ ./Miniconda3-latest-VERSION.shIf you would like to contribute to orthomap, please file an issue so that one can establish a statement of need, avoid redundant work, and track progress on your contribution.
Before you do a pull request, you should always file an issue and make sure that someone from the orthomap developer team agrees that it's a problem, and is happy with your basic proposal for fixing it.
Once an issue has been filed and we've identified how to best orient your
contribution with package development as a whole,
fork
the main repo, branch off a
feature
branch
from master,
commit
and
push
your changes to your fork and submit a pull
request
for orthomap:master.
By contributing to this project, you agree to abide by the Code of Conduct terms.
Please report any errors or requests regarding orthomap to Kristian Ullrich (ullrich@evolbio.mpg.de)
or use the issue tracker.
This repository adheres to the Contributor Covenant code of conduct for in any interactions you have within this project. (see Code of Conduct)
See also the policy against sexualized discrimination, harassment and violence for the Max Planck Society Code-of-Conduct.
By contributing to this project, you agree to abide by its terms.
Emms, D.M. and Kelly, S. (2019). OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome biology, 20(1). https://doi.org/10.1186/s13059-019-1832-y
Huerta-Cepas, J., Serra, F. and Bork, P. (2016). ETE 3: reconstruction, analysis, and visualization of phylogenomic data. Molecular biology and evolution, 33(6). https://doi.org/10.1093/molbev/msw046
Wolf, F.A., Angerer, P. and Theis, F.J. (2018). SCANPY: large-scale single-cell gene expression data analysis. Genome biology, 19(1). https://doi.org/10.1186/s13059-017-1382-0
Qiu, C., Cao, J., Martin, B.K., Li, T., Welsh, I.C., Srivatsan, S., Huang, X., Calderon, D., Noble, W.S., Disteche, C.M. and Murray, S.A. (2022). Systematic reconstruction of cellular trajectories across mouse embryogenesis. Nature genetics, 54(3). https://doi.org/10.1038/s41588-022-01018-x