sc.tl.rank_genes_groups to rank only specific genes of interest?
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 2.6k
- Forks
- 779
- Avg merge
- 1d 4h
- Merged PRs (30d)
- 27
Description
After clustering cells with a restricted gene set, I would like to see the contribution of "specified genes" in subgrouping the cells.
sc.tl.rank_genes_groups uses all the genes in the background for the statistical calculations. I want to test it for all the Louvain groups against the rest of the data (so, groups='all', reference='rest').
Is there a way, we can specify the gene list? (I tried using the use_raw of sc.tl.rank_genes_groups to subset). I don't find any other options to restrict gene lists here.
subset_genes = ldata[:, ['Gabrg1', 'Ntrk1', 'Htr1a', 'Plaur', 'Il31ra', 'Gabrg3', 'P2rx3', 'Oprk1', 'P2ry1', 'Cnih3']]
sc.tl.rank_genes_groups(ldata, 'louvain', method='wilcoxon', use_raw= 'subset_genes', n_genes = 100)
sc.pl.rank_genes_groups(ldata, n_genes=15, sharey=False)
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading the sc.tl.rank_genes_groups entry point and how its use_raw, groups, reference, and n_genes options feed the statistical calculations. The change is complete when callers can provide a restricted gene list while retaining groups='all' and reference='rest', and sc.pl.rank_genes_groups displays the resulting rankings.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- bioinformatics
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 32/100