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theislab / single-cell-tutorial

Single cell current best practices tutorial case study for the paper:Luecken and Theis, "Current best practices in single-cell RNA-seq analysis: a tutorial"
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Interpretation of rank_genes_groups #89

Closed Lavieenrose123 closed 2 years ago

Lavieenrose123 commented 2 years ago

Hi,

Thank you providing such a wonderful tutorial!

I'm using version 1.8.2 of scanpy and the same code from Case-study_Mouse-intestinal-epithelium_1906.ipynb. According to the official tutorial of scanpy, the scores in output from rank_genes_groups were z-score of pvals. If so, a higher score indicate a large p-value. However, the pvals in the output of rank_genes_groups_df were not monotonically changed while the scores were.

My questions are:

  1. How to calculate scores?
  2. How to interpret scores ？
  3. How to obtain negative markers?

Thanks!

LuckyMD commented 2 years ago

Hi @Lavieenrose123,

I think this question is better asked in the scanpy github, rather than here. I'm not sure exactly what the scores are. I think they are probably t-test statistics (if using the t-test via sc.tl.rank_genes_groups). In that case higher scores indicate lower p-values.