sc.tl.marker_gene_overlap() give the same values to each cluster

Dear There,

I recently re-installed the single cell environment. Then, the example code of sc.tl.marker_gene_overlap() on scanpy tutorial does not work. It give the same values to each cluster. Thanks for your help!

Lianyun

import scanpy as sc
adata = sc.datasets.pbmc68k_reduced()
sc.pp.pca(adata, svd_solver='arpack')
sc.pp.neighbors(adata)
sc.tl.louvain(adata)
sc.tl.rank_genes_groups(adata, groupby='louvain')
marker_genes = {'CD4 T cells': {'IL7R'},
                'CD14+ Monocytes': {'CD14', 'LYZ'},
                'B cells': {'MS4A1'},
                'CD8 T cells': {'CD8A'},
                'NK cells': {'GNLY', 'NKG7'},
                'FCGR3A+ Monocytes': {'FCGR3A', 'MS4A7'},
                'Dendritic Cells': {'FCER1A', 'CST3'},
                'Megakaryocytes': {'PPBP'}}
marker_matches = sc.tl.marker_gene_overlap(adata, marker_genes)

	0	1	2	3	4	5	6
CD4 T cells	1.0	1.0	1.0	1.0	1.0	1.0	1.0
CD14+ Monocytes	1.0	1.0	1.0	1.0	1.0	1.0	1.0
B cells	1.0	1.0	1.0	1.0	1.0	1.0	1.0
CD8 T cells	1.0	1.0	1.0	1.0	1.0	1.0	1.0
NK cells	2.0	2.0	2.0	2.0	2.0	2.0	2.0
FCGR3A+ Monocytes	1.0	1.0	1.0	1.0	1.0	1.0	1.0
Dendritic Cells	2.0	2.0	2.0	2.0	2.0	2.0	2.0
Megakaryocytes	0.0	0.0	0.0	0.0	0.0	0.0	0.0
![image](https://user-images.githubusercontent.com/57720451/92608724-029c7880-f2b6-11ea-9860-59c705183fb2.png)

Versions

---

anndata 0.7.4 scanpy 1.6.0 sinfo 0.3.1

PIL 7.2.0 anndata 0.7.4 backcall 0.2.0 cffi 1.14.1 cycler 0.10.0 cython_runtime NA dateutil 2.8.1 decorator 4.4.2 get_version 2.1 h5py 2.10.0 igraph 0.8.2 ipykernel 5.3.4 ipython_genutils 0.2.0 jedi 0.15.2 joblib 0.16.0 kiwisolver 1.2.0 legacy_api_wrap 1.2 llvmlite 0.34.0 louvain 0.7.0 matplotlib 3.3.1 mpl_toolkits NA natsort 7.0.1 numba 0.51.2 numexpr 2.7.1 numpy 1.19.1 packaging 20.4 pandas 1.1.1 parso 0.5.2 pexpect 4.8.0 pickleshare 0.7.5 pkg_resources NA prompt_toolkit 3.0.7 ptyprocess 0.6.0 pycparser 2.20 pygments 2.6.1 pyparsing 2.4.7 pytz 2020.1 scanpy 1.6.0 scipy 1.5.2 setuptools_scm NA sinfo 0.3.1 six 1.15.0 sklearn 0.23.2 statsmodels 0.12.0 storemagic NA tables 3.6.1 texttable 1.6.3 tornado 6.0.4 traitlets 4.3.3 umap 0.4.6 wcwidth 0.2.5 zmq 19.0.2

IPython 7.18.1 jupyter_client 6.1.7 jupyter_core 4.6.3 notebook 6.1.3

Python 3.8.5 | packaged by conda-forge | (default, Aug 29 2020, 01:22:49) [GCC 7.5.0] Linux-3.10.0-1062.9.1.el7.x86_64-x86_64-with-glibc2.10 128 logical CPU cores, x86_64

Session information updated at 2020-09-09 15:47

[LuckyMD]

Thanks @jpreall and @suzhanhao for jumping in with solutions here. I have finally found some time to look at this. The recent change is that sc.tl.rank_genes_groups now saves DE results not just for the top 100 genes, but for all genes. So the default for top_n_markers, which was to use all genes that have results stored automatically shifted from 100 genes to all genes. And if you look at overlaps between all genes and your gene list, you will of course get 1. The only change that is needed here would be to set the default top_n_markers = 100. That should be a 5 character change to the function 😉.

[LuckyMD]

Addressed by #1464