pySCENIC cannot reproduce AUCell + tSNE projection from a tutorial

[ninhleba]

Hi,

I've been testing pySCENIC by following this tutorial: http://htmlpreview.github.io/?https://github.com/aertslab/SCENICprotocol/blob/master/notebooks/SCENIC%20Protocol%20-%20Case%20study%20-%20Cancer%20data%20sets.html. The dataset I tried was the first one (Accession ID: GSE115978, Cancer type: SKCM). Everything looked pretty compatible until the AUCell + tSNE projection, which didn't seem to be able to cluster cells by cell type at all, in contrast with the corresponding plot in the tutorial.

Previous steps such as grn, ctx and aucell ran smoothly, and the clustermap based on binarized AUCell matrix I obtained also suggests tSNE computed from AUCell scores should be able to cluster out at least half the number of cell types.

I understand the nature of the algorithm makes the outputs of different runs vary slightly from one another but I don't think they should by this much. I don't think the error stems from tSNE because the PCA + tSNE projection looks like it's supposed to.

I would really appreciate it if someone could share their thoughts on this.

Here are the databases that I used:

• Human TFs: https://github.com/aertslab/pySCENIC/blob/master/resources/lambert2018.txt

• Ranking databases: https://resources.aertslab.org/cistarget/databases/homo_sapiens/hg19/refseq_r45/mc9nr/gene_based/

  • hg19-500bp-upstream-10species.mc9nr.genes_vs_motifs.rankings.feather
  • hg19-tss-centered-5kb-10species.mc9nr.genes_vs_motifs.rankings.feather
  • hg19-tss-centered-10kb-10species.mc9nr.genes_vs_motifs.rankings.feather

• Motifs annotation: https://resources.aertslab.org/cistarget/motif2tf/motifs-v9-nr.hgnc-m0.001-o0.0.tbl

Here is my session info:

-----
anndata             0.8.0
cytoolz             0.12.1
matplotlib          3.7.1
numpy               1.23.5
pandas              1.5.3
pyscenic            0.12.1
scanpy              1.9.3
seaborn             0.12.2
session_info        1.0.0
-----
PIL                         9.4.0
appnope                     0.1.2
asttokens                   NA
attr                        22.1.0
backcall                    0.2.0
boltons                     NA
cffi                        1.15.1
cloudpickle                 2.2.1
comm                        0.1.2
ctxcore                     0.2.0
cycler                      0.10.0
cython_runtime              NA
dask                        2023.3.0
dateutil                    2.8.2
debugpy                     1.5.1
decorator                   5.1.1
defusedxml                  0.7.1
entrypoints                 0.4
executing                   0.8.3
frozendict                  2.3.5
fsspec                      2023.3.0
h5py                        3.8.0
ipykernel                   6.19.2
ipython_genutils            0.2.0
jedi                        0.18.1
jinja2                      3.1.2
joblib                      1.2.0
jupyter_server              1.23.4
kiwisolver                  1.4.4
llvmlite                    0.39.1
loompy                      3.0.7
lxml                        4.9.1
markupsafe                  2.1.1
matplotlib_inline           0.1.6
mpl_toolkits                NA
natsort                     8.3.1
networkx                    3.0
numba                       0.56.4
numexpr                     2.8.4
numpy_groupies              0.9.20
openpyxl                    3.1.1
packaging                   22.0
parso                       0.8.3
pexpect                     4.8.0
pickleshare                 0.7.5
pkg_resources               NA
platformdirs                2.5.2
prompt_toolkit              3.0.36
psutil                      5.9.0
ptyprocess                  0.7.0
pure_eval                   0.2.2
pyarrow                     11.0.0
pycparser                   2.21
pydev_ipython               NA
pydevconsole                NA
pydevd                      2.6.0
pydevd_concurrency_analyser NA
pydevd_file_utils           NA
pydevd_plugins              NA
pydevd_tracing              NA
pygments                    2.11.2
pyparsing                   3.0.9
pytz                        2022.7
scipy                       1.10.1
setuptools                  65.6.3
six                         1.16.0
sklearn                     1.2.2
stack_data                  0.2.0
statsmodels                 0.13.5
tblib                       1.7.0
threadpoolctl               3.1.0
tlz                         0.12.1
toolz                       0.12.0
tornado                     6.2
tqdm                        4.65.0
traitlets                   5.7.1
typing_extensions           NA
wcwidth                     0.2.5
yaml                        6.0
zmq                         23.2.0
zoneinfo                    NA
-----
IPython             8.10.0
jupyter_client      7.4.9
jupyter_core        5.2.0
jupyterlab          3.5.3
notebook            6.5.2
-----
Python 3.10.9 (main, Mar  8 2023, 04:44:36) [Clang 14.0.6 ]
macOS-10.16-x86_64-i386-64bit
-----
Session information updated at 2023-03-20 14:01