Comments (3)
Hi,
There is no implementation yet. But we are working on it. There will likely be an implementation in a month or two.
Best,
Martin
from scdrs.
Thanks for the super fast reply.
from scdrs.
Hi Noah,
I am following up on this issue.
We currently think it is a complicated issue. The main problem is that the target scRNA-seq data and the reference scRNA-seq data may have different modalities (e.g., collected using different technologies) and are not comparable. In this case, it is hard to make statements about false positive control of the method.
We did add a new option to adjust for cell group proportions. Specifically, it takes a set of cell group annotations and inversely weight cells by the cell group proportions (done implicitly within the computations of scDRS). This option may partially address the issue of the imbalanced data set. See the "adj_prop" option in https://martinjzhang.github.io/scDRS/reference_cli.html
It may take a while for us to finally add the option for using reference data sets. If it is urgent to your research project, a hacky way is to, after calling scdrs.preprocess
, substitute the mean_var
column in adata.uns["SCDRS_PARAM"]["GENE_STATS"]
with your own 20*20 mean-variance gene bins computed from the reference data (categorical). Then, you should be able to call scdrs.score_cell
, which finds control genes based on your definition of mean-variance gene bins.
Let me know if you have further questions.
Best,
Martin
from scdrs.
Related Issues (20)
- error metaclass conflict HOT 1
- Issues Plotting UMAP from quick start tutorial HOT 1
- gene weights for the control genes HOT 5
- Update dependencies of scDRS
- Gene weights or without gene weights HOT 3
- compute-score is not reading .gs file properly HOT 2
- custom gene set ? HOT 2
- The graphs from a single result and multiple results are inconsistent HOT 13
- Subsetting cells for downstream analysis. HOT 1
- TypeError: '<' not supported between instances of 'str' and 'float' HOT 3
- About compute-score
- Is it reasonable to use human' geneset on mouse scRNAseq data? HOT 2
- TypeError: plot_group_stats() got an unexpected keyword argument 'plot_kws' HOT 9
- trait=z_score: skipped due to small size (n_gene=5, sys_time=116.1s) HOT 1
- AssertionError when running quick test after installation HOT 7
- The 'n_fdr_0.2' number of all group is 0 HOT 7
- Interpreting scDRS score when comparing cell-type subclusters HOT 1
- Using geneset from SMR result HOT 1
- ValueError: too many values to unpack (expected 2) HOT 8
- Converting GWAS catalog .tsv file to gene set HOT 3
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from scdrs.