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First thank you for developing such great tools. I used mini-Ex recently on my scRNAseq data with great success.
I tried to run mini-Ac using data from snATAC seq (from 10x genomic multiome kit on Arabidopsis).
While the pipeline ran correctly I got no enrichments in the output files whatsoever, for any of my 8 different cell types.
I know mini-Ac was designed mostly to work on bulk ATACseq that is probably richer and less noisy than snATAC-seq but
are there some parameters I could play with to improve the pipeline prediction on such datasets ?
I get about from 10k to 2k specific peaks depending on the cell type.
Thanks in advance for your help,
Bruno
The text was updated successfully, but these errors were encountered:
Sorry for the late reply. You can play with the P_val parameter to set a different threshold for the enrichment analysis. By default, the p-value threshold is 0.01 in locus-based mode, and 0.1 in genome-wide mode. Increasing the threshold should yield more enrichments in the output, but be aware that these are then statistically less significant.
Dear mini-Ac developers,
First thank you for developing such great tools. I used mini-Ex recently on my scRNAseq data with great success.
I tried to run mini-Ac using data from snATAC seq (from 10x genomic multiome kit on Arabidopsis).
While the pipeline ran correctly I got no enrichments in the output files whatsoever, for any of my 8 different cell types.
I know mini-Ac was designed mostly to work on bulk ATACseq that is probably richer and less noisy than snATAC-seq but
are there some parameters I could play with to improve the pipeline prediction on such datasets ?
I get about from 10k to 2k specific peaks depending on the cell type.
Thanks in advance for your help,
Bruno
The text was updated successfully, but these errors were encountered: