Timeline for GSEA enrichr with 10x genomics differential_expression ranks
Current License: CC BY-SA 4.0
5 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jul 11, 2020 at 22:50 | comment | added | burger | What do you mean by "not present"? Do you mean detectable in only one cluster? If they are only detectable in one, then they should already be your top cluster markers by fold change or p-value. | |
| Jul 10, 2020 at 10:58 | comment | added | 719016 | would it be adequate to trim down the list of genes by making sure they are not present in other clusters? E.g. find the X-most genes in Cluster 1 where none or only, say, 10-20% of them are in Custers 2 to N. Is that a reasonable approach? Thanks in advance. | |
| Jul 9, 2020 at 21:19 | comment | added | burger | Depends on your dataset. It's usually very difficult to have 100 genes that identify the cluster well. You can pick the last gene and see how well it actually marks that cluster. | |
| Jul 9, 2020 at 15:21 | comment | added | 719016 | What's a good number smaller than 100? 50? Thx | |
| Jul 9, 2020 at 14:49 | history | answered | burger | CC BY-SA 4.0 |