Question: Are the "Mean UMI Counts" from differential expression analysis in Cell Ranger normalized?
(Note: "Mean UMI Counts" in Cell Ranger is the same as "Average" in Loupe Cell Browser).
$ head -5 analysis/diffexp/kmeans_3_clusters/differential_expression.csv
Gene ID,Gene Name,Cluster 1 Mean UMI Counts,Cluster 1 Log2 fold change,Cluster 1 Adjusted p value,Cluster 2 Mean UMI Counts,Cluster 2 Log2 fold change,Cluster 2 Adjusted p value,Cluster 3 Mean UMI Counts,Cluster 3 Log2 fold change,Cluster 3 Adjusted p value ENSG00000228327,RP11-206L10.2,0.0056858989363338264,2.6207666981569986,0.00052155805898912184,0.0,-0.75299726644507814,0.64066099091888962,0.00071455453829430329,-2.3725403666493312,0.0043023680184636837 ENSG00000237491,RP11-206L10.9,0.00012635330969630726,-0.31783275717885928,0.40959138980118809,0.0,3.8319652342760779,0.11986963938734894,0.0,0.56605908868652577,0.39910771338768203 ENSG00000177757,FAM87B,0.0,-2.9027952579000154,0.0,0.0,3.2470027335549219,0.19129034227967889,0.00071455453829430329,3.1510215894076818,0.0 ENSG00000225880,LINC00115,0.0003790599290889218,-5.71015017995762,8.4751637615375386e-28,0.20790015775229512,7.965820981010868,1.3374521290889345e-46,0.0017863863457357582,-2.2065304152104019,0.00059189960914085744
Answer: Yes, the "Mean UMI Counts" value reported is normalized by the size factors used in differential expression analysis. The size factor is the total UMI counts for each cell divided by the median UMI counts per cell.
The Cell Ranger differential expression analysis and "Significant Genes" analysis in Loupe Cell Browser are expected to be the same. Likewise, the "Average" value reported in the "Significant Genes" table in Loupe Cell Browser is also normalized by the size factors.
For more information on the differential expression analysis, please see the matching section in the algorithms overview.
To explore the code for differential expression analysis on your own, please see the source code.
Disclaimer: This article and code-snippet are provided for instructional purposes only. 10x Genomics does not support or guarantee the code.