Hi, I analyzed scRNA-seq data. Using Seurat, we have an object with 19742genes in 2516 cells. In that, control group 525 cells, treatment group 1991 cells. by "FindMarkers" function I got the different gene expression matrix between the control (pct.1) and treatment (pct.2) groups.

```
>dim(mydata)
[1] 540 2
>mydata[1:10,1:2]
pct.1 pct.2
Fth1 0.996 1.000
Fosb 0.389 0.092
Prdx5 0.693 0.856
Slpi 0.175 0.529
Ccl7 0.425 0.161
Ass1 0.131 0.458
Apoe 0.413 0.164
Ly6a 0.187 0.500
Junb 0.916 0.888
Nos2 0.025 0.319
```

By "getGmt", I could get specific MSigDB dataset. then the codes are :

```
myC7 <- getGmt("h.all.v7.1.symbols.gmt")
mask <- lengths(geneIds(myC7)) > 1 ## make sure all dataset contain more than one gene
myC7filt <- myC7[mask]
score <- gsva(mydata, myC7filt, method= "ssgsea",
kcdf=c("Gaussian", "Poisson", "none"),abs.ranking=F,
min.sz=1,max.sz=Inf, parallel.sz=1L, mx.diff=T, ssgsea.norm=TRUE,verbose=T)
Estimating ssGSEA scores for 3 gene sets.
|============================================================================| 100%
Warning message:
In .gsva(expr, mapped.gset.idx.list, method, kcdf, rnaseq, abs.ranking, :
Some gene sets have size one. Consider setting 'min.sz > 1'.
> score
pct.1 pct.2
HALLMARK_COMPLEMENT 1.28481 2.28481
HALLMARK_XENOBIOTIC_METABOLISM 1.28481 2.28481
HALLMARK_COAGULATION 1.28481 2.28481
```

All these scores are the same in each group.???

if change "min.sz=2"

```
score <- gsva(mydata, myC7filt, method= "ssgsea",
kcdf=c("Gaussian", "Poisson", "none"),abs.ranking=F,
min.sz=2,max.sz=Inf, parallel.sz=1L, mx.diff=T, ssgsea.norm=TRUE,verbose=T)
>Error in .gsva(expr, mapped.gset.idx.list, method, kcdf, rnaseq, abs.ranking, :
The gene set list is empty! Filter may be too stringent.
```

I'm sorry I'm really amateur in learning R.

It's done. Thank you so much.