Result of gsva is all NA

[YihengJiang0912]

Dear authors, I am now using ssgsea method in gsva to evaluate the samples' enrichment score in a dataset, but the result is all NA, I would be very grateful if you could give me some guidance on that.

Belowing please kindly find the result:
`> dim(expr_m)
[1] 20502 10122

ssGSEA_matrix <- gsva(expr = expr_m,
gset.idx.list = my_signature,
method = 'ssgsea',
kcdf = "Gaussian",
min.sz > 1,
abs.ranking = TRUE)
Estimating ssGSEA scores for 14 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
|=========================================================================================================| 100%

[1] "Normalizing..."
Warning messages:
1: In .filterFeatures(expr, method) :
4180 genes with constant expression values throuhgout the samples.
2: In .gsva(expr, mapped.gset.idx.list, method, kcdf, rnaseq, abs.ranking, :
Some gene sets have size one. Consider setting 'min.sz > 1'.

ssGSEA_matrix[1:5,1:5]
TCGA-OR-A5J1-01 TCGA-OR-A5J2-01 TCGA-OR-A5J3-01 TCGA-OR-A5J5-01 TCGA-OR-A5J6-01
Immune.enrichment.score NA NA NA NA NA
Immune.cell.subsets NA NA NA NA NA
Immune.signaling.molecules NA NA NA NA NA
X13.T.cell.signature NA NA NA NA NA
T.cells NA NA NA NA NA
`

However, if I only use part of my dataset, I can get the results:

`> ssGSEA_matrix <- gsva(expr = expr_m[,1:100],
gset.idx.list = my_signature,
method = 'ssgsea',
kcdf = "Gaussian",
min.sz > 1,
abs.ranking = TRUE)
Estimating ssGSEA scores for 14 gene sets.
[1] "Calculating ranks..."
[1] "Calculating absolute values from ranks..."
|=========================================================================================================| 100%

[1] "Normalizing..."
Warning messages:
1: In .filterFeatures(expr, method) :
571 genes with constant expression values throuhgout the samples.
2: In .gsva(expr, mapped.gset.idx.list, method, kcdf, rnaseq, abs.ranking, :
Some gene sets have size one. Consider setting 'min.sz > 1'.

ssGSEA_matrix[1:5,1:5]
TCGA-OR-A5J1-01 TCGA-OR-A5J2-01 TCGA-OR-A5J3-01 TCGA-OR-A5J5-01 TCGA-OR-A5J6-01
Immune.enrichment.score 0.07036719 0.04767565 -0.001057149 0.00694892 0.13481281
Immune.cell.subsets -0.24078220 -0.22031222 -0.299557598 -0.29809871 -0.18673913
Immune.signaling.molecules -0.25096208 -0.19650415 -0.319315871 -0.30783535 -0.18980250
X13.T.cell.signature -0.06467369 -0.03327788 -0.166935307 -0.18018616 0.02333241
T.cells
`

[axelklenk]

Dear Yiheng Jiang,

the easiest way to solve your problem probably is to upgrade to the latest version, i.e. R-4.4.0, Bioconductor 3.19 and GSVA 1.52.0 (or later), brandnew and available since last week.

In that latest version, the old API for GSVA that you are currently using is defunct and you would have to change your code to use e.g.:

sp <- ssgseaParam(exprData=expr_m, geneSets=my_signature, minSize=10)
ssGSEA_matrix <- gsva(sp)

In addition, please note that

• arguments kcdf and absRanking apply only to method GSVA and have no effect when using ssGSEA.
• argument min.sz, now renamed to minSize, must be a numerical value specifying the minimum size for gene sets to use; in the example above I have set it to 10. (I realize that the sentence Consider setting 'min.sz > 1'., as used by the warning message, is misleading and we should change it.)

However, even going back to the latest version accepting your code ( R-4.3.3, Bioconductor 3.18, GSVA 1.50.5) I have tried and could not reproduce your problem using test data -- are there NA values in your data in expr_m[, 101:10122] ? What does e.g. any(is.na(expr_m)) say?

If upgrading doesn't solve your problem and it is not caused by NA values in your data, please let me know and do not forget to include the output of sessionInfo().