gsva error

[tcmlab]

library(limma)

p <- 10 ## number of genes
n <- 30 ## number of samples
nGrp1 <- 15 ## number of samples in group 1
nGrp2 <- n - nGrp1 ## number of samples in group 2

consider three disjoint gene sets

geneSets <- list(set1=paste("g", 1:3, sep=""),
set2=paste("g", 4:6, sep=""),
set3=paste("g", 7:10, sep=""))

sample data from a normal distribution with mean 0 and st.dev. 1

y <- matrix(rnorm(n*p), nrow=p, ncol=n,
dimnames=list(paste("g", 1:p, sep="") , paste("s", 1:n, sep="")))

genes in set1 are expressed at higher levels in the last 'nGrp1+1' to 'n' samples

y[geneSets$set1, (nGrp1+1):n] <- y[geneSets$set1, (nGrp1+1):n] + 2

build design matrix

design <- cbind(sampleGroup1=1, sampleGroup2vs1=c(rep(0, nGrp1), rep(1, nGrp2)))

fit linear model

fit <- lmFit(y, design)

estimate moderated t-statistics

fit <- eBayes(fit)

genes in set1 are differentially expressed

topTable(fit, coef="sampleGroup2vs1")

estimate GSVA enrichment scores for the three sets

gsva_es <- gsva(y, geneSets, mx.diff=1)
Error: useNames = NA is defunct. Instead, specify either useNames = TRUE or useNames = FALSE.

[tcmlab]

R version 4.2.2 Patched (2022-11-10 r83330)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.5 LTS

Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0

locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8 LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

attached base packages:
[1] grid stats graphics grDevices utils datasets methods base

other attached packages:
[1] limma_3.54.2 IOBR_0.99.8 survminer_0.4.9 patchwork_1.1.3 clusterProfiler_4.6.2
[6] tidyHeatmap_1.8.1 ComplexHeatmap_2.14.0 survival_3.4-0 ggpubr_0.6.0 ggplot2_3.4.4
[11] tibble_3.2.1 GSVA_1.46.0 nichenetr_2.0.4 dplyr_1.1.4 biomaRt_2.54.1

[rcastelo]

hi, this error is caused by a recent update in package dependency upstream from GSVA. To get this fixed, you should update to the current release of R (4.3.x) and Bioconductor (3.18 and GSVA 1.50.x). Let me know if you are unsure on how to do this.

[sunPi]

@rcastelo What about a solution for Linux? There is no greater release of R than 4.2.x afaik and therefore the GSVA does not work due to the same error reported in this issue.

[rcastelo]

Hi @sunPi Linux is the main platform where R, and particularly GSVA, are developed. You can find the latest release of R 4.3.x for Linux, as well as Windows and macOS, in https://cran.r-project.org. If you want or need to install R in Linux in a different way, i.e., through some package manager system, then you should consult the maintainers of that package manager system about how to update R to 4.3.x, but certainly there is R 4.3.x for Linux.