Closed joshscurll closed 1 year ago
I am attempting to use the mixedModelDE function for differential expression analysis (post- vs pre-treatment tissue) as per Section 7.3 in the GeoMx Workflows vignette (https://bioconductor.org/packages/release/workflows/vignettes/GeoMxWorkflows/inst/doc/GeomxTools_RNA-NGS_Analysis.html#73_Between_Slide_Analysis:_Diabetic_Kidney_Disease_vs_Healthy). In my case, I am analysing pre- and post-treatment tissue from a single patient, so I have no need to include any variable in the model intercept, but otherwise my code is the same as the vignette. However, mixedModelDE returns "object 'testClass' not found" as an error. This error seems to have been encountered by someone else here: https://bytemeta.vip/repo/Nanostring-Biostats/GeomxTools/issues/174. I have added a "testClass" factor column to my pData and included it in the model formula as in the vignette, so I don't know how to resolve this error.
Here is my code that produces the error: ` pData(target_DSPdata)$testClass <- factor(pData(target_DSPdata)$sample_type)
DEA_results <- c() for(segmt in DSP_segs){ ind <- pData(target_DSPdata)$segment == segmt mixedOutmc <- mixedModelDE(target_DSPdata[, ind], elt = "log2_Q3_norm", modelFormula = ~ testClass + 1, groupVar = "testClass", nCores = 1, #parallel::detectCores(), multiCore = FALSE)
r_test <- do.call(rbind, mixedOutmc["lsmeans", ]) tests <- rownames(r_test) r_test <- as.data.frame(r_test) r_test$Contrast <- tests
r_test$Gene <- unlist(lapply(colnames(mixedOutmc), rep, nrow(mixedOutmc["lsmeans", ][[1]]))) r_test$Subset <- segmt r_test$FDR <- p.adjust(r_test$Pr(>|t|), method = "fdr") r_test <- r_test[, c("Gene", "Subset", "Contrast", "Estimate", "Pr(>|t|)", "FDR")] DEA_results <- rbind(DEA_results, r_test) } `
Pr(>|t|)
This returns the following error:
Error in eval(predvars, data, env) : object 'testClass' not found
Hi @joshscurll,
Thank you for reaching out. Our customer support team will be able to help you with this. Please email support@nanostring.com with your issue.
Thanks, Maddy
I am attempting to use the mixedModelDE function for differential expression analysis (post- vs pre-treatment tissue) as per Section 7.3 in the GeoMx Workflows vignette (https://bioconductor.org/packages/release/workflows/vignettes/GeoMxWorkflows/inst/doc/GeomxTools_RNA-NGS_Analysis.html#73_Between_Slide_Analysis:_Diabetic_Kidney_Disease_vs_Healthy). In my case, I am analysing pre- and post-treatment tissue from a single patient, so I have no need to include any variable in the model intercept, but otherwise my code is the same as the vignette. However, mixedModelDE returns "object 'testClass' not found" as an error. This error seems to have been encountered by someone else here: https://bytemeta.vip/repo/Nanostring-Biostats/GeomxTools/issues/174. I have added a "testClass" factor column to my pData and included it in the model formula as in the vignette, so I don't know how to resolve this error.
Here is my code that produces the error: ` pData(target_DSPdata)$testClass <- factor(pData(target_DSPdata)$sample_type)
DEA_results <- c() for(segmt in DSP_segs){ ind <- pData(target_DSPdata)$segment == segmt mixedOutmc <- mixedModelDE(target_DSPdata[, ind], elt = "log2_Q3_norm", modelFormula = ~ testClass + 1, groupVar = "testClass", nCores = 1, #parallel::detectCores(), multiCore = FALSE)
r_test <- do.call(rbind, mixedOutmc["lsmeans", ]) tests <- rownames(r_test) r_test <- as.data.frame(r_test) r_test$Contrast <- tests
r_test$Gene <- unlist(lapply(colnames(mixedOutmc), rep, nrow(mixedOutmc["lsmeans", ][[1]]))) r_test$Subset <- segmt r_test$FDR <- p.adjust(r_test$
Pr(>|t|)
, method = "fdr") r_test <- r_test[, c("Gene", "Subset", "Contrast", "Estimate", "Pr(>|t|)", "FDR")] DEA_results <- rbind(DEA_results, r_test) } `This returns the following error:
Error in eval(predvars, data, env) : object 'testClass' not found