Open EperLuo opened 1 year ago
Hi, I'm having the same issue. Did you figure out what was causing the problem?
I ran into the same issue. Looking at the code, I guess we're supposed to call it with type = 'raw'
? I'm not actually sure, but this seems to be working,
library(SimBench)
library(parallel) # have to explicitly load?
path <- system.file("extdata", "real.rds", package="SimBench")
real <- readRDS(path)
path <- system.file("extdata", "sim.rds", package="SimBench")
sim <- readRDS(path)
parameter_result <- eval_parameter(real = real, sim = sim, type = "raw" , method = "samplemethod")
I also had to install a few other dependencies that don't appear in the NAMESPACE. The main ones were WGCNA
and preprocessCore
(which is required by WGCNA
). For the record, here are all the ::
imports, some which don't seem explicitly declared.
(base) MacBook-Pro-de-Kris:R ksankaran$ grep -R '::' .
./countsim_eval_KS.R: ) %>% dplyr::mutate(EffLibsize = Libsize * TMM)
./countsim_eval_KS.R: sampleDF <- do.call(rbind, sampleDF) %>% dplyr::mutate(dataset = rep(names(sampleDF), ns))
./countsim_eval_KS.R: featureDF <- do.call(rbind, featureDF) %>% dplyr::mutate(dataset = rep(names(featureDF), ns))
./countsim_eval_KS.R: })) %>% dplyr::mutate(dataset = names(obj))
./parameter_estimation.R: temp <- thisparameter %>% dplyr::summarise( sum_kde = sum(abs( temp)) )
./calculateGeneCellCorr.R: corrs <- WGCNA::cor(cpms, use = "pairwise.complete.obs",
./calculateGeneCellCorr.R: do.call(rbind, sampleCorrDF) %>% dplyr::mutate(dataset = rep(names(sampleCorrDF), ns))
./calculateGeneCellCorr.R: cpms <- cpms[genefilter::rowVars(cpms) > 0,]
./calculateGeneCellCorr.R: corrs <- WGCNA::cor(t(cpms), use = "pairwise.complete.obs",
./calculateGeneCellCorr.R: do.call(rbind, featureCorrDF) %>% dplyr::mutate(dataset = rep(names(featureCorrDF), ns))
./calculateMeanVarLibrary.R: dge <- edgeR::DGEList(counts = DESeq2::counts(ds))
./calculateMeanVarLibrary.R: dge <- edgeR::calcNormFactors(dge)
./calculateMeanVarLibrary.R: dds <- DESeq2::estimateSizeFactors(ds, type = "poscounts")
./generate_DE_prop.R: design <- stats::model.matrix(~tmp_celltype)
./generate_DE_prop.R: Matrix::rowMeans(exprsMat@assays$RNA@data[, tmp_celltype == i, drop = FALSE])
./generate_DE_prop.R: Matrix::rowSums(exprsMat@assays$RNA@data[, tmp_celltype == i,
./generate_DE_prop.R: y <- methods::new("EList")
./generate_DE_prop.R: fit <- limma::lmFit(y, design = design)
./generate_DE_prop.R: fit <- limma::eBayes(fit, trend = TRUE, robust = TRUE)
./generate_DE_prop.R: tt <- limma::topTable(fit, n = Inf, adjust.method = "BH", coef = 2)
./generate_DE_prop.R: Matrix::rowSums(exprsMat@assays$RNA@data[,
./generate_DE_prop.R: stats::bartlett.test(gene~cellTypes, df)$p.value
./generate_DE_prop.R: tt <- stats::p.adjust(tt , method = "BH")
./generate_DE_prop.R: Matrix::rowSums(exprsMat@assays$RNA@data [,
./generate_DE_prop.R: stats::ks.test(x1, x2, alternative = "greater")$p.value
./generate_DE_prop.R: tt <- stats::p.adjust(tt , method = "BH")
./generate_DE_prop.R: suppressWarnings(stats::chisq.test(tab)$p.value)
./generate_DE_prop.R: tt <- stats::p.adjust(tt , method = "BH")
./generate_DE_prop.R: Matrix::rowMeans(exprsMat@assays$RNA@data[, tmp_celltype == i, drop = FALSE])
./generate_DE_prop.R: apply(exprsMat@assays$RNA@data[, tmp_celltype == i, drop = FALSE], 1, stats::var)
Hello,
I also had the same issue. I installed WCGNA
and preprocessCore
, but nothing changed. Did anyone figure out how to fix this issue?
Warning message in mclapply(sim_list, function(x) {:
“all scheduled cores encountered errors in user code”
Error in vapply(sampleCorrDF, nrow, 0): values must be length 1,
but FUN(X[[1]]) result is length 0
Traceback:
1. eval_parameter(real = real, sim = sim, type = "raw", method = "samplemethod")
2. countsim_eval(sim_list)
3. calculateSampleCorrs(sim_list = obj, maxNForCorr = maxNForCorr,
. ncore = ncore)
4. vapply(sampleCorrDF, nrow, 0)
I debug the SimBench and find it use Seurat v5. Updata your seurat may solve your problem.
Hi! I was trying to reproduce the evaluation results in the readme file, and I followed exactly the guidance said:
but then I run into this bug:
I have installed all the required dependencies, but I am not very familiar with R and not sure if the versions of these dependencies are all right.
Any help would be much appreciated!~