GreenleafLab
`addGeneIntegrationMatrix` Error in slot(object = object, name = "features")[[layer]] <- features: more elements supplied than there are to replace Traceback:
When run the tutorial in the document: https://www.archrproject.com/bookdown/cross-platform-linkage-of-scatac-seq-cells-with-scrna-seq-cells.html
projHeme2 <- addGeneIntegrationMatrix(
ArchRProj = projHeme2,
useMatrix = "GeneScoreMatrix",
matrixName = "GeneIntegrationMatrix",
reducedDims = "IterativeLSI",
seRNA = seRNA,
addToArrow = FALSE,
groupRNA = "BioClassification",
nameCell = "predictedCell_Un",
nameGroup = "predictedGroup_Un",
nameScore = "predictedScore_Un"
)
How should I solve this error:
ArchR logging to : ArchRLogs/ArchR-addGeneIntegrationMatrix-3af203550d8-Date-2024-09-30_Time-11-49-57.128984.log
If there is an issue, please report to github with logFile!
2024-09-30 11:49:57.233178 : Running Seurat's Integration Stuart* et al 2019, 0.002 mins elapsed.
2024-09-30 11:49:57.449474 : Checking ATAC Input, 0.005 mins elapsed.
2024-09-30 11:49:58.36637 : Checking RNA Input, 0.021 mins elapsed.
2024-09-30 11:50:14.923285 : Found 18601 overlapping gene names from gene scores and rna matrix!, 0.297 mins elapsed.
2024-09-30 11:50:14.929036 : Creating Integration Blocks, 0.297 mins elapsed.
2024-09-30 11:50:15.271016 : Prepping Interation Data, 0.302 mins elapsed.
2024-09-30 11:50:16.786384 : Computing Integration in 1 Integration Blocks!, 0 mins elapsed.
2024-09-30 11:50:16.799628 : Block (1 of 1) : Computing Integration, 0 mins elapsed.
2024-09-30 11:50:21.25633 : Block (1 of 1) : Identifying Variable Genes, 0.075 mins elapsed.
2024-09-30 11:50:25.130431 : Block (1 of 1) : Getting GeneScoreMatrix, 0.139 mins elapsed.
2024-09-30 11:50:30.740624 : Block (1 of 1) : Imputing GeneScoreMatrix, 0.233 mins elapsed.
Getting ImputeWeights
Warning message:
“Data is of class dgeMatrix. Coercing to dgCMatrix.”
Error in slot(object = object, name = "features")[[layer]] <- features: more elements supplied than there are to replace
Traceback:
1. .safelapply(seq_along(blockList), function(i) {
. prefix <- sprintf("Block (%s of %s) :", i, length(blockList))
. .logDiffTime(sprintf("%s Computing Integration", prefix),
. tstart, verbose = verbose, logFile = logFile)
. blocki <- blockList[[i]]
. subProj@cellColData <- subProj@cellColData[blocki$ATAC, ]
. subProj@sampleColData <- subProj@sampleColData[unique(subProj$Sample),
. , drop = FALSE]
. subRNA <- seuratRNA[, blocki$RNA]
. subRNA <- subRNA[rownames(subRNA) %in% geneDF$name, ]
. .logDiffTime(sprintf("%s Identifying Variable Genes", prefix),
. tstart, verbose = verbose, logFile = logFile)
. subRNA <- FindVariableFeatures(object = subRNA, nfeatures = nGenes,
. verbose = FALSE)
. subRNA <- ScaleData(object = subRNA, verbose = FALSE)
. if (is.null(genesUse)) {
. genesUse <- VariableFeatures(object = subRNA)
. }
. .logDiffTime(sprintf("%s Getting GeneScoreMatrix", prefix),
. tstart, verbose = verbose, logFile = logFile)
. mat <- .getPartialMatrix(getArrowFiles(subProj), featureDF = geneDF[geneDF$name %in%
. genesUse, ], threads = 1, cellNames = subProj$cellNames,
. useMatrix = useMatrix, verbose = FALSE)
. rownames(mat) <- geneDF[geneDF$name %in% genesUse, "name"]
. .logThis(mat, paste0("GeneScoreMat-Block-", i), logFile = logFile)
. if (useImputation) {
. .logDiffTime(sprintf("%s Imputing GeneScoreMatrix", prefix),
. tstart, verbose = verbose, logFile = logFile)
. imputeParams <- list()
. imputeParams$ArchRProj <- subProj
. imputeParams$randomSuffix <- TRUE
. imputeParams$reducedDims <- reducedDims
. imputeParams$dimsToUse <- dimsToUse
. imputeParams$scaleDims <- scaleDims
. imputeParams$corCutOff <- corCutOff
. imputeParams$threads <- 1
. imputeParams$logFile <- logFile
. subProj <- suppressMessages(do.call(addImputeWeights,
. imputeParams))
. mat <- suppressMessages(imputeMatrix(mat = mat, imputeWeights = getImputeWeights(subProj),
. verbose = FALSE, logFile = logFile))
. o <- suppressWarnings(file.remove(unlist(getImputeWeights(subProj)[[1]])))
. .logThis(mat, paste0("GeneScoreMat-Block-Impute-", i),
. logFile = logFile)
. }
. mat <- log(mat + 1)
. seuratATAC <- Seurat::CreateSeuratObject(counts = mat[head(seq_len(nrow(mat)),
. 5), , drop = FALSE])
. seuratATAC[["GeneScore"]] <- Seurat::CreateAssayObject(counts = mat)
. rm(mat)
. DefaultAssay(seuratATAC) <- "GeneScore"
. seuratATAC <- Seurat::ScaleData(seuratATAC, verbose = FALSE)
. .logDiffTime(sprintf("%s Seurat FindTransferAnchors", prefix),
. tstart, verbose = verbose, logFile = logFile)
. transferAnchors <- .retryCatch({
. gc()
. Seurat::FindTransferAnchors(reference = subRNA, query = seuratATAC,
. reduction = reduction, features = genesUse, verbose = FALSE,
. ...)
. }, maxAttempts = 2, logFile = logFile)
. .logThis(paste0(utils::capture.output(transferAnchors), collapse = "\n"),
. paste0("transferAnchors-", i), logFile = logFile)
. rDSub <- rD[colnames(seuratATAC), , drop = FALSE]
. .logThis(rDSub, paste0("rDSub-", i), logFile = logFile)
. transferParams$anchorset <- transferAnchors
. transferParams$weight.reduction <- CreateDimReducObject(embeddings = rDSub,
. key = "LSI_", assay = DefaultAssay(seuratATAC))
. transferParams$verbose <- FALSE
. transferParams$dims <- seq_len(ncol(rDSub))
. .logDiffTime(sprintf("%s Seurat TransferData Cell Group Labels",
. prefix), tstart, verbose = verbose, logFile = logFile)
. transferParams$refdata <- subRNA$Group
. rnaLabels <- do.call(Seurat::TransferData, transferParams)
. .logDiffTime(sprintf("%s Seurat TransferData Cell Names Labels",
. prefix), tstart, verbose = verbose, logFile = logFile)
. transferParams$refdata <- colnames(subRNA)
. rnaLabels2 <- do.call(Seurat::TransferData, transferParams)[,
. 1]
. if (addToArrow) {
. .logDiffTime(sprintf("%s Seurat TransferData GeneMatrix",
. prefix), tstart, verbose = verbose, logFile = logFile)
. transferParams$refdata <- GetAssayData(subRNA, assay = "RNA",
. slot = "data")
. gc()
. matchedRNA <- do.call(Seurat::TransferData, transferParams)
. matchedRNA <- matchedRNA@data
. }
. matchDF <- DataFrame(cellNames = colnames(seuratATAC), predictionScore = rnaLabels$prediction.score.max,
. predictedGroup = rnaLabels$predicted.id, predictedCell = rnaLabels2)
. rownames(matchDF) <- matchDF$cellNames
. .logDiffTime(sprintf("%s Saving TransferAnchors Joint CCA",
. prefix), tstart, verbose = verbose, logFile = logFile)
. jointCCA <- DataFrame([email protected][[1]]@[email protected])
. jointCCA$Assay <- ifelse(endsWith(rownames(jointCCA), "_reference"),
. "RNA", "ATAC")
. jointCCA$Group <- NA
. jointCCA$Score <- NA
. jointCCA[paste0(colnames(subRNA), "_reference"), "Group"] <- subRNA$Group
. jointCCA[paste0(matchDF$cellNames, "_query"), "Group"] <- matchDF$predictedGroup
. jointCCA[paste0(matchDF$cellNames, "_query"), "Score"] <- matchDF$predictionScore
. .safeSaveRDS(object = jointCCA, file = file.path(outDir3,
. paste0("Save-Block", i, "-JointCCA.rds")))
. rm(transferParams, transferAnchors)
. gc()
. if (addToArrow) {
. .logDiffTime(sprintf("%s Transferring Paired RNA to Temp File",
. prefix), tstart, verbose = verbose, logFile = logFile)
. tmpFilei <- paste0(tmpFile, "-IntegrationBlock-", i,
. ".h5")
. o <- h5createFile(tmpFilei)
. sampleNames <- getCellColData(subProj, "Sample")[matchDF$cellNames,
. ]
. uniqueSamples <- unique(sampleNames)
. matchedRNA <- .safeSubset(mat = matchedRNA, subsetRows = paste0(featureDF$name),
. subsetCols = matchDF$cellNames)
. for (z in seq_along(uniqueSamples)) {
. mat <- matchedRNA[, which(sampleNames == uniqueSamples[z]),
. drop = FALSE]
. Group <- uniqueSamples[z]
. o <- tryCatch({
. h5delete(tmpFilei, paste0(Group))
. }, error = function(x) {
. })
. o <- h5createGroup(tmpFilei, paste0(Group))
. j <- Rle(findInterval(seq(mat@x) - 1, mat@p[-1]) +
. 1)
. lengthRle <- length(j@lengths)
. lengthI <- length(mat@i)
. o <- .suppressAll(h5createDataset(tmpFilei, paste0(Group,
. "/i"), storage.mode = "integer", dims = c(lengthI,
. 1), level = 0))
. o <- .suppressAll(h5createDataset(tmpFilei, paste0(Group,
. "/jLengths"), storage.mode = "integer", dims = c(lengthRle,
. 1), level = 0))
. o <- .suppressAll(h5createDataset(tmpFilei, paste0(Group,
. "/jValues"), storage.mode = "integer", dims = c(lengthRle,
. 1), level = 0))
. o <- .suppressAll(h5createDataset(tmpFilei, paste0(Group,
. "/x"), storage.mode = "double", dims = c(lengthI,
. 1), level = 0))
. o <- .suppressAll(h5write(obj = mat@i + 1, file = tmpFilei,
. name = paste0(Group, "/i")))
. o <- .suppressAll(h5write(obj = j@lengths, file = tmpFilei,
. name = paste0(Group, "/jLengths")))
. o <- .suppressAll(h5write(obj = j@values, file = tmpFilei,
. name = paste0(Group, "/jValues")))
. o <- .suppressAll(h5write(obj = mat@x, file = tmpFilei,
. name = paste0(Group, "/x")))
. o <- .suppressAll(h5write(obj = colnames(mat), file = tmpFilei,
. name = paste0(Group, "/cellNames")))
. }
. rm(matchedRNA, mat, j)
. }
. .logDiffTime(sprintf("%s Completed Integration", prefix),
. tstart, verbose = verbose, logFile = logFile)
. gc()
. matchDF$Block <- Rle(i)
. matchDF
. }, threads = threads2) %>% Reduce("rbind", .)
2. Reduce("rbind", .)
3. .safelapply(seq_along(blockList), function(i) {
. prefix <- sprintf("Block (%s of %s) :", i, length(blockList))
. .logDiffTime(sprintf("%s Computing Integration", prefix),
. tstart, verbose = verbose, logFile = logFile)
. blocki <- blockList[[i]]
. subProj@cellColData <- subProj@cellColData[blocki$ATAC, ]
. subProj@sampleColData <- subProj@sampleColData[unique(subProj$Sample),
. , drop = FALSE]
. subRNA <- seuratRNA[, blocki$RNA]
. subRNA <- subRNA[rownames(subRNA) %in% geneDF$name, ]
. .logDiffTime(sprintf("%s Identifying Variable Genes", prefix),
. tstart, verbose = verbose, logFile = logFile)
. subRNA <- FindVariableFeatures(object = subRNA, nfeatures = nGenes,
. verbose = FALSE)
. subRNA <- ScaleData(object = subRNA, verbose = FALSE)
. if (is.null(genesUse)) {
. genesUse <- VariableFeatures(object = subRNA)
. }
. .logDiffTime(sprintf("%s Getting GeneScoreMatrix", prefix),
. tstart, verbose = verbose, logFile = logFile)
. mat <- .getPartialMatrix(getArrowFiles(subProj), featureDF = geneDF[geneDF$name %in%
. genesUse, ], threads = 1, cellNames = subProj$cellNames,
. useMatrix = useMatrix, verbose = FALSE)
. rownames(mat) <- geneDF[geneDF$name %in% genesUse, "name"]
. .logThis(mat, paste0("GeneScoreMat-Block-", i), logFile = logFile)
. if (useImputation) {
. .logDiffTime(sprintf("%s Imputing GeneScoreMatrix", prefix),
. tstart, verbose = verbose, logFile = logFile)
. imputeParams <- list()
. imputeParams$ArchRProj <- subProj
. imputeParams$randomSuffix <- TRUE
. imputeParams$reducedDims <- reducedDims
. imputeParams$dimsToUse <- dimsToUse
. imputeParams$scaleDims <- scaleDims
. imputeParams$corCutOff <- corCutOff
. imputeParams$threads <- 1
. imputeParams$logFile <- logFile
. subProj <- suppressMessages(do.call(addImputeWeights,
. imputeParams))
. mat <- suppressMessages(imputeMatrix(mat = mat, imputeWeights = getImputeWeights(subProj),
. verbose = FALSE, logFile = logFile))
. o <- suppressWarnings(file.remove(unlist(getImputeWeights(subProj)[[1]])))
. .logThis(mat, paste0("GeneScoreMat-Block-Impute-", i),
. logFile = logFile)
. }
. mat <- log(mat + 1)
. seuratATAC <- Seurat::CreateSeuratObject(counts = mat[head(seq_len(nrow(mat)),
. 5), , drop = FALSE])
. seuratATAC[["GeneScore"]] <- Seurat::CreateAssayObject(counts = mat)
. rm(mat)
. DefaultAssay(seuratATAC) <- "GeneScore"
. seuratATAC <- Seurat::ScaleData(seuratATAC, verbose = FALSE)
. .logDiffTime(sprintf("%s Seurat FindTransferAnchors", prefix),
. tstart, verbose = verbose, logFile = logFile)
. transferAnchors <- .retryCatch({
. gc()
. Seurat::FindTransferAnchors(reference = subRNA, query = seuratATAC,
. reduction = reduction, features = genesUse, verbose = FALSE,
. ...)
. }, maxAttempts = 2, logFile = logFile)
. .logThis(paste0(utils::capture.output(transferAnchors), collapse = "\n"),
. paste0("transferAnchors-", i), logFile = logFile)
. rDSub <- rD[colnames(seuratATAC), , drop = FALSE]
. .logThis(rDSub, paste0("rDSub-", i), logFile = logFile)
. transferParams$anchorset <- transferAnchors
. transferParams$weight.reduction <- CreateDimReducObject(embeddings = rDSub,
. key = "LSI_", assay = DefaultAssay(seuratATAC))
. transferParams$verbose <- FALSE
. transferParams$dims <- seq_len(ncol(rDSub))
. .logDiffTime(sprintf("%s Seurat TransferData Cell Group Labels",
. prefix), tstart, verbose = verbose, logFile = logFile)
. transferParams$refdata <- subRNA$Group
. rnaLabels <- do.call(Seurat::TransferData, transferParams)
. .logDiffTime(sprintf("%s Seurat TransferData Cell Names Labels",
. prefix), tstart, verbose = verbose, logFile = logFile)
. transferParams$refdata <- colnames(subRNA)
. rnaLabels2 <- do.call(Seurat::TransferData, transferParams)[,
. 1]
. if (addToArrow) {
. .logDiffTime(sprintf("%s Seurat TransferData GeneMatrix",
. prefix), tstart, verbose = verbose, logFile = logFile)
. transferParams$refdata <- GetAssayData(subRNA, assay = "RNA",
. slot = "data")
. gc()
. matchedRNA <- do.call(Seurat::TransferData, transferParams)
. matchedRNA <- matchedRNA@data
. }
. matchDF <- DataFrame(cellNames = colnames(seuratATAC), predictionScore = rnaLabels$prediction.score.max,
. predictedGroup = rnaLabels$predicted.id, predictedCell = rnaLabels2)
. rownames(matchDF) <- matchDF$cellNames
. .logDiffTime(sprintf("%s Saving TransferAnchors Joint CCA",
. prefix), tstart, verbose = verbose, logFile = logFile)
. jointCCA <- DataFrame([email protected][[1]]@[email protected])
. jointCCA$Assay <- ifelse(endsWith(rownames(jointCCA), "_reference"),
. "RNA", "ATAC")
. jointCCA$Group <- NA
. jointCCA$Score <- NA
. jointCCA[paste0(colnames(subRNA), "_reference"), "Group"] <- subRNA$Group
. jointCCA[paste0(matchDF$cellNames, "_query"), "Group"] <- matchDF$predictedGroup
. jointCCA[paste0(matchDF$cellNames, "_query"), "Score"] <- matchDF$predictionScore
. .safeSaveRDS(object = jointCCA, file = file.path(outDir3,
. paste0("Save-Block", i, "-JointCCA.rds")))
. rm(transferParams, transferAnchors)
. gc()
. if (addToArrow) {
. .logDiffTime(sprintf("%s Transferring Paired RNA to Temp File",
. prefix), tstart, verbose = verbose, logFile = logFile)
. tmpFilei <- paste0(tmpFile, "-IntegrationBlock-", i,
. ".h5")
. o <- h5createFile(tmpFilei)
. sampleNames <- getCellColData(subProj, "Sample")[matchDF$cellNames,
. ]
. uniqueSamples <- unique(sampleNames)
. matchedRNA <- .safeSubset(mat = matchedRNA, subsetRows = paste0(featureDF$name),
. subsetCols = matchDF$cellNames)
. for (z in seq_along(uniqueSamples)) {
. mat <- matchedRNA[, which(sampleNames == uniqueSamples[z]),
. drop = FALSE]
. Group <- uniqueSamples[z]
. o <- tryCatch({
. h5delete(tmpFilei, paste0(Group))
. }, error = function(x) {
. })
. o <- h5createGroup(tmpFilei, paste0(Group))
. j <- Rle(findInterval(seq(mat@x) - 1, mat@p[-1]) +
. 1)
. lengthRle <- length(j@lengths)
. lengthI <- length(mat@i)
. o <- .suppressAll(h5createDataset(tmpFilei, paste0(Group,
. "/i"), storage.mode = "integer", dims = c(lengthI,
. 1), level = 0))
. o <- .suppressAll(h5createDataset(tmpFilei, paste0(Group,
. "/jLengths"), storage.mode = "integer", dims = c(lengthRle,
. 1), level = 0))
. o <- .suppressAll(h5createDataset(tmpFilei, paste0(Group,
. "/jValues"), storage.mode = "integer", dims = c(lengthRle,
. 1), level = 0))
. o <- .suppressAll(h5createDataset(tmpFilei, paste0(Group,
. "/x"), storage.mode = "double", dims = c(lengthI,
. 1), level = 0))
. o <- .suppressAll(h5write(obj = mat@i + 1, file = tmpFilei,
. name = paste0(Group, "/i")))
. o <- .suppressAll(h5write(obj = j@lengths, file = tmpFilei,
. name = paste0(Group, "/jLengths")))
. o <- .suppressAll(h5write(obj = j@values, file = tmpFilei,
. name = paste0(Group, "/jValues")))
. o <- .suppressAll(h5write(obj = mat@x, file = tmpFilei,
. name = paste0(Group, "/x")))
. o <- .suppressAll(h5write(obj = colnames(mat), file = tmpFilei,
. name = paste0(Group, "/cellNames")))
. }
. rm(matchedRNA, mat, j)
. }
. .logDiffTime(sprintf("%s Completed Integration", prefix),
. tstart, verbose = verbose, logFile = logFile)
. gc()
. matchDF$Block <- Rle(i)
. matchDF
. }, threads = threads2)
4. mclapply(..., mc.cores = threads, mc.preschedule = preschedule)
5. lapply(X = X, FUN = FUN, ...)
6. FUN(X[[i]], ...)
7. Seurat::CreateSeuratObject(counts = mat[head(seq_len(nrow(mat)),
. 5), , drop = FALSE])
8. CreateSeuratObject.default(counts = mat[head(seq_len(nrow(mat)),
. 5), , drop = FALSE])
9. CreateAssay5Object(counts = counts, min.cells = min.cells, min.features = min.features,
. ...)
10. .CreateStdAssay(counts = counts, min.cells = min.cells, min.features = min.features,
. transpose = transpose, type = type, csum = csum, fsum = fsum,
. ...)
11. .CreateStdAssay.list(counts = counts, min.cells = min.cells,
. min.features = min.features, transpose = transpose, type = type,
. csum = csum, fsum = fsum, ...)
12. `LayerData<-`(object = `*tmp*`, layer = layer, features = features[[layer]],
. cells = cells[[layer]], transpose = transpose, value = counts[[layer]])
13. `LayerData<-.Assay5`(object = `*tmp*`, layer = layer, features = features[[layer]],
. cells = cells[[layer]], transpose = transpose, value = counts[[layer]])
14. .handleSimpleError(function (cnd)
. {
. watcher$capture_plot_and_output()
. cnd <- sanitize_call(cnd)
. watcher$push(cnd)
. switch(on_error, continue = invokeRestart("eval_continue"),
. stop = invokeRestart("eval_stop"), error = invokeRestart("eval_error",
. cnd))
. }, "more elements supplied than there are to replace", base::quote(slot(object = object,
. name = "features")[[layer]] <- features))
Thanks a lot
Hi @danli349! Thanks for using ArchR! Lately, it has been very challenging for me to keep up with maintenance of this package and all of my other responsibilities as a PI. I have not been responding to issue posts and I have not been pushing updates to the software. We are actively searching to hire a computational biologist to continue to develop and maintain ArchR and related tools. If you know someone who might be a good fit, please let us know! In the meantime, your issue will likely go without a reply. Most issues with ArchR right not relate to compatibility. Try reverting to R 4.1 and Bioconductor 3.15. Newer versions of Seurat and Matrix also are causing issues. Sorry for not being able to provide active support for this package at this time.
@rcorces Thanks a lot for helping, can you please let me know which Seurat and Matrix versions should I use?
@rcorces I solved this problem by changing the version of Seurat package:
remove.packages("SeuratObject")
packageurl <- "http://cran.r-project.org/src/contrib/Archive/SeuratObject/SeuratObject_4.1.3.tar.gz"
install.packages(packageurl, repos=NULL, type="source")
remove.packages("Seurat")
packageurl <- "http://cran.r-project.org/src/contrib/Archive/Seurat/Seurat_4.3.0.tar.gz"
install.packages(packageurl, repos=NULL, type="source")
Thanks a lot
@rcorces I solved this problem by changing the version of
Seuratpackage:remove.packages("SeuratObject") packageurl <- "http://cran.r-project.org/src/contrib/Archive/SeuratObject/SeuratObject_4.1.3.tar.gz" install.packages(packageurl, repos=NULL, type="source") remove.packages("Seurat") packageurl <- "http://cran.r-project.org/src/contrib/Archive/Seurat/Seurat_4.3.0.tar.gz" install.packages(packageurl, repos=NULL, type="source")Thanks a lot
Solved for me too, thanks!
ArchR Gene Integration Process
Code Execution
ArchRsub.lungnew <- addGeneIntegrationMatrix(
ArchRProj = ArchRsub.lungnew,
useMatrix = "GeneScoreMatrix",
matrixName = "GeneIntegrationMatrix",
reducedDims = "IterativeLSI",
seRNA = seRNA,
addToArrow = FALSE,
groupRNA = "celltype_bped_main",
nameCell = "predictedCell_Un",
nameGroup = "predictedGroup_Un",
nameScore = "predictedScore_Un"
)
ArchR logging to : ArchRLogs/ArchR-addGeneIntegrationMatrix-4bf73914b78f-Date-2024-10-19_Time-12-09-13.353955.log
If there is an issue, please report to github with logFile!
2024-10-19 12:09:13.473208 : Running Seurat's Integration Stuart* et al 2019, 0.002 mins elapsed.
2024-10-19 12:09:13.745389 : Checking ATAC Input, 0.007 mins elapsed.
2024-10-19 12:09:14.673089 : Checking RNA Input, 0.022 mins elapsed.
2024-10-19 12:09:19.392725 : Found 18706 overlapping gene names from gene scores and rna matrix!, 0.101 mins elapsed.
2024-10-19 12:09:19.396339 : Creating Integration Blocks, 0.101 mins elapsed.
2024-10-19 12:09:19.421006 : Prepping Interation Data, 0.101 mins elapsed.
2024-10-19 12:09:20.119927 : Computing Integration in 1 Integration Blocks!, 0 mins elapsed.
2024-10-19 12:09:20.132852 : Block (1 of 1) : Computing Integration, 0 mins elapsed.
2024-10-19 12:09:20.979738 : Block (1 of 1) : Identifying Variable Genes, 0.014 mins elapsed.
2024-10-19 12:09:23.12459 : Block (1 of 1) : Getting GeneScoreMatrix, 0.05 mins elapsed.
2024-10-19 12:09:34.256679 : Block (1 of 1) : Imputing GeneScoreMatrix, 0.236 mins elapsed.
Getting ImputeWeights
2024-10-19 12:10:09.657839 : Block (1 of 1) : Seurat FindTransferAnchors, 0.826 mins elapsed.
<simpleError in dimnames(x) <- dn: length of 'dimnames' [1] not equal to array extent>
Error in .retryCatch({ :
Moments ago I have faced the same problems in the issue. I have use the same solution to change the Seurat package and run through with Seurat V4 with my RNA data. But when I run the addGeneIntegrationMatrix part, new error came. How to solve this?
@rcorces I solved this problem by changing the version of
Seuratpackage:remove.packages("SeuratObject") packageurl <- "http://cran.r-project.org/src/contrib/Archive/SeuratObject/SeuratObject_4.1.3.tar.gz" install.packages(packageurl, repos=NULL, type="source") remove.packages("Seurat") packageurl <- "http://cran.r-project.org/src/contrib/Archive/Seurat/Seurat_4.3.0.tar.gz" install.packages(packageurl, repos=NULL, type="source")Thanks a lot
Solved for me too, thanks!
same. Thank you kindly for sharing @danli349
@immanuelazn could you please guide me how i can fix this error projHeme5 <- addArchRAnnotations(ArchRProj = projHeme5, collection = "EncodeTFBS") ArchR logging to : ArchRLogs/ArchR-addArchRAnnotations-19a5c72d2a4560-Date-2024-12-05_Time-14-31-56.261448.log If there is an issue, please report to github with logFile! Error in H5Fopen(file, flags = flags, fapl = fapl, native = native) : HDF5. File accessibility. Unable to open file.
Hi @IqRaZaFaR16 , sorry about this issue. This is related to HDF5 file locking, and has been an ongoing issue for a while. Refer to #248 for some more information, but I would recommend passing subThreading = FALSE during createArrowFiles() calls. Additionally, I would recommend trying out the dev branch through remotes::install_github("GreenleafLab/ArchR", ref = "dev") as we implemented a fix for this there
@rcorces I solved this problem by changing the version of
Seuratpackage:remove.packages("SeuratObject") packageurl <- "http://cran.r-project.org/src/contrib/Archive/SeuratObject/SeuratObject_4.1.3.tar.gz" install.packages(packageurl, repos=NULL, type="source") remove.packages("Seurat") packageurl <- "http://cran.r-project.org/src/contrib/Archive/Seurat/Seurat_4.3.0.tar.gz" install.packages(packageurl, repos=NULL, type="source")Thanks a lot
I use this and it works, but change to another error😭
subproj4 <- addGeneIntegrationMatrix(
- ArchRProj = subproj3,
- useMatrix = "GeneScoreMatrix",
- matrixName = "GeneIntegrationMatrix_ArchR", #整合后的名称
- reducedDims = "IterativeLSI",
- seRNA = merged_rna_filtered2, #对应的RNA对象
- groupList = groupList,
- addToArrow = T,
- force= TRUE,
- groupRNA = "Major_celltype",#这里其实可以调整为celltype或者cluster。调整之后会对GeneIntefrationMatrix有影响，因为是根据group来将细胞进行匹配然后看其基因的表达
- nameCell = "predictedCell_ArchR",
- nameGroup = "predictedCluster_ArchR",#这里对应就是cell/cluster，取个名区分下
- nameScore = "predictedScore_ArchR",
- plotUMAP = F,
- useImputation = F,
- transferParams = list(dims = 1:30),
- assayRNA = "RNA"
- )
ArchR logging to : ArchRLogs/ArchR-addGeneIntegrationMatrix-e1fd2403fdda0-Date-2025-02-17_Time-16-03-57.990328.log If there is an issue, please report to github with logFile! 2025-02-17 16:03:58.057631 : Running Seurat's Integration Stuart* et al 2019, 0.001 mins elapsed. 2025-02-17 16:03:58.087769 : Checking ATAC Input, 0.002 mins elapsed. 2025-02-17 16:04:09.807863 : Checking RNA Input, 0.197 mins elapsed. Error in GetAssay.Seurat(object = object, assay = assay) : RNA is not an assay present in the given object. Available assays are:
package.version("Seurat") [1] "4.3.0" package.version("SeuratObject") [1] "4.1.3"
ArchR Gene Integration Process
Code Execution
ArchRsub.lungnew <- addGeneIntegrationMatrix( ArchRProj = ArchRsub.lungnew, useMatrix = "GeneScoreMatrix", matrixName = "GeneIntegrationMatrix", reducedDims = "IterativeLSI", seRNA = seRNA, addToArrow = FALSE, groupRNA = "celltype_bped_main", nameCell = "predictedCell_Un", nameGroup = "predictedGroup_Un", nameScore = "predictedScore_Un" )
ArchR logging to : ArchRLogs/ArchR-addGeneIntegrationMatrix-4bf73914b78f-Date-2024-10-19_Time-12-09-13.353955.log If there is an issue, please report to github with logFile! 2024-10-19 12:09:13.473208 : Running Seurat's Integration Stuart* et al 2019, 0.002 mins elapsed. 2024-10-19 12:09:13.745389 : Checking ATAC Input, 0.007 mins elapsed. 2024-10-19 12:09:14.673089 : Checking RNA Input, 0.022 mins elapsed. 2024-10-19 12:09:19.392725 : Found 18706 overlapping gene names from gene scores and rna matrix!, 0.101 mins elapsed. 2024-10-19 12:09:19.396339 : Creating Integration Blocks, 0.101 mins elapsed. 2024-10-19 12:09:19.421006 : Prepping Interation Data, 0.101 mins elapsed. 2024-10-19 12:09:20.119927 : Computing Integration in 1 Integration Blocks!, 0 mins elapsed. 2024-10-19 12:09:20.132852 : Block (1 of 1) : Computing Integration, 0 mins elapsed. 2024-10-19 12:09:20.979738 : Block (1 of 1) : Identifying Variable Genes, 0.014 mins elapsed. 2024-10-19 12:09:23.12459 : Block (1 of 1) : Getting GeneScoreMatrix, 0.05 mins elapsed. 2024-10-19 12:09:34.256679 : Block (1 of 1) : Imputing GeneScoreMatrix, 0.236 mins elapsed. Getting ImputeWeights 2024-10-19 12:10:09.657839 : Block (1 of 1) : Seurat FindTransferAnchors, 0.826 mins elapsed. <simpleError in dimnames(x) <- dn: length of 'dimnames' [1] not equal to array extent> Error in .retryCatch({ : Moments ago I have faced the same problems in the issue. I have use the same solution to change the Seurat package and run through with Seurat V4 with my RNA data. But when I run the addGeneIntegrationMatrix part, new error came. How to solve this?
How did you solve this problem, bro? I also have this error.
