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Hi, I think I have the same problem as issue #1394 - thanks for any help you can provide! Here is my code:
library(Seurat)
library(Signac)
library(EnsDb.Hsapiens.v86)
library(BSgenome.Hsapiens.UCSC.hg38)
folder = '/wynton/home/pollen/jwallace/S234_analysis/Signac/V4/'; dir.create(folder); setwd(folder)
fragment_dir = '/wynton/scratch/jwallace/Fragment_files/Fragment_files_all_prefix/'
macs2_temp = '/wynton/scratch/jwallace/Fragment_files/Macs2_temp/'; dir.create(macs2_temp)
macs2_path = "/wynton/home/pollen/jwallace/envs/env_signac/bin/macs2"
rna <- readRDS('rna.rds')
annotation <- readRDS("annotation.rds")
newlevels <- paste('chr', seqlevels(annotation), sep=""); newlevels[25] <- "chrM"; seqlevels(annotation) <- newlevels
genome(annotation) <- "hg38"
human_rna <- subset(rna, species == 'human')
#Make fragment objects for all conditions
file_prefixes = c("S_","K1_","K6_","1_K1_t1_","2_K1_t1_","1_K1_t2_","1_K6_t1_",
"2_K6_t1_","1_K6_t2_","2_S_t1_","1_S_t2_","1_P1_t2_","1_P6_t2_") #make sure these are in same order as barcode prefixes
barcode_prefixes = c("S","K1","K6","k1_t1_1","k1_t1_2","k1_t2","k6_t1_1","k6_t1_2",
"k6_t2","s_t1_2","s_t2","p1","p6")
frags_list = list()
for (i in seq_along(file_prefixes)){
cells = colnames(subset(human_rna, subset = orig.ident== barcode_prefixes[i]))
frags_list[i] <- CreateFragmentObject(path = file.path(fragment_dir,paste(file_prefixes[i], "Human_fragments.tsv.gz",sep="")), cells = cells)
}
fragpath = dir(fragment_dir,"*gz$",full.names=TRUE)
#call peaks using macs2 on all cells
peaks_all <- CallPeaks(fragpath, macs2.path = macs2_path,fragment.tempdir = macs2_temp, verbose = TRUE)#if getting weird errors, restart session
peaks_all <- keepStandardChromosomes(peaks_all, pruning.mode = "coarse")
peaks_all <- subsetByOverlaps(x = peaks_all, ranges = blacklist_hg38_unified, invert = TRUE)
macs2_counts <- FeatureMatrix(fragments = frags_list,features = peaks_all,cells = NULL)
During the FeatureMatrix step, I get the output and error:
Extracting reads overlapping genomic regions
Extracting reads overlapping genomic regions
Extracting reads overlapping genomic regions
Extracting reads overlapping genomic regionsection refused
Extracting reads overlapping genomic regions
Extracting reads overlapping genomic regions
Extracting reads overlapping genomic regions
Extracting reads overlapping genomic regions
Extracting reads overlapping genomic regions
Extracting reads overlapping genomic regions
Extracting reads overlapping genomic regions
Extracting reads overlapping genomic regions
Extracting reads overlapping genomic regions
Error: non-conformable matrix dimensions in dimCheck(e1, e2)
I also tried
cells = colnames(human_rna)
in the call to FeatureMatrix, but that gave the same error. I do not get the error if I call FeatureMatrix on each fragment object individually instead of the whole list.
My session info is:
R version 4.2.0 (2022-04-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: CentOS Linux 7 (Core)
Matrix products: default
BLAS: /wynton/home/cbi/shared/software/CBI/R-4.2.0-gcc10/lib64/R/lib/libRblas.so
LAPACK: /wynton/home/cbi/shared/software/CBI/R-4.2.0-gcc10/lib64/R/lib/libRlapack.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US$
[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_IDENTIFICATIO$
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] Signac_1.9.0 SeuratObject_4.1.3 Seurat_4.3.0
loaded via a namespace (and not attached):
[1] Rtsne_0.16 colorspace_2.1-0 deldir_1.0-6 ellipsis_0.3.2 ggri$
[6] XVector_0.38.0 GenomicRanges_1.50.2 rstudioapi_0.14 spatstat.data_3.0-1 leid$
[11] listenv_0.9.0 ggrepel_0.9.3 fansi_1.0.4 codetools_0.2-19 spli$
[16] RcppRoll_0.3.0 polyclip_1.10-4 jsonlite_1.8.4 Rsamtools_2.14.0 ica_$
[21] cluster_2.1.4 png_0.1-8 uwot_0.1.14 shiny_1.7.4 sctr$
[26] spatstat.sparse_3.0-1 compiler_4.2.0 httr_1.4.6 Matrix_1.5-4 fast$
[31] lazyeval_0.2.2 cli_3.6.1 later_1.3.1 htmltools_0.5.5 tool$
[36] igraph_1.4.2 gtable_0.3.3 glue_1.6.2 GenomeInfoDbData_1.2.9 RANN$
[41] reshape2_1.4.4 dplyr_1.1.2 fastmatch_1.1-3 Rcpp_1.0.10 scat$
[46] Biostrings_2.66.0 vctrs_0.6.2 spatstat.explore_3.2-1 nlme_3.1-162 prog$
[51] lmtest_0.9-40 spatstat.random_3.1-5 stringr_1.5.0 globals_0.16.2 mime$
[56] miniUI_0.1.1.1 lifecycle_1.0.3 irlba_2.3.5.1 goftest_1.2-3 futu$
[61] zlibbioc_1.44.0 MASS_7.3-60 zoo_1.8-12 scales_1.2.1 prom$
[66] spatstat.utils_3.0-3 parallel_4.2.0 RColorBrewer_1.1-3 reticulate_1.28 pbap$
[71] gridExtra_2.3 ggplot2_3.4.2 stringi_1.7.12 S4Vectors_0.36.2 Bioc$
[76] BiocParallel_1.32.6 GenomeInfoDb_1.34.9 rlang_1.1.1 pkgconfig_2.0.3 matr$
[81] bitops_1.0-7 lattice_0.21-8 ROCR_1.0-11 purrr_1.0.1 tens$
[86] patchwork_1.1.2 htmlwidgets_1.6.2 cowplot_1.1.1 tidyselect_1.2.0 para$
[91] RcppAnnoy_0.0.20 plyr_1.8.8 magrittr_2.0.3 R6_2.5.1 IRan$
[96] generics_0.1.3 pillar_1.9.0 fitdistrplus_1.1-11 survival_3.5-5 abin$
[101] RCurl_1.98-1.12 sp_1.6-0 tibble_3.2.1 future.apply_1.10.0 cray$
[106] KernSmooth_2.23-21 utf8_1.2.3 spatstat.geom_3.2-1 plotly_4.10.1 grid$
[111] data.table_1.14.8 digest_0.6.31 xtable_1.8-4 tidyr_1.3.0 http$
[116] stats4_4.2.0 munsell_0.5.0 viridisLite_0.4.2
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