Problem: FindMotifs gives a (slightly cryptic) error message when run with only one feature
library("Signac")
library("JASPAR2020")
library("TFBSTools")
library("BSgenome.Hsapiens.UCSC.hg19")
pfm <- getMatrixSet(x = JASPAR2020,
opts = list(species = 9606, all_versions = FALSE))
# add motif information
atac_small <- AddMotifs(object = atac_small,
genome = BSgenome.Hsapiens.UCSC.hg19,
pfm = pfm)
motifs <- FindMotifs(object = atac_small, features = "chr1-9064752-9065614")
# Selecting background regions to match input sequence characteristics
# Matching GC.percent distribution
# Testing motif enrichment in 1 regions
# Error in base::colSums(x, na.rm = na.rm, dims = dims, ...) :
# 'x' must be an array of at least two dimensions
Expected result: that is would be possible (even if it's probably not biologically meaningful!) to run FindMotifs on any number of features, or that it would fail with an error message that makes it clear what the issue is without reading the code
Proposed solution: If you add drop=FALSE to the matrix subsetting statement in this line and the one below, the objects returned will be matrices even if they only have one row, so colSums will work.
sessionInfo() # R version 4.1.0 (2021-05-18) # Platform: x86_64-pc-linux-gnu (64-bit) # Running under: Ubuntu 20.04.2 LTS # # Matrix products: default # BLAS/LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.8.so # # locale: # [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8 # [6] LC_MESSAGES=C LC_PAPER=en_US.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C # [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C # # attached base packages: # [1] stats4 parallel stats graphics grDevices utils datasets methods base # # other attached packages: # [1] BSgenome.Hsapiens.UCSC.hg19_1.4.3 BSgenome_1.60.0 rtracklayer_1.52.0 Biostrings_2.60.1 # [5] XVector_0.32.0 GenomicRanges_1.44.0 GenomeInfoDb_1.28.1 IRanges_2.26.0 # [9] S4Vectors_0.30.0 BiocGenerics_0.38.0 TFBSTools_1.30.0 JASPAR2020_0.99.10 # [13] Signac_1.3.0 # # loaded via a namespace (and not attached): # [1] utf8_1.2.1 reticulate_1.20 R.utils_2.10.1 tidyselect_1.1.1 poweRlaw_0.70.6 # [6] RSQLite_2.2.7 AnnotationDbi_1.54.1 htmlwidgets_1.5.3 grid_4.1.0 docopt_0.7.1 # [11] BiocParallel_1.26.1 Rtsne_0.15 munsell_0.5.0 codetools_0.2-18 ica_1.0-2 # [16] future_1.21.0 miniUI_0.1.1.1 colorspace_2.0-2 Biobase_2.52.0 knitr_1.33 # [21] rstudioapi_0.13 Seurat_4.0.3 ROCR_1.0-11 tensor_1.5 listenv_0.8.0 # [26] MatrixGenerics_1.4.0 slam_0.1-48 GenomeInfoDbData_1.2.6 polyclip_1.10-0 bit64_4.0.5 # [31] farver_2.1.0 parallelly_1.26.1 vctrs_0.3.8 generics_0.1.0 xfun_0.24 # [36] lsa_0.73.2 ggseqlogo_0.1 R6_2.5.0 bitops_1.0-7 spatstat.utils_2.2-0 # [41] cachem_1.0.5 DelayedArray_0.18.0 assertthat_0.2.1 promises_1.2.0.1 BiocIO_1.2.0 # [46] scales_1.1.1 gtable_0.3.0 globals_0.14.0 goftest_1.2-2 seqLogo_1.58.0 # [51] rlang_0.4.11 RcppRoll_0.3.0 splines_4.1.0 lazyeval_0.2.2 spatstat.geom_2.2-2 # [56] BiocManager_1.30.16 yaml_2.2.1 reshape2_1.4.4 abind_1.4-5 httpuv_1.6.1 # [61] tools_4.1.0 ggplot2_3.3.5 ellipsis_0.3.2 spatstat.core_2.2-0 RColorBrewer_1.1-2 # [66] ggridges_0.5.3 Rcpp_1.0.7 plyr_1.8.6 zlibbioc_1.38.0 purrr_0.3.4 # [71] RCurl_1.98-1.3 rpart_4.1-15 deldir_0.2-10 pbapply_1.4-3 cowplot_1.1.1 # [76] zoo_1.8-9 SeuratObject_4.0.2 SummarizedExperiment_1.22.0 ggrepel_0.9.1 cluster_2.1.2 # [81] motifmatchr_1.14.0 magrittr_2.0.1 data.table_1.14.0 scattermore_0.7 lmtest_0.9-38 # [86] RANN_2.6.1 SnowballC_0.7.0 fitdistrplus_1.1-5 matrixStats_0.59.0 hms_1.1.0 # [91] patchwork_1.1.1 mime_0.11 evaluate_0.14 xtable_1.8-4 XML_3.99-0.6 # [96] sparsesvd_0.2 gridExtra_2.3 compiler_4.1.0 tibble_3.1.2 KernSmooth_2.23-20 # [101] crayon_1.4.1 R.oo_1.24.0 htmltools_0.5.1.1 mgcv_1.8-36 later_1.2.0 # [106] tidyr_1.1.3 DBI_1.1.1 tweenr_1.0.2 MASS_7.3-54 Matrix_1.3-4 # [111] readr_1.4.0 R.methodsS3_1.8.1 igraph_1.2.6 pkgconfig_2.0.3 GenomicAlignments_1.28.0 # [116] TFMPvalue_0.0.8 plotly_4.9.4.1 spatstat.sparse_2.0-0 annotate_1.70.0 DirichletMultinomial_1.34.0 # [121] stringr_1.4.0 digest_0.6.27 sctransform_0.3.2 RcppAnnoy_0.0.18 pracma_2.3.3 # [126] CNEr_1.28.0 spatstat.data_2.1-0 rmarkdown_2.9 leiden_0.3.8 fastmatch_1.1-0 # [131] uwot_0.1.10 restfulr_0.0.13 shiny_1.6.0 Rsamtools_2.8.0 gtools_3.9.2 # [136] rjson_0.2.20 lifecycle_1.0.0 nlme_3.1-152 jsonlite_1.7.2 viridisLite_0.4.0 # [141] fansi_0.5.0 pillar_1.6.1 lattice_0.20-44 KEGGREST_1.32.0 fastmap_1.1.0 # [146] httr_1.4.2 survival_3.2-11 GO.db_3.13.0 glue_1.4.2 qlcMatrix_0.9.7 # [151] png_0.1-7 bit_4.0.4 ggforce_0.3.3 stringi_1.7.2 blob_1.2.1 # [156] caTools_1.18.2 memoise_2.0.0 dplyr_1.0.7 irlba_2.3.3 future.apply_1.7.0
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