hemberg-lab
Error in !isSpike(object) : invalid argument type
Hi,
I guess this is somehow related with #53 or 10X data. I tried to run sc3 on a 10x data set. Based on #53 , I manually convert both counts slot and logcounts slot to a standard/regular matrix. However, I am getting another error
Setting SC3 parameters...
Error in !isSpike(object) : invalid argument type
It seems the issue came from gene_filter. Set gene_filter = FALSE will make the code work. 10X data most likely will have no Spike-in. For my data set, isSpike(mySingleCellExperiment) will return NULL, which is the expected behavior.
Here is my session info:
R version 3.4.2 (2017-09-28)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Debian GNU/Linux 9 (stretch)
Matrix products: default
BLAS/LAPACK: /usr/lib/libopenblasp-r0.2.19.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=C LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C 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] SC3_1.7.2 Rtsne_0.13 cowplot_0.9.1 scater_1.6.1
[5] SingleCellExperiment_1.0.0 SummarizedExperiment_1.8.0 DelayedArray_0.4.0 matrixStats_0.52.2
[9] GenomicRanges_1.30.0 GenomeInfoDb_1.14.0 IRanges_2.12.0 S4Vectors_0.16.0
[13] ggplot2_2.2.1 Biobase_2.38.0 BiocGenerics_0.24.0 knitr_1.17
loaded via a namespace (and not attached):
[1] bitops_1.0-6 bit64_0.9-7 RColorBrewer_1.1-2 doParallel_1.0.11 progress_1.1.2
[6] tools_3.4.2 doRNG_1.6.6 R6_2.2.2 KernSmooth_2.23-15 vipor_0.4.5
[11] DBI_0.7 lazyeval_0.2.1 colorspace_1.3-2 gridExtra_2.3 prettyunits_1.0.2
[16] bit_1.1-12 compiler_3.4.2 pkgmaker_0.22 caTools_1.17.1 scales_0.5.0
[21] mvtnorm_1.0-6 DEoptimR_1.0-8 robustbase_0.92-8 stringr_1.2.0 digest_0.6.12
[26] XVector_0.18.0 rrcov_1.4-3 pkgconfig_2.0.1 htmltools_0.3.6 WriteXLS_4.0.0
[31] limma_3.34.4 rlang_0.1.2 RSQLite_2.0 shiny_1.0.5 bindr_0.1
[36] gtools_3.5.0 dplyr_0.7.4 RCurl_1.95-4.8 magrittr_1.5 GenomeInfoDbData_0.99.1
[41] Matrix_1.2-11 Rcpp_0.12.14 ggbeeswarm_0.6.0 munsell_0.4.3 viridis_0.4.0
[46] stringi_1.1.5 yaml_2.1.14 edgeR_3.20.1 zlibbioc_1.24.0 rhdf5_2.22.0
[51] gplots_3.0.1 plyr_1.8.4 grid_3.4.2 blob_1.1.0 gdata_2.18.0
[56] shinydashboard_0.6.1 lattice_0.20-35 locfit_1.5-9.1 rjson_0.2.15 rngtools_1.2.4
[61] reshape2_1.4.2 codetools_0.2-15 biomaRt_2.34.0 XML_3.98-1.9 glue_1.2.0
[66] data.table_1.10.4-3 httpuv_1.3.5 foreach_1.4.4 gtable_0.2.0 assertthat_0.2.0
[71] mime_0.5 xtable_1.8-2 e1071_1.6-8 pcaPP_1.9-72 class_7.3-14
[76] viridisLite_0.2.0 pheatmap_1.0.8 tibble_1.3.4 iterators_1.0.9 AnnotationDbi_1.40.0
[81] registry_0.5 beeswarm_0.2.3 memoise_1.1.0 tximport_1.6.0 bindrcpp_0.2
[86] cluster_2.0.6 ROCR_1.0-7
Thanks in advance, Yi-Chien.
@yicheinchang sorry for a delayed response, have you figured the problem? If not, could you please share your dataset with [email protected]?
Hi @wikiselev Unfortunately, I couldn't share my actual data. However, I suspected this is a 10X specific issue. Perhaps you can reproduce this issue by using the public datasets released by 10X Single Cell Gene Expression Datasets
In addition, I found a quick workaround. All you need is to explicitly set the spike-in information even when there is no spike-in in the experiment. For example,
isSpike(sce, "ERCC") <- rep(FALSE, time = nrow(sce))
Best, Yi-Chien.