search

hemberg-lab / SC3

A tool for the unsupervised clustering of cells from single cell RNA-Seq experiments
http://bioconductor.org/packages/SC3
GNU General Public License v3.0
119 stars 55 forks source link

compute time #38

Closed yuqiyuqitan closed 7 years ago

yuqiyuqitan commented 7 years ago

Hi, I ran 500 cells scRNA-seq data (gene_filter = TRUE, and ks = 5:15) on my local computer (MacBook Pro (2016), OS Sierra 10.12.5 with 2.5 GHz Intel Core i7 processor, 16 GB 1600 MHz DDR3 of RAM). It took 3hrs to finish the run. Could you share with me the command or parameters you used to achieve sc3 clustering 5k cells in 20min as mentioned in the paper?

Thanks!

wikiselev commented 7 years ago

Hi, could you provide your sessionInfo() information?

yuqiyuqitan commented 7 years ago

R version 3.3.1 (2016-06-21) Platform: x86_64-apple-darwin13.4.0 (64-bit) Running under: OS X 10.12.5 (Sierra)

locale: [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages: [1] parallel stats graphics grDevices utils datasets methods base

other attached packages: [1] shiny_1.0.3 SC3_1.1.4 singleCellNet_0.0.0.9000 CellNet_0.0.0.9000
[5] scater_1.0.4 ggplot2_2.2.1 Biobase_2.32.0 BiocGenerics_0.18.0

loaded via a namespace (and not attached): [1] bitops_1.0-6 matrixStats_0.52.2 doParallel_1.0.10 RColorBrewer_1.1-2 tools_3.3.1
[6] doRNG_1.6.6 R6_2.2.2 KernSmooth_2.23-15 DBI_0.6-1 lazyeval_0.2.0
[11] colorspace_1.3-2 gridExtra_2.2.1 compiler_3.3.1 pkgmaker_0.22 labeling_0.3
[16] caTools_1.17.1 scales_0.4.1 DEoptimR_1.0-8 mvtnorm_1.0-6 robustbase_0.92-7
[21] randomForest_4.6-12 stringr_1.2.0 digest_0.6.12 wdman_0.2.2 rrcov_1.4-3
[26] htmltools_0.3.6 WriteXLS_4.0.0 limma_3.28.21 rlang_0.1.1 RSQLite_1.1-2
[31] jsonlite_1.5 gtools_3.5.0 dplyr_0.7.0 RCurl_1.95-4.8 magrittr_1.5
[36] Rcpp_0.12.11 munsell_0.4.3 S4Vectors_0.10.3 viridis_0.4.0 stringi_1.1.5
[41] edgeR_3.14.0 zlibbioc_1.18.0 rhdf5_2.16.0 gplots_3.0.1 Rtsne_0.13
[46] plyr_1.8.4 grid_3.3.1 gdata_2.17.0 shinydashboard_0.6.1 semver_0.2.0
[51] lattice_0.20-35 igraph_1.0.1 rjson_0.2.15 rngtools_1.2.4 reshape2_1.4.2
[56] codetools_0.2-15 biomaRt_2.28.0 stats4_3.3.1 XML_3.98-1.7 glue_1.1.0
[61] data.table_1.10.4 httpuv_1.3.3 foreach_1.4.3 gtable_0.2.0 openssl_0.9.6
[66] tidyr_0.6.1 assertthat_0.2.0 binman_0.1.0 mime_0.5 xtable_1.8-2
[71] e1071_1.6-8 class_7.3-14 pcaPP_1.9-61 viridisLite_0.2.0 tibble_1.3.3
[76] pheatmap_1.0.8 iterators_1.0.8 RSelenium_1.7.1 AnnotationDbi_1.34.4 registry_0.3
[81] memoise_1.1.0 IRanges_2.6.1 tximport_1.0.3 cluster_2.0.6 ROCR_1.0-7

wikiselev commented 7 years ago

Hi, you have a very old version of SC3 (I am surprised it's still working...). Please update your R to 3.4.0, then update Bionconductor to 3.5. After that reinstall both scater and SC3 packages, so that scater is 1.4.0 and SC3 is 1.4.2. Then you should have fast compute times. For the newest version please follow the SC3 vignette.

wikiselev commented 7 years ago

I assume your problem have been solved, so I am closing this issue. Feel free to reopen it if it's still exist.