LTLA
commented
4 years ago Looks like you're using BioC-release, but modelGeneVar is in BioC-devel (scran v1.13.*).
If you want to switch to the BioC-devel version, check out the instructions here.
It's actually a timely question, because the next release is occurring at the end of this month... whereupon modelGeneVar will be available in scran v1.14.0. See here.
FrancesWong
Good afternoon,
I'm trying to follow the workflow from http://bioconductor.org/packages/devel/bioc/vignettes/batchelor/inst/doc/correction.html for batch correcting two SCE. I have scRNAseq, scran, scater, and batchelor installed and loaded but I cannot find the modelGeneVar function to run! I've checked that this function exists from Scran (https://rdrr.io/github/MarioniLab/scran/src/R/modelGeneVar.R) and I tried to install from github for the latest version but it ends with:
` R inst ** byte-compile and prepare package for lazy loading Error: object ‘bsparam’ is not exported by 'namespace:BiocSingular' Execution halted ERROR: lazy loading failed for package ‘scran’
`gcc: error: "/home/brian/R/x86_64-pc-linux-gnu-library/3.6/Rhdf5lib/lib/libhdf5.a": No such file or directory gcc: error: "/home/brian/R/x86_64-pc-linux-gnu-library/3.6/Rhdf5lib/lib/libsz.a": No such file or directory /usr/share/R/share/make/shlib.mk:6: recipe for target 'HDF5Array.so' failed make: *** [HDF5Array.so] Error 1 ERROR: compilation failed for package ‘HDF5Array’
Session Info is: `> sessionInfo() R version 3.6.1 (2019-07-05) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Ubuntu 16.04.5 LTS
Matrix products: default BLAS: /usr/lib/libblas/libblas.so.3.6.0 LAPACK: /usr/lib/lapack/liblapack.so.3.6.0
Random number generation: RNG: Mersenne-Twister Normal: Inversion Sample: Rounding
locale: [1] LC_CTYPE=en_CA.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_CA.UTF-8 LC_COLLATE=en_CA.UTF-8
[5] LC_MONETARY=en_CA.UTF-8 LC_MESSAGES=en_CA.UTF-8
[7] LC_PAPER=en_CA.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_CA.UTF-8 LC_IDENTIFICATION=C
attached base packages: [1] parallel stats4 stats graphics grDevices utils datasets [8] methods base
other attached packages: [1] BiocSingular_1.0.0 batchelor_1.0.1
[3] scRNAseq_1.10.0 scater_1.12.2
[5] ggplot2_3.2.1 scran_1.12.1
[7] SingleCellExperiment_1.6.0 SummarizedExperiment_1.14.1 [9] DelayedArray_0.10.0 BiocParallel_1.18.1
[11] matrixStats_0.55.0 Biobase_2.44.0
[13] GenomicRanges_1.36.1 GenomeInfoDb_1.20.0
[15] IRanges_2.18.3 S4Vectors_0.22.1
[17] BiocGenerics_0.30.0 Rhdf5lib_1.6.2
[19] Seurat_3.1.1
loaded via a namespace (and not attached): [1] ggbeeswarm_0.6.0 Rtsne_0.15 colorspace_1.4-1
[4] ggridges_0.5.1 dynamicTreeCut_1.63-1 XVector_0.24.0
[7] BiocNeighbors_1.2.0 leiden_0.3.1 listenv_0.7.0
[10] npsurv_0.4-0 remotes_2.1.0 ggrepel_0.8.1
[13] codetools_0.2-16 splines_3.6.1 R.methodsS3_1.7.1
[16] lsei_1.2-0 zeallot_0.1.0 jsonlite_1.6
[19] ica_1.0-2 cluster_2.1.0 png_0.1-7
[22] R.oo_1.22.0 uwot_0.1.4 sctransform_0.2.0
[25] BiocManager_1.30.7 compiler_3.6.1 httr_1.4.1
[28] dqrng_0.2.1 backports_1.1.5 assertthat_0.2.1
[31] Matrix_1.2-17 lazyeval_0.2.2 limma_3.40.6
[34] htmltools_0.4.0 tools_3.6.1 rsvd_1.0.2
[37] igraph_1.2.4.1 gtable_0.3.0 glue_1.3.1
[40] GenomeInfoDbData_1.2.1 RANN_2.6.1 reshape2_1.4.3
[43] dplyr_0.8.3 Rcpp_1.0.2 vctrs_0.2.0
[46] gdata_2.18.0 ape_5.3 nlme_3.1-141
[49] DelayedMatrixStats_1.6.1 gbRd_0.4-11 lmtest_0.9-37
[52] stringr_1.4.0 globals_0.12.4 lifecycle_0.1.0
[55] irlba_2.3.3 gtools_3.8.1 statmod_1.4.32
[58] future_1.14.0 edgeR_3.26.8 zlibbioc_1.30.0
[61] MASS_7.3-51.4 zoo_1.8-6 scales_1.0.0
[64] RColorBrewer_1.1-2 curl_4.2 reticulate_1.13
[67] pbapply_1.4-2 gridExtra_2.3 stringi_1.4.3
[70] caTools_1.17.1.2 bibtex_0.4.2 Rdpack_0.11-0
[73] SDMTools_1.1-221.1 rlang_0.4.0 pkgconfig_2.0.3
[76] bitops_1.0-6 lattice_0.20-38 ROCR_1.0-7
[79] purrr_0.3.2 htmlwidgets_1.5.1 cowplot_1.0.0
[82] tidyselect_0.2.5 RcppAnnoy_0.0.13 plyr_1.8.4
[85] magrittr_1.5 R6_2.4.0 gplots_3.0.1.1
[88] withr_2.1.2 pillar_1.4.2 fitdistrplus_1.0-14
[91] survival_2.44-1.1 RCurl_1.95-4.12 tibble_2.1.3
[94] future.apply_1.3.0 tsne_0.1-3 crayon_1.3.4
[97] KernSmooth_2.23-16 plotly_4.9.0 viridis_0.5.1
[100] locfit_1.5-9.1 grid_3.6.1 data.table_1.12.4
[103] metap_1.1 digest_0.6.21 tidyr_1.0.0
[106] R.utils_2.9.0 RcppParallel_4.4.4 munsell_0.5.0
[109] beeswarm_0.2.3 viridisLite_0.3.0 vipor_0.4.5 `
Any assistance in being able to use the modelGeneVar would be greatly appreciated!
Best, -Frances