r3fang / SnapATAC

Analysis Pipeline for Single Cell ATAC-seq

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Installation issues

darlene003 opened this issue · comments

I've been trying to install SnapATAC and am running into all kinds of issues, which I think are due to not having the right versions of dependencies.

Can you please give me a list of everything needed, including R packages and other modules, to install SnapATAC successfully?

Thank you!

I managed to install it using a conda environment with R 3.4.3 and and python 2.7, downloading manually some R packages as Matrix and rhdf5 and reinstalling SnapATAC.

Despite installing, it does not work. I run into this old issue #114 , but having right version of rhdf5 loaded in the session:

`> library(SnapATAC)
Loading required package: Matrix
Loading required package: rhdf5

sessionInfo()
R version 3.4.3 (2017-11-30)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.7 LTS

Matrix products: default
BLAS: /comun/marian/juliam/miniconda3/envs/R-3.4/lib/R/lib/libRblas.so
LAPACK: /comun/marian/juliam/miniconda3/envs/R-3.4/lib/R/lib/libRlapack.so

locale:
[1] LC_CTYPE=en_GB.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_GB.UTF-8 LC_COLLATE=en_GB.UTF-8
[5] LC_MONETARY=en_GB.UTF-8 LC_MESSAGES=en_GB.UTF-8
[7] LC_PAPER=en_GB.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C

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

other attached packages:
[1] SnapATAC_1.0.0 rhdf5_2.22.0 Matrix_1.2-14
[4] RevoUtils_10.0.8 RevoUtilsMath_10.0.1

loaded via a namespace (and not attached):
[1] Rcpp_0.12.14 pillar_1.0.1 plyr_1.8.4
[4] compiler_3.4.3 RColorBrewer_1.1-2 GenomeInfoDb_1.14.0
[7] XVector_0.18.0 viridis_0.4.0 bitops_1.0-6
[10] iterators_1.0.9 zlibbioc_1.24.0 viridisLite_0.2.0
[13] tibble_1.4.1 gtable_0.2.0 Rtsne_0.13
[16] lattice_0.20-35 rlang_0.1.6 pkgconfig_2.0.1
[19] doSNOW_1.0.16 foreach_1.4.5 igraph_1.1.2
[22] parallel_3.4.3 gridExtra_2.3 GenomeInfoDbData_1.0.0
[25] S4Vectors_0.16.0 IRanges_2.12.0 stats4_3.4.3
[28] locfit_1.5-9.1 plot3D_1.1.1 grid_3.4.3
[31] snow_0.4-2 bigmemory_4.5.31 bigmemory.sri_0.1.3
[34] RANN_2.5.1 limma_3.34.9 irlba_2.3.1
[37] ggplot2_2.2.1 edgeR_3.20.9 magrittr_1.5
[40] scales_0.5.0 codetools_0.2-15 BiocGenerics_0.24.0
[43] GenomicRanges_1.30.3 misc3d_0.8-4 colorspace_1.3-2
[46] lazyeval_0.2.1 munsell_0.4.3 RCurl_1.95-4.9
[49] doParallel_1.0.12`

If anyone can help me fixing this issue, I could share the conda environment to help setting up SnapATAC for other users.

I managed using:

conda create -n testR3 python=2.7 r-base=3.6 r-terra=1.2 bioconductor-rhdf5=2.30 r-usethis=2.0.1 r-biocmanager r-dosnow r-plot3d r-ggplot2 r-umap r-gridextra pybedtools

conda activate testR3

pip install snaptools

R

install.packages("devtools", repos = "https://stat.ethz.ch/CRAN/")

devtools::install_github("r3fang/SnapATAC")

library(SnapATAC)

This is not clean as it mixes conda environment with manual installation but it works...

> sessionInfo()
R version 3.6.3 (2020-02-29)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: Arch Linux

Matrix products: default
BLAS/LAPACK: /home/ldelisle/.conda/envs/testR3/lib/libopenblasp-r0.3.18.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=C                  LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
[1] SnapATAC_1.0.0 rhdf5_2.30.0   Matrix_1.3-3  

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.6             pillar_1.6.1           plyr_1.8.6            
 [4] compiler_3.6.3         RColorBrewer_1.1-2     GenomeInfoDb_1.22.0   
 [7] XVector_0.26.0         viridis_0.6.2          bitops_1.0-7          
[10] iterators_1.0.13       zlibbioc_1.32.0        viridisLite_0.4.0     
[13] tibble_3.1.2           gtable_0.3.0           lifecycle_1.0.0       
[16] Rtsne_0.15             lattice_0.20-44        rlang_0.4.11          
[19] pkgconfig_2.0.3        doSNOW_1.0.19          foreach_1.5.1         
[22] igraph_1.2.11          parallel_3.6.3         gridExtra_2.3         
[25] GenomeInfoDbData_1.2.2 vctrs_0.3.8            S4Vectors_0.24.0      
[28] IRanges_2.20.0         stats4_3.6.3           locfit_1.5-9.4        
[31] plot3D_1.4             grid_3.6.3             glue_1.6.2            
[34] R6_2.5.0               snow_0.4-3             fansi_0.4.2           
[37] bigmemory_4.5.36       bigmemory.sri_0.1.3    tcltk_3.6.3           
[40] RANN_2.6.1             limma_3.42.2           irlba_2.3.5           
[43] ggplot2_3.3.3          Rhdf5lib_1.8.0         edgeR_3.28.1          
[46] magrittr_2.0.1         ellipsis_0.3.2         scales_1.1.1          
[49] codetools_0.2-18       BiocGenerics_0.32.0    GenomicRanges_1.38.0  
[52] misc3d_0.9-0           colorspace_2.0-1       utf8_1.2.1            
[55] munsell_0.5.0          RCurl_1.98-1.3         doParallel_1.0.17     
[58] crayon_1.4.1   

Thanks @lldelisle !! The solution above still seems to work for me in June 2022, with an additional manual install install.packages("https://cran.r-project.org/src/contrib/Archive/locfit/locfit_1.5-9.2.tar.gz") since the latest version of locfit as of writing requires R ≥ 4.1.0. Cheers!

Thanks @lldelisle . Works very well.

I created a conda env file (env.yaml) using your solution and attached as zipped it to this comment. To avoid manual packages installation, I added "r-devtools", bioconductor-edger" to the list.

Note: old-versions is the name of the conda env I'm creating using the yaml file.

In command line:
$ conda env create -f env.yaml
$ conda activate old-versions
$ pip install snaptools
$ R

Then inside R:
devtools::install_github("r3fang/SnapATAC")
library(SnapATAC)

Bests,
env.zip