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Aleksobrad / single-cell-rcc-pipeline

Data files and code for analysis of single-cell ccRCC data for the manuscript "Tumor-Specific Cell Populations in Clear Cell Renal Carcinoma Associated with Clinical Outcome Identified Using Single-Cell Protein Activity Inference." Includes code for VIPER protein activity inference pipeline
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where is the data of the file sc_nets? #3

Closed liu-zzu closed 3 years ago

liu-zzu commented 3 years ago

Hello, When I run the R script singlecell_gex_viper_analysis.R, there is an error. where is the data of the file sc_nets? " filenames <- list.files("sc_nets/", pattern="Patient*", full.names=TRUE)" Thanks !!!

Aleksobrad commented 3 years ago

sc_nets is the subdirectory available at https://github.com/Aleksobrad/single-cell-rcc-pipeline/tree/master/sc_nets

On Fri, Jul 16, 2021 at 1:43 PM liu-zzu @.***> wrote:

Hello, When I run the R script singlecell_gex_viper_analysis.R, there is an error. where is the data of the file sc_nets? " filenames <- list.files("sc_nets/", pattern="Patient*", full.names=TRUE)" Thanks !!!

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liu-zzu commented 3 years ago

Thank you for your kind reply! Between lines 1320 and 1340 in the R script “singlecell_gex_viper_analysis.R”, the code that generates the ARACNe network results seems to be missing there. Where is the code that generates the data in sc_nets file ? Best wishes!

Aleksobrad commented 3 years ago

The code that generates the ARACNe networks is not implemented in R, and instead uses the java implementation of the ARACNe-AP tool from https://github.com/califano-lab/ARACNe-AP

ARACNE is executed on the .rds files created in local environment by the makeCMFA() function within the R script. For each of these files ARACNe is run on our high-performance computing cluster to improve speed by parallelization. We describe this workflow in more detail at https://github.com/califano-lab/PISCES and in https://www.biorxiv.org/content/10.1101/2021.05.20.445002v2

We are working on future implementations of ARACNe executable directly from R, but at the moment ARACNe must be run separately within the overall workflow and requires a significant amount of compute time, or else a pre-computed set of ARACNe networks can be provided as input to downstream VIPER inferences.

On Fri, Jul 16, 2021 at 10:58 PM liu-zzu @.***> wrote:

Thank you for your kind reply! Between lines 1320 and 1340 in the R script “singlecell_gex_viper_analysis.R”, the code that generates the ARACNe network results seems to be missing there. Where is the code that generates the data in sc_nets file ? Best wishes!

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liu-zzu commented 3 years ago

Thank you for your prompt reply！ Maybe you can set up a separate R script for parallel computing ARACNe network with library(parallel) in R。 Single-cell protein activity inference is very valuable work. And if it is easy to use, it would be universally welcomed. Best wishes!

baoyulinn commented 2 years ago

Where is the Rscript "singlecell_gex_viper_analysis.R" ? Thank you!

Aleksobrad commented 2 years ago

https://github.com/Aleksobrad/single-cell-rcc-pipeline/blob/master/singlecell_gex_viper_analysis.R

On Mon, Sep 12, 2022 at 10:48 PM baoyulinn @.***> wrote:

Where is the Rscript "singlecell_gex_viper_analysis.R" ? Thank you!

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