1.1.13

.github/workflows/main.yml

@@ -26,6 +26,7 @@ on:
 jobs:
   build:
     runs-on: ${{ matrix.os }}
+    timeout-minutes: 300
     strategy:
       matrix:
         os: [ubuntu-latest, macos-latest]
@@ -56,6 +57,12 @@ jobs:
              website
              coverage
 
+      - name: Install blas/lapack
+        run: |
+            La_library()
+            extSoftVersion()["BLAS"]
+        shell: Rscript {0}
+
       - name: Install reticulate
         run: |
             library("reticulate")

DESCRIPTION

@@ -1,6 +1,7 @@
 Package: netZooR
+Type: Package
 Title: Unified methods for the inference and analysis of gene regulatory networks
-Version: 1.1.12
+Version: 1.1.14
 Date: 2022-07-07
 Authors@R: c(person("Marouen", "Ben Guebila",
 			email = "benguebila@hsph.harvard.edu", role = c("aut","cre"), comment = c(ORCID = "0000-0001-5934-966X")),
@@ -18,6 +19,7 @@ Authors@R: c(person("Marouen", "Ben Guebila",
                         email = "",role = "aut", comment = c(ORCID = "0000-0003-4979-5871")),
 		 person("Kate", "Shutta",
                         email = "",role = "ctb", comment = c(ORCID = "0000-0003-0402-3771")))
+Maintainer: Marouen Ben Guebila <benguebila@hsph.harvard.edu>
 Description: netZooR unifies the implementations of several Network Zoo methods (netzoo, netzoo.github.io) into a single package by creating interfaces between network inference and network analysis methods. Currently, the package has 3 methods for network inference including PANDA and its optimized implementation OTTER (network reconstruction using mutliple lines of biological evidence), LIONESS (single-sample network inference), and EGRET (genotype-specific networks). Network analysis methods include CONDOR (community detection), ALPACA (differential community detection), CRANE (significance estimation of differential modules), MONSTER (estimation of network transition states). In addition, YARN allows to process gene expresssion data for tissue-specific analyses and SAMBAR infers missing mutation data based on pathway information.
 Depends: R (>= 4.1.0),
    	 igraph,
@@ -75,4 +77,4 @@ VignetteEngine: knitr
 VignetteBuilder: knitr
 RoxygenNote: 7.1.2
 BugReports: https://github.com/netZoo/netZooR/issues
-URL: https://github.com/netZoo/netZooR, https://netzoo.github.io/
+URL: https://github.com/netZoo/netZooR, https://netzoo.github.io/

NEWS.md

@@ -1,4 +1,4 @@
-CHANGES IN VERSION 1.0.11
+CHANGES IN VERSION 1.1.12
 --------------------------
 
     o Reactivated unit tests for Ubuntu GitHub actions.

R/LIONESS.R

@@ -132,8 +132,10 @@ lionessPy <- function(expr_file, motif_file=NULL, ppi_file=NULL, computing="cpu"
    # create an instance named "lioness_obj" of Lioness Class.
    # when save_single_network = TRUE
    if(save_single_network==TRUE){
-   py_run_string(paste("lioness_obj = Lioness(panda_obj", " , " , "computing='", computing, "' , ","start=", start_sample," , ", "end=" ,end_sample, " , " ,'save_single_network= True', " , ", "save_dir='", save_dir, "' , " , "save_fmt='" , save_fmt, "' )",sep = "" ))
-   } else {py_run_string(paste("lioness_obj = Lioness(panda_obj", " , " , "computing='", computing, "' , ","start=", start_sample," , ", "end=" ,end_sample,  ")",sep = "" ))}
+     py_run_string(paste("lioness_obj = Lioness(panda_obj", " , " , "computing='", computing, "' , ","start=", start_sample," , ", "end=" ,end_sample, " , ", "save_dir='", save_dir, "' , " , "save_fmt='" , save_fmt, "' )",sep = "" ))
+   }else{
+     py_run_string(paste("lioness_obj = Lioness(panda_obj", " , " , "computing='", computing, "' , ","start=", start_sample," , ", "end=" ,end_sample,  ")",sep = "" ))
+  }
 
    # retrieve the "total_lioness_network" attribute of instance "lionesss_obj"
    py_run_string("lioness_network = lioness_obj.export_lioness_results",local = FALSE, convert = TRUE)

README.md

@@ -4,7 +4,7 @@
 [![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)
 <a href="https://netzoo.github.io/netZooR/"><img src="https://img.shields.io/badge/docs-passing-green"></a>
 [![tutorials](https://img.shields.io/badge/netZooR-tutorials-9cf)](https://github.com/netZoo/netZooR/tree/master/vignettes)
-[![netBooks](https://img.shields.io/badge/netZooR-netBooks-ff69b4)](http://netbooks.networkmedicine.org/user/marouenbg/notebooks/Welcome_to_netBooks.ipynb?)
+[![Netbooks](https://img.shields.io/badge/netZooR-Netbooks-ff69b4)](http://netbooks.networkmedicine.org/user/marouenbg/notebooks/Welcome_to_netBooks.ipynb?)
 [![discussions](https://img.shields.io/badge/netZooR-discussions-orange)](https://github.com/netZoo/netZooR/discussions)
 
 

inst/CITATION

@@ -0,0 +1,12 @@
+citEntry(entry="article",
+         title = "The Network Zoo: a multilingual package for the inference and analysis of biological networks",
+         author = personList( as.person("Marouen Ben Guebila"),
+                              as.person("Tian Wang"),
+                              as.person("John Quackenbush")),
+         year = 2022,
+         journal = "bioRxiv",
+         doi = "10.1101/2022.05.30.494077",
+         textVersion = 
+         paste("Ben Guebila, M, Wang, T., Quackenbush, J.", 
+               "The Network Zoo: a multilingual package for the inference and analysis of biological networks",
+                "bioRxiv, 2022" ) )