Inferring global protein activity profiles by network based analysis of gene expression signatures

<p>This file contains all the normalized datasets and R-scripts used in the "Inferring global protein activity profiles<br>by network based analysis of gene expression signatures" manuscript by  Mariano J. Alvarez, Yao Shen, B. Belinda Ding, B. Hilda Ye and Andrea Califano.</p

Bcell example R-data package

<p>This is an R-system data package containing a human B-cell gene expression dataset and a transcriptional regulatory network required by the ssmarina R-system package Sweave vignette.</p

MCF7 human breast carcinoma cell line transcriptional regulatory network

<p>The MCF7 human breast carcinoma cell line transcriptional regulatory network was reverse engineered by the ARACNe algorithm (PMID 16723010) from 527 MCF7 cell line samples perturbed with small molecule compounds for 6h (Connectivity MAP). Gene expression was profiled on Affymetrix H-GU133A arrays, processed by the cleaner algorithm (PMID 20042104), and normalized with MAS5 (affy package from Bioconductor). The regulatory network ('regul', 623 transcription factors regulating 5,982 target genes through 90,870 interactions) and the expression dataset used to assemble it ('dset', 527 samples x 6,839 probe-sets) are included as an R-system binary file.</p

Human B-cell transcriptional regulatory network

<p>The human B-cell regulatory network was reverse engineered by the ARACNe algorithm (PMID 16723010) from 264 samples including normal (naive and greminal center B-cells), several tumor phnotypes (B-cell lymphomas) and cell lines. Gene expression was profiled on Affymetrix H-GU133Plus2 arrays, processed by the cleaner algorithm (PMID 20042104), and normalized with MAS5 (affy package from Bioconductor). The regulatory network ('regul', 1,223 transcription factors regulating 13,007 target genes through 327,837 interactions) and the expression dataset used to assemble it ('dset', 264 samples x 13,007 probe-sets) are included as an R-system binary file.</p

Human vs. mouse prostate interactome comparison

<p>This file contains a SWEAVE document and the resulting PDF document for the analysis of conservation between human and mouse prostate transcriptional interactomes</p

Human glioma transcriptional regulatory network

<p>The human glioma regulatory network was reverse engineered by the ARACNe algorithm (PMID 16723010) from 176 human glioma grade III and IV samples. Gene expression was profiled on Affymetrix H-GU133A arrays, processed by the cleaner algorithm (PMID 20042104), and normalized with MAS5 (affy package from Bioconductor). The regulatory network ('regul', 835 transcription factors regulating 8,263 target genes through 256,965 interactions) and the expression dataset used to assemble it ('dset', 176 samples x 9,535 probe-sets) are included as an R-system binary file.</p

Sweave document and datasets for Ikiz et.al. manuscript: "The regulatory machinery of neurodegeneration in in vitro models of amyotrophic lateral sclerosis" published in Cell Reports

<p>This file contains a Sweave document and additional datasets and regulatory networks required to run it.</p> <p>The Sweave document contains the data analysis pipeline for the Ikiz et.al. manuscript " The regulatory machinery of neurodegeneration in in vitro models of amyotrophic lateral sclerosis"</p

GEP-NET transcriptional regulatory network

Gastro-Entero-Pancreatic Neuroendocrine Tumors (GEP-NET) transcriptional regulatory network assembled by the ARACNe algorithm and formated to be used with the VIPER algorith

crosspeciesData

<p>This is an R-system (www.r-project.org) package that contains 4 human and 1 mouse prostate carcinoma genome-wide expression datasets, and 6 transcriptional interactomes</p

Human breast carcinoma signalome regulatory network

<p>The human breast carcinoma signalome regulatory network was reverse engineered by the ARACNe algorithm (PMID 16723010) from 851 human breast invasive carcinoma samples profiled by RNASeq by "The Cancer Genome Atlas" (TCGA). The level 3 raw counts data was normalized and varianze stabilized using the DESeq package from Bioconductor (PMID 12664684). The regulatory network ('regul', 2,020 signaling genes regulating 18,135 target genes through 509,011 interactions) and the expression dataset used to assemble it ('dset', 851 samples x 20,155 genes) are included as an R-system binary file.</p