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gespeR: Gene-Specific Phenotype EstimatoR ====== gespeR is a novel model to estimate gene-specific phenotypes from off-target confounded RNAi screens. The observed phenotype for each siRNA is modeled as a the weighted linear combination of gene-specific phenotypes from the on- and all off-target genes. This deconvolution approach yields highly reproducible phenotypes, essential for unbiased analyses of siRNA screening data. ###### Reference: Fabian Schmich, Ewa Szczurek, Saskia Kreibich, Sabrina Dilling, Daniel Andritschke, Alain Casanova, Shyan Huey Low, Simone Eicher, Simone Muntwiler, Mario Emmenlauer, Pauli Ramo, Raquel Conde-Alvarez, Christian von Mering, Wolf-Dietrich Hardt, Christoph Dehio and Niko Beerenwinkel. <b>[gespeR: a statistical model for deconvoluting off-target-confounded RNA interference screens](</b> <i>Genome Biology</i>, 2015. ### Installation gespeR is hosted on GitHub and available through [Bioconductor]( The package is released under the GNU General Public License (GPL) version 3 and includes examples and a [vignette]( ### Data In addition to the phenotypic readout, gespeR requires siRNA-to-gene target relation matrices, quantifying how strongly each siRNA downregulates transcript genes via on- and off-targeting. These matrices can be computed with miRNA target prediction tools, such as for instance [TargetScan]( ###### Target Relation Matrices Below, we provide pre-computed matrices for all libraries used in Schmich et al., 2015. Wrapper scripts to run TargetScan in batch mode for the prediction of siRNA-to-gene target relation matrices are also available on [GitHub](, including a README with step-by-step instructions. All pre-computed siRNA-to-gene target relation matrices are stored in .rds files using R's serialization interface for single objects. Load the data into R by using the function readRDS(). Note that loading target relation matrices can require up to 5GB of RAM. - [Ambion]( - [Dharmacon]( - [Dharmacon deconvoluted]( - [Qiagen]( - [Qiagen kinome]( - [Validation]( - [Schultz et al., 2011]( ###### Pathogen Infection Screen Phenotypes High-content, image based phenotypes for pathogen infection RNAi screens from the [InfectX consortium]( are hosted at [PubChem]( ### Usage Step-by-step instructions demonstrating how to download, pre-process and deconvolute pathogen infection screen phnotypes is available in form of an [R/Vignette]( ### Contributions - [Fabian Schmich]( - [Ewa Szczurek]( - [Niko Beerenwinkel]( ###Contact ``` Fabian Schmich fabian.schmich (at) ```