Data for reproducing Webster figures

# Data for reproducing Webster figures<br>This zip file contains the file structure and input data for plugging into the Webster figure generation code repo (https://github.com/joshbiology/gene_fn).<br>For flat files and Excel spreadsheets containing the actual output of Webster, see our other Figshare (10.6084/m9.figshare.14963561).<br>This folder is strucured as follows:<br>```data├── interim│ ├── biomarker│ └── matlab│ ├── depmap_deep│ ├── depmap_denoise│ ├── depmap_grid│ ├── depmap_wide│ ├── durocher│ ├── durocher_no_graph│ └── synthetic└── raw ├── depmap ├── durocher ├── genesets ├── hart ├── humancellmap ├── nusiance_genesets └── prism```<br><br>## raw<br>This folder contains tables from other resources, described below.<br>* depmap<br>https://depmap.org/<br>* durocher<br>https://pubmed.ncbi.nlm.nih.gov/32649862/<br>* genesets<br>Custom genesets from:<br>* * STAGA/ATAC complexes (Spedale et al., 2012)* * SWI/SNF complexes (Mashtalir et al., 2018).* * Mediator complex (Tsai et al., 2014). * * Integrator complex (Pfleiderer and Galej, 2021; Sabath et al., 2020; Tilley et al., 2021; Zheng et al., 2020)<br><br>* hart<br>Common essential genesets from Hart et al. 2015<br>* humancellmap<br>Subcellular localization info from https://humancellmap.org/ and Go et al. 2021.<br>* nusiance_genesets<br>Genesets from HUGO.<br>* prism<br>Compound sensitivity data from https://depmap.org/repurposing/ and Corsello et al 2020.<br><br>## interim<br>This folder contains MATLAB files (.mat) that are the output of the dual-graph regularized dictionary learning applied with this codebase (https://github.com/joshbiology/graph_dictionary_learning) on preprocessed input data contained here (10.6084/m9.figshare.14963561).<br>* depmap_deep<br>Input: DepMap data. Output: sweep over a few values of k, at t=4 and multiple random seeds.<br>* depmap_denoise<br>Input: DepMap data with added noise. Output: Dictionaries (k=220, t=4) learned on noisy DepMap data.<br>* depmap_grid<br>Input: DepMap data. Output: sweep over many values of k and t.<br>* depmap_wide<br>Input: DepMap data. Output: sweep over many values of k, and t = 4 and the same random seed.<br>* durocher<br>Input: genotoxic fitness data (Olivieri et al 2020). Output: sweep over many values of k, at t=1,2.<br>* durocher_no_graph<br>Input: genotoxic fitness data (Olivieri et al 2020). Output: sweep over many values of k, at t=1,2, with alpha and beta set to 0. <br>* synthetic<br>Input: Synthetic fitness data.<br><br>VersionsV1: Initial commitV2: Cached additional intermediate data in the interim folder.