A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles. Proteogenomics connects somatic mutations to signalling in breast cancer. PANOPLY: a cloud-based platform for automated and reproducible proteogenomic data analysis. Detailed documentation can be found here.Įmail with questions, comments or feedback.For a quick introduction and tour of PANOPLY, follow the tutorial.Users can also customize or create new pipelines and add their own tasks and integrate them into the PANOPLY.
Mass spectrometry-based proteomics data amenable to analysis by PANOPLY includes isobaric label-based LC-MS/MS approaches like iTRAQ, TMT and TMTPro profiling the proteome and multiple PTM-omes including phospho-, acetyl-and ubiquitylomes. Most analysis modules include a report generation task that outputs a HTML interactive report summarizing results from the respective analysis tasks. PANOPLY provides a comprehensive collection of proteogenomic data analysis methods including sample QC (sample quality evaluation using profile plots and tumor purity scores (1), identify sample swaps, etc.), association analysis, RNA and copy number correlation (to proteome), connectivity map analysis (1 ,2), outlier analysis using BlackSheep (3), PTM-SEA (4), GSEA (5) and single-sample GSEA (6), consensus clustering, and multi-omic clustering using non-negative matrix factorization (NMF). The workspaces include all data, parameter settings and results. Terra workspaces showing case studies of applying PANOPLY to the analysis of CPTAC BRCA (7) and CPTAC LUAD (8) datasets.The PANOPLY_Tutorial workspace contains data and results from running the tuorial. A tutorial illustrating the application of PANOPLY to a published breast cancer dataset and demonstrating the practical relevance of PANOPLY by regenerating many of the results described in (Mertins et al) (1) with minimal effort.A GitHub wiki includes documentation and description of algorithms.
#Panoply org code#
A GitHub repository that contains code for all PANOPLY tasks and workflows, including R code for implementing analysis algorithms, task module creation, and release management.An interactive Jupyter notebook (included in the Terra workspaces) that provides step-by-step instructions for uploading data, identifying data types, specifying parameters, and setting up the PANOPLY workspace for analyzing a new dataset.A Terra production workspace on PANOPLY_Production_Pipelines_v1_1 with a preconfigured unified workflow to automatically run all analysis tasks on proteomics (global proteome, phosphoproteome, acetylome, ubiquitylome), transcriptome and copy number data and an additional workspace that includes separate methods for each analysis component.
PANOPLY v1.2 consists of the following components: A wide array of algorithms applicable to all cancer types have been implemented, and available in PANOPLY for analysis of cancer proteogenomic data. PANOPLY leverages Terra-a cloud-native platform for extreme-scale data analysis, sharing, and collaboration-to host proteogenomic workflows, and is designed to be flexible, automated, reproducible, scalable, and secure. PANOPLY is a platform for applying state-of-the-art statistical and machine learning algorithms to transform multi-omic data from cancer samples into biologically meaningful and interpretable results. Our readers have come to expect excellence from our products, and they can count on us to maintain a commitment to producing rigorous and innovative information products in whatever forms the future of publishing may bring.PANOPLY: A cloud-based platform for automated and reproducible proteogenomic data analysis Version 1.2 Through our commitment to new products-whether digital journals or entirely new forms of communication-we have continued to look for the most efficient and effective means to serve our readership. Since the late 1960s, we have experimented with generation after generation of electronic publishing tools. The Press's enthusiasm for innovation is reflected in our continuing exploration of this frontier. We were among the first university presses to offer titles electronically and we continue to adopt technologies that allow us to better support the scholarly mission and disseminate our content widely. Among the largest university presses in the world, The MIT Press publishes over 200 new books each year along with 30 journals in the arts and humanities, economics, international affairs, history, political science, science and technology along with other disciplines.
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