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D. R. Mani edited this page Mar 22, 2021 · 13 revisions

Introduction

Welcome to the PANOPLY wiki!

PANOPLY is a cloud-based platform for applying statistical and machine learning algorithms to transform multi-omic data from cancer samples into biologically meaningful and interpretable results. PANOPLY leverages Terra, and is designed to be flexible, automated, reproducible, scalable, and secure. A wide array of algorithms for proteogenomic data analysis have been implemented in PANOPLY.

Documentation and Tutorial can be found in the Sidebar.

Requirements

  1. To run PANOPLY, you need a Terra account. To create an account follow the steps here. A Google account is required to create a Terra account.
  2. Once you have an account, you need to create a cloud billing account and project. Here, you will find step-by-step instructions to set up billing, including a free credits program for new users to try out Terra with $300 in Google Cloud credits.

Inputs

Input data consists of a ZIP compressed file containing the following data tables:

Required:
  • Datasets for preconfigured piplelines:
    • At least one proteomics dataset (global proteome, phosphoproteome, acetylome, ubiquitylome) --- after database searching and quantification;
    • Genomics data --- CNA and RNA data (both are required), normalized and filtered as needed;
  • Dataset(s) for running individual analysis modules:
    • At least one dataset: either proteomics (global proteome, phosphoproteome, acetylome, ubiquitylome--after database searching and quantification) or genomics (RNA, CNA--normalized and filtered as needed) data;
  • Annotation table with at least Sample.ID and Type columns, in addition to an arbitrary number of annotations for the samples.
Optional:
  • A groups file that lists a subset of annotations (one per line) to be used for association and enrichment analysis;
  • A default parameter file is used, unless one is specified in the input (in yaml format);
  • Pathway databases for PTM-SEA (PTM-SigDB v1.9.0) and GSEA (v6.2 hallmark pathways) are automatically included, and can be over-ridden by providing appropriate gmt input files.
Input File Specifications:
File Format Specification
annotation csv The annotation table must include Sample.ID and Type columns. Sample.IDs must be unique and cannot have duplicates. If replicate samples are present, they must have unique Sample.IDs, but can be identified as replicates by using an additional Participant annotation column with identical id's for replicate samples. The annotation table input to the panoply_parse_sm_table module must include Experiment (TMT or iTRAQ plex number) and Channel (TMT or iTRAQ channel id).
groups csv Lists annotation columns (one per line) present in the annotation table for use in association and enrichment analysis in various PANOPLY modules. If a groups file is not specified in the input, one will be interactively created by the PANOPLY-startup-notebook using the annotations present in the annotation table.
proteomics data gct v1.3 Can be proteome, phosphoproteome, acetylome, ubiquitylome. Data matrix (resulting from MS database search) must have protein/PTM-site as rows and samples as columns, with entries containing abundance values (usually log2 ratio to a common reference). At least one proteomics data type must be specified. PANOPLY provides an option to normalize proteomics data, if needed.
genomics data gct v1.3 Both CNA (normalized log-ratio, derived from WXS, WGS or combination) and RNA expression (log-transformed and normalized, derived from RNAseq) data are required. These data must be normalized prior to input in PANOPLY. To include mutation data, samples with mutations in relevant genes must be identified and an annotation column added for each gene in the annotation table---maf or vcf cannot be directly input.
parameters yaml The master-parameters.yaml file (also available in the PANOPLY Production Workspaces on Terra) contains default parameter settings for all PANOPLY modules, and is used as a default, if no input parameters file is specified.
pathway databases gmt If no pathway databases are specified in the input, PTM-SigDB v1.9.0 is used for PTM-SEA, and the Cancer Hallmark Pathways v6.2 is used for GSEA and ssGSEA.
Notes:
  • All proteomics and genomics data tables must have sample ids (column names) conforming to the Sample.IDs used in the annotation table. Ideally, the sample annotations included in the annotation table would be present in the GCT v1.3 data files as column annotations.
  • All genomics data tables must be appropriately normalized/filtered prior to use in PANOPLY. Proteomics data can be optionally normalized/filtered in PANOPLY.

Documentation

PANOPLY modules are grouped into Data Preparation, Data Analysis, Report and Support categories. There is also documentation on navigating results. In addition, a step-by-step tutorial is included. The documentation main pages are listed below, and can also be accessed using the sidebar for this Wiki.

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