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Omics Studio documentation ​

Welcome to the Omics Studio documentation. Whether you are setting up your first project, preparing data files for upload, or running enrichment analyses, this documentation covers the full platform workflow from start to finish.

The guides are organized into three sections - getting started, data preparation, and analysis - so you can jump directly to what you need.

Prepare your data for upload ​

Omics Studio works with CSV files. Before uploading, your files need to follow specific formatting rules. These guides explain the requirements for each file type, with examples and common pitfalls to avoid.

  • Expression Matrix CSV - How to format your abundance or expression values, including supported orientations, valid molecule IDs, and how missing values are handled.
  • Statistics CSV - How to format differential expression results, including required columns, comparison naming conventions, and rules for uploading multiple statistics files.
  • Sample Metadata CSV - How to describe your samples with group, treatment, timepoint, or any other attributes used for labeling in plots.
  • Feature Metadata CSV - How to provide additional annotations for your molecules, such as names, categories, or descriptions.
  • Uploading Datasets - A step-by-step guide to creating a dataset in Omics Studio, uploading your files, and preparing them for use in studies.

Project and study setup ​

If you are new to Omics Studio, start here. These guides walk you through the initial setup steps: creating a project, uploading a dataset, and opening a study for exploration.

  • Setting Up Your First Project - A combined walkthrough covering project creation, dataset upload, and study setup in one flow. The recommended starting point for new users.
  • Creating a Study - A focused guide on creating a study within an existing project, including how to select the right files and finalize your setup.
  • Open a Study and Start Exploring - An overview of the Explorer interface and all the tools available once your study is open.

Exploration and analysis ​

Once your study is open in the Explorer, Omics Studio guides you through a structured analytical workflow. Each tool builds on the previous one, taking you from raw data to validated biological insight.

Study preferences ​

Configure identifiers, expression thresholds, statistical defaults, and annotation databases that apply across all analyses in your study. It is an easy way to keep your analysis focus consistent.

Expression view ​

The Expression View gives you a clear picture of your data before downstream interpretation.

  • Total Identification Overview - Assess how many features were detected across samples and evaluate data completeness.
  • Principal Component Analysis - Visualize sample clustering, batch effects, and biological grouping through interactive PCA plots.
  • Summed Abundance Calculation - Compare total signal levels across conditions to spot systemic differences before diving into feature-level changes.
  • Relative Expression - Examine fold changes and feature-level patterns across samples and conditions.

Statistics view ​

  • Statistical Analysis - Identify significant features using volcano plots, dot plots, and interactive thresholding with support for multiple testing correction.

Enrichment analysis ​

  • Over-Representation Analysis (ORA) - Test whether biological pathways or processes are over-represented in your list of significant features. Includes a step-by-step guide to the ORA wizard and how to interpret bar charts, dot plots, and result tables.
  • Gene Set Enrichment Analysis (GSEA) - Evaluate coordinated pathway-level shifts across a ranked feature list. Includes guidance on setting thresholds, selecting databases, and reading normalized enrichment scores.

Query UniProt, Reactome, and the Human Protein Atlas directly from your workspace to retrieve functional, structural, and expression annotations for your features.

My lists ​

Create, manage, and export custom lists of identifiers. Lists can be used to focus enrichment analyses on a specific subset of features and shared with collaborators via export.

A Note on supported data types ​

Omics Studio supports proteomics, transcriptomics, and metabolomics data. These can be combined into multiomics studies.

If you have questions about a specific workflow or run into an issue not covered here, reach out to the Omics Studio team directly.