Omics Data Analysis Guide

This analysis guide explains the basic workflow for analyzing various types of omics data with Subio Platform, including RNA-Seq and microarray data, DNA methylation data, ChIP-chip, genomic position data derived from ChIP-Seq or ATAC-Seq, proteomics, metabolomics, and more. Each step is linked to the corresponding operations in Subio Platform.

The guide provides links to operation guides for each step of the analysis workflow, including data import, creating Series/DataSets, normalization and preprocessing, filtering, differential expression analysis (extracting genes, probes, or molecules with differences), multivariate analysis (PCA and clustering), biological interpretation (GO analysis and pathway analysis), analysis using genomic positions or sequence information, and data sharing.

If you want to experience the entire workflow using a single dataset, please see the RNA-Seq Data Analysis Tutorial. If you only need to check a specific step, select the relevant item from the analysis workflow below.

Choose the Best Starting Point for Your Goal

If you want to learn the full workflow: The RNA-Seq Data Analysis Tutorial lets you experience the workflow from FASTQ processing to normalization, visualization, differential expression analysis, and biological interpretation.
If you want to check a specific operation: Select the item you want to learn more about from the analysis workflow below. From the list of related articles, you can learn the specific operations.
If you want to consult about your own data: For those who do not have enough time or analyze data only a few times a year, we offer a data analysis service. For those who want to learn thoroughly and become able to make their own analysis decisions, we offer online training.

Subio Platform

Basic Plug-in

Advanced Plug-in

System Plug-in
Stages of Workflow		Data Analysis Service
Preparation	Create a Platform Create a Genome
Import Experimental Data	Import Experimental Data
Setting Up	Setting Up Series/DataSets
Normalization	Editing Normalization What are Processed Signals? Why do you turn signals into logrations?
Data Browsing	Viewers Venn Diagram
Data Analysis	Quality Control
Statistical Test Multivariate Analysis
Interpreting data and analysis results in the biological context. Analyzing data from Genomic Location or Sequence.
	Integrating Multi-Omics Datasets
Data Management	Data Management
	Edit/Copy Series
	Scan Genes over Series
Data Sharing	Data Sharing

Subio Platform
Basic Plug-in
Advanced Plug-in
System Plug-in

Frequently Asked Questions

Yes. This guide explains not only the operations commonly used in RNA-Seq analysis, but also how to look at the data and make analysis decisions. If you are new to RNA-Seq analysis, we recommend starting with the RNA-Seq Data Analysis Tutorial to understand the overall workflow.

Yes. From the analysis workflow, you can move to operation guides. For background concepts and practical ways to use the methods, please see the case studies. In addition, we provide a guide on using R scripts such as edgeR and DESeq2, as well as a microarray data analysis tutorial.

Yes. Subio Platform can handle multiple types of omics data, including RNA-Seq, microarray, DNA methylation, ChIP-chip, genomic position data derived from ChIP-Seq or ATAC-Seq, proteomics, and metabolomics. However, the appropriate normalization, preprocessing, and interpretation methods differ depending on the data type.