Welcome to Omic Integrate Analysis
README
Omic integrate analysis is a Comprehensive Online Statistics Analysis Tool for Multi-Omics and Omic-Clinical Association Analysis.
It is a cutting-edge tool designed to empower users in conducting multi-omics and omic-clinical association analysis. With its user-friendly interface and powerful features, we offer a seamless experience for researchers and analysts to unlock valuable insights from complex biological data.
1. Interactive Graphs for Exploratory Analysis:
We provides interactive graphs, including principal component analysis (PCA) graphs and volcano graphs generated through differential analysis. These graphs offer intuitive visualizations that enable users to understand patterns, identify outliers, and gain a deeper understanding of their multi-omics data.
2. Cross Omics Correlation Network:
Using the results from differential analysis and clustering analysis, we allow users to construct interactive cross omics correlation networks. These networks help visualize the relationships and interactions between different types of omics datasets, providing a holistic view of the underlying biological mechanisms and potential biomarkers.
3. Omic-Clinical Association Analysis:
OIA goes beyond exploring multi-omics data by facilitating omic-clinical association analysis. By integrating omics data with clinical information, researchers can uncover correlations and associations between molecular signatures and clinical outcomes. This analysis aids in identifying potential biomarkers or therapeutic targets for various diseases and conditions.
4. Downloading Results:
To support further analysis and reporting, OIA offers the convenience of downloading results. Users can easily export graphs, correlation networks, and association analysis results, ensuring seamless integration with other tools or platforms.
Whether you are a bioinformatician, molecular biologist, or clinician, OIA equips you with the necessary tools to conduct sophisticated multi-omics analysis and bridge the gap between omics data and clinical insights. Harness the power of this online tool to unlock the full potential of your data and drive groundbreaking discoveries in the field of precision medicine.
User guide
For detailed userguide, please click the button below.
Contact Us
Technical Support: yan.li@qlife-lab.com
Multi-omics Analysis v1.0
Methods
Volcano plot
Mfuzz results
PCA Graph
Clinical boxplot
Methods
Correlation molecules and interactive graphs
Correlation molecules and interactive graphs
Clinical-omic linear regression
User Guide
Welcome to the user guide for OIA! This guide will take you through the step-by-step process for data analysis. From "Data Loading" page to the subsequent pages for statsitics, correlation and clinic-omic calculation, this guide will provide clear instructions, and ensure a smooth user experience.
1. "Data Loading" Page:
First, select data you want to use. you can either select sample data (covid data, published and open access), or upload your own data.
If upload your data, please make sure upload a zip file, which include a folder named "data", and all files are stored in this folder, such as "Protein_identified_information.xlsx" (If you have protein data involved in your analysis, Name and format must be exactly the same, .xls extension also accepted. If you don’t have protein data, then ignore it.), "Metabolite_identified_information.xlsx", and "Lipid_identified_information.xlsx". In addition to omic data, you must provide a "compare.csv" file, which contains group information. If clinical data involved, please name it as "clinic.xlsx" and put it into "data" folder.
If you are still confused, please download our sample data at the bottom-left corner of “Data Loading” page, and make sure your uploaded file has the same contents (name of zip file doesn’t matter, everything inside zip file must have exact same name). You can also check data formats by using data preview of sample covid data, or downloading sample covid data.
After uploading your data, click “Protein”, “Metabolite”, “Lipid”, and “Clinical” checkbox listed below, to select what kind of data combination you want to use.
Next, on the right hand side, click corresponding “Protein”, “Metabolite”, “Lipid”, and “Clinical” subpage, to have a preview of data tables, and make sure data is properly uploaded and read.
All required data files are prepared at this point. Click “Statistics Analysis” button to start calculating results for “Statistics” page.
2. "Statistics" Page:
This page provides three different analysis methods. As listed, they are Differential analysis, Mfuzz analysis, PCA analysis and Clinical statistics.
If no data detected, you may see a Warning message. In this case, please go back to “Data Loading” to let the website recognize which data you are using.
Differential Analysis:
Volcano table subpage will show results calculated from “Statistics Analysis” button from “Data Loading” page.
After setting parameters for volcano plot, simply click “Plot!” button and graph will show on “Graph” subpage.
Mfuzz Analysis:
Similar to volcano plot, you can check results from “Data Loading” page, then calculate Mfuzz clusters and check table results on “Mfuzz Analysis” subpage, graph results on “Graph” subpage.
PCA analysis:
Select analyte type you want to show on the PCA graph.
Clinical statistics:
Select Clinical element and compare groups(>1) to draw boxplot.
3. "Correlation" Page:
This page will display an interactive multi-omics correlation network and associated molecule information used in the network. Results are calculated based on “Differential Analysis” and “Mfuzz Analysis” methods on “Statistics” page.
Therefore, please go to “Statistics” page and generate required tables before click any calculate buttons, otherwise will cause disconnection from the server, and you may need to start from the beginning again.
Three primary functions are distinguished in differential based analysis. As illustrated below, inputs and corresponding results enclosed with the same color. Notably, users are required to run the correlation calculation initially (depicted by the blue-boxed function) to subsequently utilize the remain two sub-functions.
4. "Clinical" page:
This page is independent from “Statistics” and “Correlation”. After select/upload your data on “Data Loading” page, you may start clinic-omic association caculation directly.
There are two independent analysis here. Analysis 1 allows user to select multiple clinical elements and one omic type.
Analysis two allows user to select one clinical element and show all molecules that satisfies filter conditions.
Click “Draw” button, and the website will do linear regression calculation, show results on “LR result” subpage on the right, and draw circle graph on “Graph” subpage.
Tips:
1. If you disconnect from the server right after you click any calculation related button, it is very possible that something goes wrong. Thinking of uploading format of uploaded files or missing required files from previous pages.
2. If you disconnet from the server when you did nothing, then check your internet connection.
3. upload size of zip cannot exceed 60M.
4. If you have any other questions when using our service, you are welcome to contact us.
About Us
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