Xia Lab - Translation

September 1, 2023

Dear Colleagues and Friends,

It has been such a pleasure to serve you over the past decades. I started my bioinformatics journey about 15 years ago, and soon realized that for most data analysis tasks, many excellent methods and algorithms exist. However, properly using them requires substantial statistical knowledge and computer programming - skills that could take years to master by very few experts (elite analytics), and are uninteresting or even distracting to many in life sciences. We felt strongly that omics data analysis should be unintimidating, pleasant and inspiring to the majority who design their experiments and generate their data.

Analytics 1.0

The web and cloud technologies have played major roles to make data analytics accessible to broad audience. Leveraging these technologies, we have implemented a series of tools integrating visualization and statistics (visual analytics) to lower the barriers to omics data analysis. These tools have been used by ~1 million researchers worldwide. However, long-term sustainabilities and supporting advanced needs have become our growing concerns due to the inherent instability of funding and personnel as an academic lab.

Analytics 2.0

We are at the dawn of revolution on data analytics. The generative AI technologies (such as ChatGPT) allow us to chat with our data (conversational analytics). An AI chatbot, further trained for omics data analysis (OmicsBot), can not only answer questions, but also help create workflows and generate custom reports. The experience of data analysis can be greatly simplified (drop your data, leave a message, and pick up your live analysis report) yet significantly improved (you can review, explore, and edit this report) with OmicsBot as co-pilot.

Analytics 3.0

To help sustain our tools, the community and to smoothly transition into AI-augmented, conversational analytics, we are happy to offer a comprehensive training and support package (see below), and invite you to join us on this exciting journey. Please sign up to indicate your interest. The scheduled launch date is 01/01/2024.

Join Us

Overview

Training Omics Data Science course
Single omics & multi-omics analysis
Online lectures + demos + hands-on practices Details

OmicsTools Pro Many enhanced features
Batch processing & larger data upload
OmicsBot support & personalized live report Details

Enterprise Solution Self-hosted solution
Dedicated training & support
Private database & custom workflows Details

Training: Omics Data Science course

Course objectives: underlying the diverse "-omics" technologies, there is a stable core of omics data analysis. After taking the course, you will
1. Develop a good knowledge of the core concepts and approaches in omics data analysis;
2. Understand the subtleties or uniqueness of common omics data analysis workflows;
3. Perform effective omics data analysis using
  - user-friendly Omics Tools (community or pro) through web interface
  - intelligent (and fun) OmicsBot through conversation!
  - the underlying R packages (only if you are familiar with R and want to get hands dirty)
Target audience: senior undergraduates, graduate students, postdoctoral fellows, PIs, researchers and clinicians who are interested in omics data analysis
Date: January - March, 2024
Delivery
- Format: online (Zoom) and in English
- Live: every Saturday morning 9:00 - 11:30 AM (New York / Montreal Time)*.
*The live session will be based on the main time zone of the attendees. All slides and recordings including lectures, lab demos, as well as short videos will be available.
Support: OmicsForum, OmicsBot, Email
Course outline: see below (click a title to see more, details will be added soon)

Week 1 - Overview (Part I)

[Objective]: To develop a good understanding of omics data generation and analysis workflow
[Lecture]: Overview of omics technologies and data analysis workflow
[Lab]: none

Week 2 - Overview (Part II)

[Objective]: To develop a good understanding of general data formats and analysis methods
[Lecture]: General concepts in experimental designs, statistics and visualization techniques
[Lab]: none

Week 3 - Transcriptomics (Part I)

[Objective]: To develop a good understanding of RNAseq workflow and common analysis methods
[Lecture]: RNAseq data analysis in model species
[Lab]: ExpressAnalyst & NetworkAnalyst

Week 4 - Transcriptomics (Part II)

[Objective]: To understand how to analysis of RNAseq data without reference genomes
[Lecture]: RNAseq data analysis for non-model species
[Lab]: ExpressAnalyst (Seq2Fun Docker)

Week 5 - Non-coding RNAs

[Objective]: To understand general workflow for microRNA data analysis and interpretation
[Lecture]: MicroRNAs, noncoding RNAs and biological networks
[Lab]: NetworkAnalyst & miRNet

Week 6 - Proteomics

[Objective]: To understand general workflow for proteomics data analysis and interpretation
[Lecture]: Proteomics data generation and analysis
[Lab]: ExpressAnalyst

Week 7 - Metabolomics (Part I)

[Objective]: To understand general workflow for analysis and interpretation of targeted metabolomics data
[Lecture]: Targeted metabolomics data analysis and interpretation
[Lab]: MetaboAnalyst

Week 8 - Metabolomics (Part II)

[Objective]: To understand general workflow for LC-MS/MS untargeted metabolomics data analysis
[Lecture]: Untargeted metabolomics data analysis and interpretation
[Lab]: MetaboAnalyst (MetaboAnalystR4 Docker)

Week 9 - Microbiome (Part I)

[Objective]: To understand key concepts and current practices of maker gene data analysis
[Lecture]: Marker gene profiling
[Lab]: MicrobiomeAnalyst (DADA2 Docker)

Week 10 - Microbiome (Part II)

[Objective]: To understand key concepts and current practices of shotgun metagenomics data analysis
[Lecture]: Shotgun metagenomics
[Lab]: MicrobiomeAnalyst (Kraken2 Docker)

Week 11 - Multi-omics (Part I)

[Objective]: To understand general concepts and approaches for network-based multi-omics integration
[Lecture]: Knowledge-driven approaches
[Lab]: OmicsNet

Week 12 - Multi-omics (Part II)

[Objective]: To understand general concepts of common multivariate approaches for multi-omics integration
[Lecture]: Data-driven approaches (dimensionality reduction and clustering)
[Lab]: OmicsAnalyst

Miscellaneous Topics for Lectures and Labs

These topics will be offered throughout the year based on the common interests and perceived needs from subscribed users. Some examples are given below:

How to create personalized workflow for batch processing
How to work with a live analysis report to manuscript for publication
Tips to interact with OmicsBot
Topics based on your feedback ....

OmicsTools Pro

The Pro versions address the key needs that are difficult to meet by the Community versions due to limited resources. Main differences are listed below:

Key Features	Community Version	Pro Version	Notes
Batch processing	--	✓
Workflow creation	--	✓
Project management	--	✓
Resumable analysis	--	✓
Enhanced graphics	--	✓
Default data filtering	Always on	Optional
Troubleshooting support	Community-based	Within 48 hours
New feature request	Community	Prioritized
Databases options	Community / public	More options	Based on user requests and costs of commercial databases
OmicsBot support	--	✓	Continuously updated using public documents, slides, transcripts, forum Q/As, and manual tuning
Large file upload	Default	2 X default + manual support	Pro users come with manual upload support (max 3 times or 300 samples)
Analysis report	+/- (static)	+++++ (live)	A live document (within 1-yr), supporting interaction, updating, and creating publication figures

Enterprise Solution

We are aware of the important needs from companies or large research groups with large data generation or privacy concerns. They are best addressed using on premise or private cloud solution. We provide support for local installation of Pro versions of our OmicsTools. It is also possible to implement custom workflows or use private / commercial databases. Please contact us.

Pre-registration Form