Informatics and Statistics for Metabolomics 2020

Welcome

[Welcome] to Informatics and Statistics for Metabolomics 2020.

The course schedule can be found here

Meet your faculty! here

Pre-Workshop Materials

Pre-workshop Lecture

Pre-readings and pre-work can be found here here.
It is in your best interest to complete these before the workshop.

Class Photo

Class Photo

Day 1

Welcome

Rachade Hmamouchi

Module 1: Introduction to Metabolomics

David Wishart

Access Module 1’s lecture here.

Module 2: Metabolite Identification and Annotation

David Wishart

Access Module 2’s lecture slides here —- Updated slides here

## Module 2 LAB: Metabolite Identification and Annotation

Access Module 2’s lab practical slides here —- Updated slides here

Follow the instructions for Module 2’s lab here

Briefly, the lab will go over the following pre-processing workflows:

  1. NMR and Bayesil.

  2. GC-MS and GC-Autofit.

  3. LC-MS and MetaboAnalyst.

Data Set and Results Files:

NMR (Bayesil):

Example datasets (zipped files) for Lab2

GCMS (GC-Autofit):

Example datasets (mzXML.zip files)

Download this file: GC_autofit.zip

LC-MS (MetaboAnalyst):

Example datasets (mzXML.zip files)

Download this file: ibd_data_cbw2020_updated.zip

Spectra processing with MetaboAnalyst (example result files)

- Peak Table

- Input for MS Peaks to Path

- Finished MetaboAnalyst spectral processing job

Module 3: Databases for Chemical, Spectral, and Biological Data

David Wishart

Access Module 3’s lecture here

(Optional) Lab Practical: Spectral Processing and Functional Analysis with MetaboAnalyst(R)

Jeff Xia

This dataset was acquired using an UPLC-Q/E-ESI- in negative ionization mode. The 10 samples (per group) are a subset of a much larger study from Lloyd-Price et al., and include fecal samples from patients with Crohn’s Disease (CD, 4), healthy controls (4), and two quality controls. The metadata contains more sample information. Using the MetaboAnalyst web service or MetaboAnalystR, process one of the example datasets below.

Full Metadata here

Larger example datasets (mzXML.zip files) (Optional!! Intended only for Monday’s evening session)

Download example data here

Following spectra processing, use the lab practical and follow Protocol 9 on the resulting peak table to gain functional insights from the untargeted metabolomics data.

Day 2

Module 4: Backgrounder in Statistics

Jeff Xia

Access Module 4’s lecture here — Updated slides here

Module 5: MetaboAnalyst

Jeff Xia

Access Module 5’s lecture here

To understand how to use MetaboAnalyst, please follow the 11 protocols in this lab practical.

Data Input:

Critical: Before uploading your data, perform a sanity check:

  • Verify that it is a data table separated by commas (.csv) or tabs (.txt);
  • For concentration/peak intensity tables: three types of labels should be present; feature names, sample names and group labels (must directly follow sample names);
  • All measurements should be numerical values (empty for missing values);

  • For details and screenshot instructions, click here

  • Data 1 Metabolomic concentration table of 77 urine samples from cancer patients and healthy controls. Can be used for Protocols 1-5.
  • Data 2 Peak intensity table of 48 fecal samples from pediatric inflammatory bowel disease patients and healthy controls. Can be used for Protocols 1-3.
  • Data 3 Peak list of 48 fecal samples from pediatric inflammatory bowel disease patients and healthy controls. Used for Protocol 9.
  • Data 4 Full peak intensity table of stool samples of CD (n = 266), UC (n = 144), and non-IBD (n = 135) obtained from Lloyd-Price et al.. Full metadata here. Can be used for Protocols 1-3.

Module 6: Future of Metabolomics

David Wishart

Access Module 6’s lecture here

Survey

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