Informatics and Statistics for Metabolomics 2018
Welcome
Informatics and Statistics for Metabolomics.
The course schedule can be found here.
Pre-readings, pre-work, and laptop setup instructions can be found here.
We are using Google Classroom for discussion. Join the Class at https://classroom.google.com, select the “+” symbol in the upper right corner, click on “Join Class” and enter the class code provided to you.
The full course notes are available as a single PDF.
Class photo
Day 1
Welcome
Ann Meyer
Module 1: Introduction to Metabolomics
David Wishart
Module 2: Metabolite Identification and Annotation
David Wishart
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NMR and Bayesil.
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GC-MS and GCMS.
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LC-MS and XCMS in R. If R doesn’t work, try XCMS online.
Data Set and Results Files:
NMR:
GC-Autofit:
Download this file
LC-MS:
Raw datasets (raw.zip files)
Converted datasets (mzxml.zip files)
XCMS using R (results files)
XCMS online (results files)
Cleaned Diffreport
Normalized Results
Unnormalized Results
Links:
- MetaboMiner
- rNMR
- BMRB Peaks Server
- BATMAN
- Bayesil
- Golm Database
- NIST/AMDIS
- CFM-ID
- Metlin
- MetFusion
- Adduct Table
- MZedDB
- MWTWIN
- HighChem
- 7GR Software
- MyCompoundID
Module 3: Databases for Chemical, Spectral, and Biological Data
David Wishart
Links:
- HMDB
- DrugBank
- METLIN
- PubChem
- ChEBI
- ChemSpider
- SDBS
- BioMagResBank
- MMCD
- MassBank
- BMRB
- NMRShiftDB
- SMPDB
- KEGG
- Reactome
- BioCyc
Day 2
Module 4: Backgrounder in Statistics
Jeff Xia
Module 5: MetaboAnalyst
Jeff Xia
Data Input:
Critical: before uploading your data, perform a sanity check:
- It is a data table separated by comma (.csv) or tab (.txt);
- Three types of labels: feature names, sample names and group labels (must directly follow sample names);
- All measurements should be numerical values (empty for missing values);
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For details and screenshot instructions, click here
- You may have downloaded the NMR results .zip folder yesterday. You will need the .csv file from the .zip folder. NMR results.zip (Bayesil output - need to remove annotations lines starting with #, keep one type of ID - name/HMDB ID)
- Cleaned GCMS results (Auto-GCMS output that has been cleaned for you)
- Normalized LCMS csv
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Module 6: Future of Metabolomics
David Wishart
Thank you for attending the Analysis of Metagenomic Data workshop! Help us make this workshop better by filling out our survey