MetaboAnalyst

Please upload your data

This module supports functional analysis of untargeted metabolomics data generated from high-resolution mass spectrometry (HRMS). The basic assumption is that putative annotation at individual compound level can collectively predict changes at functional levels as defined by metabolite sets or pathways. This is because changes at group level rely on "collective behavior" which is more tolerant to random errors in compound annotation as demonstrated by Li et al. To use this approach,

The input peak list or peak table must contain the complete data, not just significant data - we need the complete data to estimate the null model (background);
[Required] Feature or peak names must be their numeric mass (m/z) values for putative annotation;
[Optional] You can also provide retention time (RT) to further improve peak annotation

Try our example datasets

Data

Format

Description

IBD

Three columns (m.z, p.value, t.score)

Peak list data (12 pediatric IBD patients and 12 controls) obtained using a Q-Exactive Plus Orbitrap (negative ion mode) from the Integrative Human Microbiome Project (iHMP).

IBD 2

Four columns (m.z, p.value, t.score, rt)

Same as above

Dendritic Cells

One column (m.z ranked by p.value)

Peak list data obtained from human monocyte-derived dendritic cells stimulated by yellow fever vaccine strain (YF17D), collected using an Orbitrap LC-MS (positive ion mode).

Macrophages

Four columns (m.z, p.value, t.score, mode)

Peak list from mice alveolar macrophages, with or without mTOR knock-out (details), collected using an Orbitrap LC-MS (C18 negative ion mode and HILIC positive ion mode)

Upload a peak intensity table

Try our example datasets

Data

Format

Description

Immune Cell

Generic peak intensity table (no retention time)

Example peak intensity table from KO experiment of dendritic cells and epithelial cells treated in DSS.

Covid-19

Peak intensity table with retention time

Peak intensity table of COVID-19 global metabolomics study with over 9,000 peaks.

Malaria

Small intensity table with retention time

Peak table of a Malaria metabolomics study with 5,113 peaks.

Try our example datasets

Data

Format

Description

Download

Human Islet

Peak List: Three columns (mz, rt, p.value);
Compound List: InchiKeys IDs, Marked with peak index;

Data lists (5 Low-glucose and 5 High-glucose) obtained using LC-MS/MS (ESI+).

Peaks Compounds

COVID-19

Peak List: Five columns (mz, rt, t.score, p.value, mode);
Compound List: InchiKeys, same length;

Data lists (6 COVID-19 patients and 6 Controls) obtained using LC-MS/MS (ESI+ and ESI- modes) from Mahmoud S. et al.

Peaks Compounds

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The Molecular Weight Tolerance refers to the ppm used for matching m/z features to compounds.

When primary ions are enforced, mz matches to compounds must contain a primary ion to be considered valid. Primary ions considered are 'M+H[1+]', 'M+Na[1+]', 'M-H2O+H[1+]', 'M-H[-]', 'M-2H[2-]', 'M-H2O-H[-]', 'M+H [1+]', 'M+Na [1+]', 'M-H2O+H [1+]', 'M-H [1-]', 'M-2H [2-]', and 'M-H2O-H [1-]'. Note this is only used in Version 2.

Mummichog requires p.values and GSEA requires t.scores for peak ranking purposes. You can upload your data in a tab-delimited text file (.txt) format. For single mode, for Version 1, a complete dataset contains three columns with specific names - m.z, p.value, and t.score. While for Version 2, a complete dataset contains four columns with specific names - m.z, p.value, t.score and r.t. For mixed mode, for Versions 1 and 2, your last column ("mode") must indicate whether the m.z's are positive or negative. Please see below for an example (mixed mode). Note that you can use fold change values instead of t.scores.

m.z             p.value                 t.score     mode
304.2979	1.0153771115e-10	14.7179316191   negative
177.1024	1.61647122234e-10	14.2666000207   negative
345.0277	1.71651483296e-10	-14.2091952724  positive
491.0325	1.83359804763e-10	-14.1463478332  positive
258.0048	2.16851438688e-10	-13.987636322   positive
483.1205	2.21510885538e-10	-13.9676335843  positive
694.9937	2.81091747637e-10	-13.7451720928  negative
270.9767	3.26786548614e-10	13.6060704804   positive

The Molecular Weight Tolerance refers to the ppm used for matching m/z features to compounds.

Use Generic if the data is formatted as a generic peak table. Note that if retention times are included, they must be formatted with two underscores between the m/z and retention time:

Sample              VT_150821_065.cdf       VT_150821_083.cdf
Group               healthy                 healthy
376.3808__0.93      119306.8796991          181692.0970101
135.1020__0.98      196722.430865503        337410.3473859
374.8815__0.59      409570.3544994          514658.461539
86.0603__2.15       1087129.323483          2038021.41222857
142.9618__1.35      638567.840138999        549900.622946999
129.0663__1.97      21840649.9192819        4237026.934809

The MS Peaks to Pathways module also supports the output directly from MZmine.

The Molecular Weight Tolerance refers to the ppm used for matching m/z features to compounds.

m.z             p.value                 t.score     mode
304.2979	1.0153771115e-10	14.7179316191   negative
177.1024	1.61647122234e-10	14.2666000207   negative
345.0277	1.71651483296e-10	-14.2091952724  positive
491.0325	1.83359804763e-10	-14.1463478332  positive
258.0048	2.16851438688e-10	-13.987636322   positive
483.1205	2.21510885538e-10	-13.9676335843  positive
694.9937	2.81091747637e-10	-13.7451720928  negative
270.9767	3.26786548614e-10	13.6060704804   positive

You must upload a text file which containing the potential chemical annotation for the MS peaks.

There are two formats for compound lists:

A compounds list generated by Spectra Processing Module directly. This option contains the same rows of compounds as the peak list (See 2nd example, COVID-19 dataset);
A compound list containing multiple rows whose number is different from the peak list. But, the first column must be the row index corresponding to the peak list. (See 1st example, Human Islet dataset).

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