Help
We provide a comprehensive User manual for TraceMetrix, which users can download for detailed guidance. The Help section describes the data requirements and format specifications for each analysis step and also offers demo data for practice. Click "Download" to obtain demo data for each step. If you encounter any issues during the analysis, please refer to this section for assistance.
If you are still unsure how to resolve a problem, you can download the support form, fill in the required information, and email it to the system administrator at chenwei2019@sibs.ac.cn.
Step File Input File Requirements Parameters Input Demo
Preprocessing
XCMS

(case 1)

 Data File (.mzXML/.mzML)
  1. MS data must be .mzXML/.mzML
  2. All MS data must be in a folder
  • Data File：mzXML
  • Sample File：sample.file.csv
  • Data Type：Open(mzXML)
  • Polarity：positive
  • Instrument：mzXML
  • Parameter：Agilent_6530
 Download
Sample File (sample.info.csv)
  1. Column names must include file.name, sample.names
  2. file.name must be include MS file(s)’name
XCMS

(case 2)

 Data File(.vendor)
  1. Different raw data from vendors
  2. Our platform surport two raw data formats(.wiff and .d)
  3. file.name must be include MS file(s)’name
  • Data File：Agilen
  • Sample File：sample.file.csv
  • Data Type：Vendor
  • Polarity：positive
  • Instrument：Agilent_6530(.d)
  • Parameter：Agilent_6530
 Download
Sample File (sample.info.csv)
  1. Column names must include: file.name, sample.names
  2. file.name must be include MS file(s)’name
Annotation

(case 1)

 ms1 file
  1. Column names must include :compound.id、mz、rt
  • MS level：MS1(mz)
  • ms1file：featureData.csv
  • polarity：positive
  • ms1MatchPPM：30
  • Cadicate Num：3
  • Column：hilic
  • AnnotationType：ms1
Annotation

(case 2)

 ms1 file
  1. Column names must include :compound.id、mz、rt
  • MS level：MS2(mz)
  • ms1file：featureData.csv
  • ms2file：ms2 file(s)
  • polarity：positive
  • ms1MatchPPM：30
  • Cadicate Num：3
  • Column：hilic
  • AnnotationType：ms2
ms2 file(s)
  1. MS file(s) convert to .mgf format as input
Data Clean
Background Removal

(case 1)

 Data File (data.csv)
  1. Column names must include：compound.id
  • Data File：data.csv
  • Sample File：sample_info.csv
  • Method：Blank
  • Fold：3
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Sample File (sample_info.csv)
  1. Column names must include sample.names、classes
  2. Classes must include “Blank” and “Sample”
Background Removal

(case 2)

 Data File (data.csv)
  1. Column names must include：compound.id
  • Data File：data.csv
  • Sample File：sample_info.csv
  • Method：Blank
  • Fold：3
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Sample File (sample_info.csv)
  1. Column names must include sample.names、classes
  2. Classes must include “Dilution” and “Sample”
  3. Dilution can input file or input information online
  4. Dilution file Colname be：sample.names,order, dilution
Missing value Processing Data File (data.csv)
  1. Column names must include：compound.id
  • Data File：data.csv
  • Sample File：sample_info.csv
  • Method：median
  • NA Ratio：0.2
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Sample File (sample_info.csv)
  1. Column names must include sample.names、classes
Normalization

(case 1)

 Data File (data.csv)
  1. Column names must include：compound.id
  2. Data without NA value
  • Data File：data.csv
  • Sample File：sample_info.csv
  • Method：median
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Sample File (sample_info.csv)
  1. Column names must include sample.names、classes
Normalization

(case 2)

 Data File (data.csv)
  1. Column names must include：compound.id
  2. Data without NA value
  • Data File：data.csv
  • Sample File：sample_info.csv
  • Method：QC_SVR
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Sample File (sample_info.csv)
  1. Column names must include sample.names,classes,injection.order
  2. classes must have QC and Sample
Filtered by RSD Data File (data.csv)
  1. Column names must include：compound.id
  2. Data without NA value
  • Data File：data.csv
  • Sample File：sample_info.csv
  • RSD：30
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Sample File (sample_info.csv)
  1. Column names must include sample.names,classes
Data Integration Data File (data.csv)
  1. Column names must include：compound.id
  2. Data without NA value
  • Data File：data.csv
  • Sample File：sample_info.csv
  • Method：median
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Sample File (sample_info.csv)
  1. Column names must include sample.names,classes,batch
  2. classes names must include QC or Sample
  3. batch must be two or more batches
Removal Outliers Data File (data.csv)
  1. Column names must include：compound.id
  2. Data without NA value
  • Data File：data.csv
  • Sample File：sample_info.csv
  • CI：0.95
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Sample File (sample_info.csv)
  1. Column names must include sample.names,classes
Statistic
Two-sample Comparison (case 1)

 Data File (data.csv)
  1. Column names must include：compound.id
  2. Data without NA value
  • Data File：data.csv
  • Sample File：sample_info.csv
  • Paired：FALSE
  • Method：Auto
  • Alternative：Two.side
  • Group Colunm：group_test
  • Group:2A 2B、2B 2A、3A 3B、 4A 4B、5A 5B
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Sample File (sample_info.csv)
  1. Column names must include sample.names
  2. You need to choose column with group information
Two-sample Comparison

(case 2)

 Data File (data.csv)
  1. Column names must include：compound.id
  2. Data without NA value
  • Data File：data.csv
  • Sample File：sample_info.csv
  • Paired：TRUE
  • Method：Auto
  • Alternative：Two.side
  • Group Colunm：group_test
  • Group:2A 2B
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Sample File (sample_info.csv)
  1. Column names must include sample.names,label
  2. You need to choose column with group information
  3. Group only contain two groups
  4. Label of the two groups’information correspond one-to-one
Multi-sample Comparison Data File (data.csv)
  1. Column names must include：compound.id
  2. Data without NA value
  • Data File：data.csv
  • Sample File：sample_info.csv
  • Method：Auto
  • Alternative：Two.side
  • Group Colunm：group_test
  • Group:2A, 2B, 3A, 3B, 4A, 4B,5A,5B
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Sample File (sample_info.csv)
  1. Column names must include sample.names,label
  2. You need to choose column with group information
  3. Group only contain three or more groups
PCA Data File (data.csv)
  1. Column names must include：compound.id
  2. Data without NA value
  • Data File：data.csv
  • Sample File：sample_info.csv
  • Method：pareto
  • Group Colunm：group_test
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Sample File (sample_info.csv)
  1. Column names must include sample.names
  2. You need to choose column with group information from column
PLS-DA Data File (data.csv)
  1. Column names must include：compound.id
  2. Data without NA value
  • Data File：data.csv
  • Sample File：sample_info.csv
  • Method：pareto
  • Group Colunm：group_test
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Sample File (sample_info.csv)
  1. Column names must include sample.names
  2. You need to choose column with group information from column
OPLS-DA Data File (data.csv)
  1. Column names must include：compound.id
  2. Data without NA value
  • Data File：data.csv
  • Sample File：sample_info.csv
  • Method：pareto
  • Group Colunm：group_test
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Sample File (sample_info.csv)
  1. Column names must include sample.names
  2. You need to choose column with group information from column
Correction Analysis

(case 1)

 Data File (data1.csv)
  1. The first cloumn must be name
  2. Other colmun contain you want to deal data information
  • Data File：data1.csv
  • Method：Pearson
  • Alternative：Two.side
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Correction Analysis

(case 2)

 Data File1 (data1.csv)
  1. The first cloumn must be name
  2. Other colmun contain you want to deal data information
  • Data File1：data1.csv
  • Data File2：data2.csv
  • Method：Pearson
  • Alternative：Two.side
 Download
Data File2 (data2.csv)
Linear Regression

(case 1)

 Data File (data.csv)
  1. File must contain independent variable(s) or must be a dependent variable
  • Data File：data.csv
  • Dependent Variable：Murder
  • Independent Variable：Population,Illiteracy,Income,Frost
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Linear Regression

(case 2)

 Data File (data.csv)
  1. File must contain independent variable(s) or must be a dependent variable
  2. File also need include interaction and Categorical variable(s)
  3. Categorical variable(s) can choose one or more and the order variable must be 1,2,3…, the unorder variable A,B,C…
  • Data File：data.csv
  • Dependent Variable：Murder
  • Independent Variable：Population,Illiteracy,Income,Frost
  • categorical variable(s)：unorder1,unorder2,order1,order2
  • Interaction ：Population:Illiteracy,Illiteracy:Income
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Logistic regression

(case 1)

 Data File (data.csv)
  1. File must contain independent variable(s) or must be a dependent variable
  • Data File：data.csv
  • Dependent Variable：Murders
  • Independent Variable：Sepal.Width,Sepal.Length,Petal.Length,Petal.Width
  • Method：polytomous
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Logistic regression

(case 2)

 Data File (data.csv)
  1. File must contain independent variable(s) or must be a dependent variable
  2. File also need include interaction and Categorical variable(s)
  3. Categorical variable(s) can choose one or more and the order variable must be 1,2,3…, the unorder variable A,B,C…
  • Data File：data.csv
  • Dependent Variable：Murders
  • Independent Variable：Sepal.Width,Sepal.Length,Petal.Length,Petal.Width
  • Method:ordinal
  • categorical variable(s)：unorder1,unorder2,order1,order2
  • Correction ：unorder1,unorder2,order1,order2,test
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COX Proportional Hazard Regression

(case 1)

 Data File (data.csv)
  1. Data File must be include time , events , independent variables
  2. You need to choose this column from your file
  • Data File：data.csv
  • Time：time
  • Event：status
  • Independent variable：sex,ph.ecog
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COX Proportional Hazard Regression

(case 2)

 Data File (data.csv)
  • Data File：data.csv
  • Time：time
  • Event：status
  • Independent variable：sex,ph.ecog
  • OrderC：ph.ecog
 Download
Kaplan-Meier Analysis

(case 1)

 Data File (data.csv)
  1. 1.Data File must be include time , events
  2. 2.You need to choose this column from your file
  • Data File：data.csv
  • Time：time
  • Event：status
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Kaplan-Meier Analysis

(case 2)

 Data File (data.csv)
  1. 1.Data File must be include time,events,groups column
  2. 2.You need to choose this column from your file
  • Data File：data.csv
  • Time：time
  • Event：status
  • Groups：sex
 Download
Kaplan-Meier Analysis

(case 2)

 (metabolites’name or metabolites’ID)
  1. Only input a type of metabolites
  • Type：Compound Name
  • Database：kegg
  • Species：homo
Quantitative Enrichment Analysis

(case 1)

 Data File (data.csv)
  1. The First Column must be name, and subsequent columns’ name is the metabolite’name or ID
  • Type：Compound Name
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  • Database：kegg
  • Species：homo
Quantitative Enrichment Analysis

(case 2)

 Data File (data.csv)
  1. The First Column must be name, and subsequent columns’ name is the metabolite’name or ID
  • Type：Compound Name
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  • Method：median
  • NA Ratio：0.2
Sample File
  1. Column names must include : sample.names,classes
  • Method：median
  • Database：kegg
  • Species：homo
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