This tool allows you to map your metabolome data on the metabolic network of your organism of interest, and gives you the list of perturbed reporter pathways as an output

This tool allows you to map your transcriptome data on the metabolic network of your organism of interest using the classical approach, and gives you the list of perturbed reporter pathways as an output

This tool allows you to map your transcriptome data on the metabolic network of your organism of interest, and gives you the list of perturbed reporter metabolites as an output. It uses the approach introduced by Patil and Nielsen in 2005.

HOME BUTTON
Clicking this button will return you to the homepage

TUTORIAL
Contains the documentation and tutorial on how to use the tools

FAQ (FREQUENTLY ASKED QUESTIONS)
Contains the most frequently asked questions regarding the tool and the answers to the questions

GUEST BUTTON
Clicking this button will log you in as a guest. You will be able to use all features of the tools. However, your results will not be saved after you leave the website.

LOG IN BUTTON
Clicking this button will redirect you to login page

SIGN UP BUTTON
Clicking this button will redirect you to the registration page to open an account

The screenshot of the output text file is given above:
The file has three columns. The first column gives pathway names in alphabetical order. All the pathways associated with the reactions are listed here, without any significance-based filtering. The second column is the number of metabolites associated with the corresponding pathways. The last column gives significance scores for the pathways in terms of p-values. We recommend the users to open the file in a spreadsheet program, and rank the pathways from the lowest p-value to the highest.
The list shows that pathways from lipid and nucleotide metabolisms are the highest-affected metabolic pathways in Alzheimer’s Disease.
We prefer to not to list the pathways based on the significance intentionally. The user would want to perform multiple analyses with the same metabolic network. In this way, all the output files will have the same order of pathways, and it will be easy for the user to compare the pathways across different analyses in terms of significance.

To register an account, you need to click the Sign-Up button located in the right top corner of the screen, then you will be asked to fill in the sign-up form. In the form, you will be asked to enter your username, email address, password, your first and your last name. Once you’re done filling out the form you will be directed to the Tools page.

When you log in using your account or as a guest user, you will be directed to the tool selection view page. In this page, you can select the tool that you want to analyse your data with. Currently, there are four tools available for use, ranging from Reporter Metabolite Analysis to different forms of Reporter Pathway Analysis.

This tool allows you to map your transcriptome data on the metabolic network of your organism of interest using the novel approach by Çakır et al. (2015), and gives you the list of perturbed reporter pathways as an output

After clicking “Use Sample Files”, the user can assign a name to the analysis using the “Results” box. If no name is assigned, then an automatic name that include the date and time of the analylsis will be assigned.
If the user wants to use p-values from his/her own transcriptome/proteome data, he/she can use “choose file” button to select and upload the text file that includes the gene names and p-values in two-column tab-delimited format. The gene name format in the p-value data file must also be specified through the interface. Two options are available: Entrez Gene ID and Gene Symbol.
The next step is to click on “Proceed” button, which will run the analysis. The analysis time takes less than one minute most of the time. The user should switch to “Results” menu from the menu on the left. There, the analysis is presented in a single line, with the assigned name and the date for the analysis. “Download” column allows the users to download the output file. If the button on the “Download” column is red, this means the output file is not ready. If it is blue, then by right-clicking on the blue button, and selecting “save the link as”, the users can download the output file in tab delimited text format.

In order to use the tool, either you need to register an account or you can use the tool as a guest user. Registering an account will allow you to see your old data and results from your previous uses of the web tool. If you’re already registered, you can click the Log In button located on the right top corner of the homepage. You will then be directed to the tools view. Clicking any of the tools will direct you to the input page where you need to provide the input files or you can use the sample data provided on the site. Once you introduce the input files you will be able to run the tool.

INPUT DESCRIPTION:
RESULT NAME (optional):
You can give a name to your analysis. When it is left blank, it will be named using the date and time of the analysis you are about to perform.

p-VALUES:
The p-value file is a file of p-values the user derived from transcriptome data analysis (or metabolome in the case of Mx-RPAm tool). The p-value file must be in an mx2 format where the first column includes m gene names, and the second column includes corresponding p-values. The file should include p-values of all available genes, not only the ones below a certain p-value cut-off value.

NETWORK:
The network file should be a file that contains four columns. The first column will be reaction names, the second column the reaction itself (with all substrates and products separated by “//”), the third column the gene names (again multiple genes separated by “//”), and the fourth column the associated pathway names (again multiple pathways separated by “//”). This file can be obtained from sites/databases such as BioCyc. In order to help the users, we provide metabolic networks of ten most commonly used organisms, derived from BioCyc. These networks are accessible when the user selects “I will use the default network”.

SELECT THE SAMPLE FILE FOR ANALYSIS
All four tools in ReporterPathways Web Tool have very similar inputs and outputs. Therefore, the example dataset will focus on the use of Metabolite-Centric Reporter Pathway Analysis from Transcriptome Data (Tx-RPAm). The comparison of the results with the traditional Reaction-Centric approach (RPAr) will also be made at the end of this tutorial.
To analyze the example dataset by yourself, please select the tool Tx-RPAm from the Tools menu, and select “Use Sample Files” in the bottom-left of the page. This will automatically upload the input p-value data and will select Human Metabolic Network as input.
As it is shown in the figure above, after clicking “Use Sample Files”, the users can also download the corresponding dataset file, which includes gene symbols in the first column and their t-test based p-values in the second column. The file includes 20589 lines. The ReporterPathways Web Tool check the input files, and in case there are multiple entries for a gene (due to multiple-probes issues in microarray data), it keeps the one with lowest p-value for further analysis.

THE DATASET:
The example dataset is the transcriptomic analysis of patients with Alzheimer’s Disease and healthy controls (REF). The dataset is available in Gene Expression Omnibus website, with a GSE ID of GSE26927 (link). The dataset was also analyzed by Çakır (2015), the article that demonstrated the superiority of metabolite-centric approach over reaction-centric approach. Please read the paper for the detailed analysis of the analysis results. The patient transcriptome data was compared with the healthy control data using t-test, and p-values were calculated.

THE NETWORK:
Clicking “Use Sample Files” automatically selects “Homo Sapiens” as default metabolic network, which was obtained from HumanCyc Database.