Easy as pie: just click on Add a new organism in the organism overview, give it a name and submit. That’s it.
There are two possible ways: either via the organism selection or directly in the plotting area.
You can upload a new pathway as SVG:
Here you can see, how to export pathways drawn in MS Powerpoint:
Earlier versions of Powerpoint and other programs that does not offer SVG export can be converted via the third-party tool Convertio.
You can also add an existing pathway to another organism:
Click on in the plotting interface to edit the selected pathway and add new plot boxes and identifiers.
See this short example to know more about the file format and identifiers.
You can easily change the plot type and visualize your data again:
This short tutorial shows how the range influences your plots:
Here you can see how to remove or change loaded datasets:
Welcome to MetaboMAPS beta! Thank you for your support. Here you can see a list of features that will be included during the beta phase:
The organism selection can be found at the start page and by clicking on Organisms in the navigation bar.
You see a list of all available organisms. A blue circle at the right side shows the amount of available pathway maps for each organism. By default, organisms without metabolic maps are hidden. Before adding a new organism, please check whether its already present by unchecking Show only organisms with pathway maps.
It is possible to filter the list by entering parts of the organism name into the input field at the top. This search is case-sensitive!
A new organism can be added by clicking on + (on the bottom end of the list). This feature is only available for logged-in users.
The pathway selection can be found by clicking on Pathways in the navigation bar.
You see a list of all available pathway maps, which are open for public use. A blue circle at the right side shows the amount of organisms that are assigned to this pathway. Clicking on the pathway name will open a box with additional information, e.g. a preview, the pathway description, references, and all assigned organisms. You can visit the pathway page by selecting an organism. Your own private pathway maps are marked with .
The pathway accession is always shown in the following format: P61O9
The primary function of this accession is to link to pathways and organisms, e.g. you can copy the accession code for the use in your publication or to share your pathways with your coworkers. You can search for a metabolic pathway with your accession in our search.
To link to for example to the TCA cycle from Homo sapiens, use the following url:
Note: Your data are loaded locally into your browser and are never saved on our server!
After selecting an organism, you are redirected to the Plotting area. Here you see the interaction section on the left and the pathway map on the right.
1 Overview: The title shows the organism. A dropdown allows the selection of a metabolic pathway. Underneath is a button group (A-D) that gives further tools and information: A: You can add a new pathway to this organism by clicking on . B: You can edit the currently selected pathway by clicking on . C: You get a list of all identifiers that are assigned to this pathway by clicking on . D: You get further information on the currently selected pathway by clicking on , e.g. the description, a publication link, the editor and contact information, as well as the pathway accession.
2 Visualize data: You can load your own data sets and visualize them directly on metabolic pathways. MetaboMAPS distinguishes between reaction- and metabolite-dependant data, so that both can be visualized simuoltaneously but with different settings. A: load your data set as CSV format with semicolons as delimiters. The first row (header) is used to draw the legends. The first column must contain identifiers to connect the data with related plot boxes. Which identifiers can be used for the current map, can be seen in the Editing section of by clicking on the pathway name or by clicking on . See section Edit existing pathways to read more about plot boxes and identifiers. You can find test files in our example. B: Select a plot type from the list. Currently, heat maps, bar charts, line charts, pie charts, and circle indicators are supported. The selected plot type influences the color scale, e.g. heat maps and circle indicators (which represent values via colors) use a sequential color scale. Thus, categorical colors are not possible. In contrast, bar charts and pie charts always use discrete color scales, where not the value influences the color, but the position on the chart. C: you can select a color scale from the list. The selected color scale is shown below. D: you can specify a range for your data. If nothing is set, MetaboMAPS will use the minimum and maximum value of your data set. Defining the zero value is for example important, when you plot a heat map with only one value (e.g. log fold transcription changes). When you set a zero value, data points above and below are shown as arrows in the respective direction.
3 Metabolites: you can apply the same settings as above for metabolite-associated data.
4 Legends: legends are drawn when you plot your data. Until this point, the legend card is invisible. A seperate legend is drawn for metabolite and reaction associated data. There are color and categorical legends, depending on the plot type. You can download and add them to your pathway maps.
5 Interact with the map: You can download the map (including all plots) either as SVG or PNG.
The map itself can be navigated by drag and drop and mouse-wheel zoom.
The currently supported plot types are:
A grouped bar chart will look like this:
It is created by selecting Bar Chart (grouped) as plot type. Please notice, that the actual grouping of your data sets requires a special format of your header! The following example shows, how underscores are used to seperate the group from the condition:
metabolome;t0_pyruvate;t0_alanine;t0_glutamate;t1_pyruvate;t1_alanine;t1_glutamate citrate;100;80;100;80;100;80 fumarate;96;46;22;75;78;44 ...
In this way, we retrieve two groups (t0 and t0) containing each three conditions (pyruvate, alanine, and glutamate). Conclusively, the legend will look like this:
In this example, a randomized dataset was visualized on the TCA cycle of Homo sapiens. Both, transcriptome and metabolome data, are present as CSV files that can be downloaded for test purposes. We simulate the comparison of five different conditions (condition 1 to 5) with each other. This could be the growth on different substrates, different time points after some event, ...
The transcriptome dataset represents log2-fold changes for each condition compared with condition 1. In this case we have values reaching from -4 to 4. The ideal plot type is a heatmap, which can also represent negative values. Because the color represents the value in heat maps, one should select a diverging color scheme (e.g. red > blue), where zero values get a neutral color. It is further possible to set the range of the color scale, otherwise the minimum and maximum of your dataset is used. Missing values in heat maps are simply omitted (see 22.214.171.124 in the example image). Here you see how the example dataset looks like:
transcriptome;cond2/cond1;cond3/cond1;cond4/cond1;cond5/cond1 126.96.36.199;1.6373;-0.4676;1.9557;1.1629 188.8.131.52;1.2822;3.4548;1.7405;1.4302 184.108.40.206;3.8356;2.5053;2.4721;0.0066 220.127.116.11;3.1788;0.5758;3.2314;0.1287 18.104.22.168;-3.2978;;-1.024;-1.7283 22.214.171.1246;0.1044;1.3471;2.172;1.6541 126.96.36.199;-1.7583;-3.6425;-1.0489;-1.7944 188.8.131.52;-0.6426;0.4599;0.6528;0.4703
The metabolome dataset represents metabolite concentrations for each condition, ranging from 0 to 100. The ideal plot type is a classical bar chart. Since a discrete color scale is applied to bar charts, a radial color scheme would be best. Missing values in bar charts are marked with * (see malate and succinyl-CoA in the example image). In our example, we used the popular viridis color scheme. Here you see how the example dataset looks like:
metabolome;condition1;condition2;condition3;condition4;condition5 citrate;7;38;56;37;65 isocitrate;2;33;37;17;96 2-oxoglutarate;72;71;56;78;26 succinyl-coa;7;79;;5;22 succinate;27;70;92;68;14 fumarate;96;46;0;75;78 malate;79;20;;91;36 oxaloacetate;4;21;24;91;78 acetyl-coa;6;66;37;88;88 coenzyme_a;69;92;43;91;4
By clicking on Plot, all datasets are visualized on the metabolic map:
Note: This section is only available for logged-in users!
After selecting an organism, a pathway can be added by clicking on + (next to the pathway selection). Then you have two options for adding a pathway:
After adding a pathway to the organism, you will be redirected to the editing page, for the addition af plot boxes and identifiers.
Browse your file system and upload your own pathway in SVG format. You will see a preview of your pathway. Note: The pathway is not uploaded yet! You must fill the form and click on Submit to upload it.
After the preview is shown, you must name the pathway. Additionally, you can add a description to your pathway and link the publication to receive credits for your work. In the end, you must select if the uploaded pathway shall be visible by everyone or kept private (e.g. if the map is yet unpublished). You can change this later: when your pathway map is published, you can add the link to the publication and make it public.
You can select an existing pathway from another organism and add it to the current organism. After selecting a pathway map from the dropdown menu, you will see a preview. The form below will show all available pathway information. Note: You cannot change the pathway information when selecting an existing pathway map. If you are the editor of this pathway, you can change these information in the Edit existing pathways section.
Note: This section is only available for logged-in users!
To edit an existing pathway, click on (next to the pathway selection). You will be redirected to the Pathway editing page, where you can add the so-called plot boxes and assign identifiers. The plot boxes are only visible in the editing area. You can zoom into the pathway map by using the mouse wheel and navigate by drag and drop on the background.
Plot boxes and identifiers are the essentials of MetaboMAPS. A new plot box is added to the selected pathway maps by right click. The newly created box will have a red border, meaning that no identifiers are assigned yet. You can move all boxes by drag and drop and select them by left click. When a plot box is selected, you will see a form on the right side, where identifiers can be assigned. We distinguish between general identifiers that are organism-independant (e.g. EC numbers, metabolite names...) and organism-specific identifiers (e.g. locus tags, GIs...). Identifiers from other organisms are shown for reference, but cannot be modified. Make sure to use underscores (_) instead of spaces inside of identifiers. Furthermore you can define if the plot box belongs to a metabolite or to a reaction. Metabolite boxes are marked with a dashed border. Once you save the identifier, the plot box border will turn green. You can remove selected plot boxes by clicking on the .
If the plot boxes are to small or to large for the pathway map, you can easily adjust the size of all boxes by clicking on /
After all plot boxes are drawn and all identifiers are assigned, you can save the pathway by clicking on Save Pathway. The page will be reloaded when the save was successful. Afterwards you can add other plot boxes or click on Visit Pathway to see the result and visualize your data on the map.
When you are the editor of this pathway map, you are also allowed to change the pathway information, such as pathway name, description and publication link. You can also change the visibility. Note: The pathway informations are not organism-dependant, meaning that they are changed for all organisms using this pathway.
14.01.2020: Pathway Sharing
13.01.2020: Pathway Versioning
08.01.2020: Improvement of the blot box editor
07.01.2020: Added pathway categories
06.01.2020: Minor update (thanks to the feedback of Tobias!)
17.12.2019: Minor update with new plot type
10.12.2019: Minor update (thanks to the feedback of Sabine!)
25.11.2019: Minor update
19.11.2019: Minor update
13.11.2019: First release