Browsing an MTP set

An MTP set consists of two or more MTPs, representing a group of microbiome samples. Once an MTP set is created, it can be browsed by the <MTP set browser>. Here, we will open a set called “seniors” which contains 68 MTPs with the same and different tags (For example, all MTPs has “senior” tag, but only some are labeled with “Cdiff+”, “antibiotics+” or”antibiotics-“.

Opening the MTP set browser

Open an MTP set

  1. All MTP sets are available here. You can generate an unlimited number of sets. Click the tab to bring out the list of your MTP sets.
  2. Open the desired MTP set.
  3. Edit the MTP set name of the set
  4. Delete the set if you want.

There are four menus in the MTP Set Browser.

Top menus of the MTP Set Browser


MTP List

In this page, the list of MTPs in the set is displayed.

Listing MTPs in an MTP set

  1. Name of the MTP set
  2. Taxonomic database version used for the MTP pipeline. MTPs of the different versions of databases cannot be included in the same set.
  3. Select tag(s) to quickly filter MTPs.
  4. Open an MTP if you want to explore single MTP.


In this page, three submenus (tabs) are provided: <Stacked bar>, <Double pie>, and <Selected taxa>

Stacked bar

Stacked bar visualization of an MTP set

  1. You can change the option for normalization. You can normalize or correct the compositional data using re-sampled reads or gene copy number [Learn more].
  2. You can export the data as an Excel spreadsheet file.
  3. All reads that are present in minor quantity are classified as ETC. You can change the cut-off for the ETC reads here.
  4. You can select the taxonomic rank to visualize.
  5. Color legends are located here for the stacked bar chart.
  6. Parameters applied are given here.
  7. An image file can be downloaded here.

Double pie

The double pie chart is a special, interactive chart that simultaneously displays compositions of two taxonomic ranks in the sample time.

Double pie chart of an MTP set

  1. Select the taxonomic rank of the inner circle.
  2. Select the taxonomic rank of the outer circle.
  3. Click [Apply] to make the change effective.
  4. This is the outer circle for the averaged composition profiles of all MTPs in the set. Bring the cursor to highlight the taxon (pie).
  5. This is the inner circle.
  6. These are the double pie chart of individual MTPs.

 Selected taxa

In this page, the composition of a selected taxon can be shown as a box plot. In addition, predefined sets are provided to quickly browse the compositional information.

Selected human gut taxa in an MTP set

  1. Predefined taxonomic groups are listed here. We will expand them in future.
  2. Here, “human gut taxa” is selected to list all important taxa of the human gut microbiome.
  3. Box plots are shown here [Learn more].
  4. By clicking this, box plots will be re-drawn with the outliers.
  5. An image file can be downloaded here.

Box plot of the relative abundance of a selected taxon in an MTP set

  1. Enter a name of taxon here to display. You can input any taxon from phylum to species.
  2. In this example, “Vibrio” is entered, and the result shows that there are very little Vibrio species found in this MTP set.
  3. An image file can be downloaded here.


In this menu, general information and indices explaining alpha-diversity are provided. Basically, alpha-diversity indices are calculated for each MTPs. In this visualization, all of those values are shown side by side for you to quickly compare.

Alpha-diversity indices of an MTP set

  1. Various alpha-diversity indices are given in this page.
  2. In this screenshot, individual rarefaction curves of 69 MTPs are shown in a chart.
  3. Download an image of this chart.


Beta-diversity analytics allows us to understand the relationship of microbial communities stored in multiple MTPs. At present, these are presented as either ordination analysis or hierarchical clustering. The first step for the beta-diversity is to calculate the distances among the set of MTPs. In the ordination analysis, the data reduction of the distance matrix is performed by the principal coordinate analysis (PCoA) to give the major axes of principal components (PCs). In EzBioCloud 16S-based MTP app, we take either the first two or three PCs to draw the scattergrams. The same distance matrix can be used to carry out the hierarchical clustering using UPMGA algorithm (Unweighted Pair Group Method with Arithmetic Mean). There are several different algorithms to calculate beta-diversity distances and pertaining parameters. EzBioCloud 16S-based MTP app allows instant and interactive navigation of data space using optimized user interface.

PCoA (2D)

PCoA-based 2-dimensional ordination scattergram

  1. Select a beta-diversity distance metric.
  2. Decide if you want to include data up to the species or genus level.
  3. Some sequencing reads are not taxonomically identified at the species or higher level. These reads are assigned in the unclassified group (labeled as *_uc). You can choose to either include or exclude these data. If most of the reads were assigned to the species, which is most cases in human microbiome analysis of EzBioCloud, this option will have a very small impact on the outcome of beta-diversity.
  4. Time to maximize your tags here. Select a tag to quickly display the sub-set of MTPs in your MTP set. In this screenshot, the tag “Antobiotic+” was selected to highlight the MTPs (human subjects) who took the antibiotics.
  5. Changing or selecting a combination of tags (e.g. “Antibiotic+” and “CDiff+”) will highlight the picked MTPs (Clostridium difficile infection patients who took antibiotics) in this 2D plot.
  6. An image file can be downloaded here.
  7. Download the list of three PCoA axes as a excel format file.

PCoA (3D)

This is the same scattergram as the above 2D one, except that it takes an additional, first principle component axis.

PCoA-based 3-dimensional ordination scattergram

  1. Use the left click+mouse to rotate the figure.
  2. Bring the cursor will highlight additional menus on this visualization.

UPGMA clustering

Unlike ordination diagrams, hierarchical clustering forces each MTPs (samples) to be grouped in a strictly hierarchical way. Again, you can change the distance algorithms and associated parameters. The chart should be called a dendrogram, not a phylogenetic tree.

A dendrogram resulted from a UPMGA clustering

  1. Enlarge or reduce the dendrogram.
  2. Download the dendrogram as an image.
  3. Download the dendrogram as a Newick format file which can be read by other tree viewing software tools.

The EzBioCloud team / Last edited on Feb. 8, 2019