Introduction

Visualization differential testing is a grouped boxplot with significance annotation for differential testing results visualization.

The visualization application allows visualizing the significantly different taxonomy from kingdom to species by changing the setting. You can set the threshold of significance (default: p-value < 0.05, annotated with "*"; p-value < 0.005, annotated with "**") and interactively adjust the parameters of the graph, such as the range of the axis, shape of boxplot, edit labels and box width.

Currently, only comparisons of two groups are acceptable.

If you have the raw profiling table of samples without differential testing analysis, you can use differential testing module.

If you want to visualize your processed results, you can upload the following inputs to interactively visualize online:

Input Files

1. Profiling tables (TSV file)

The file contains the relative abundance of samples in the taxonomy you want to show in the graph.

• header/column names: Samples ID separated with tab.

• row names: Taxonomy names.

2. Group info (TSV file)

The group information of samples to participate in the analysis, only exactly two groups are allowed now.

• header
  

• rows
  sample ID and the group information for the corresponding sample.

3. P values (TSV file) (optional)

Display Interactions

• Tooltips
  Hover on the box, and the info tooltips will show.

• Draggable Lengend
  Drag lengend to adjust its position.

• Editable Y-axis Label
  Double-click the label on the Y-axis to edit the label.

• Download
  Click the Download Chart button to generate the graph in the SVG format.

Editor Functions

• Files

  • Manage Files: checklist of files uploaded previously, where you can delete or download the files.
  • Upload: upload files. Note that the duplicated file name will be alerted and given a random postfix.
  • Choose: choose files uploaded previously.

• Data

  • Taxonomic Rank: select the taxonomic rank of the data to display.
  • Range lower bound: edit the minimum of the value range.
  • Range upper bound: edit the maximum of the value range.
  • P First Cutoff: Enter a value as the first cutoff value of P.
  • P Second Cutoff: Enter a value as the second cutoff value of P.

• Settings

  • Plot Height: input a value to adjust the height of the plot.
  • Plot Margin(y): input a value less than 0.1 to adjust the margin of the plot.
  • Box Width: input a value to adjust the width of the box.
  • Outliers: Check to display outliers.
    
  • P annotation: Check to display P annotation.
  • Background axises: Check to display background axises.

Manual version=1.0, written by Dr. JIANG Yiqi and Ms. WANG Yanfei on 2022-02-01.

Manual version=1.1, updated by Dr. JIANG Yiqi on 2022-04-19.