biobakery / biobakery / wiki / lefse — Bitbucket

LEfSe Tutorial

LEfSe (Linear discriminant analysis Effect Size) determines the features (organisms, clades, operational taxonomic units, genes, or functions) most likely to explain differences between classes by coupling standard tests for statistical significance with additional tests encoding biological consistency and effect relevance.

LEfSe is available as a Galaxy module, a Homebrew formula, a Docker image, and included in bioBakery (VM and cloud). For additional information, please refer to the LEfSe paper.

We provide support for LEfSe users. Please join our Google group designated specifically for LEfSe users. Feel free to post any questions on the google group by posting directly or emailing [e-mail].

---

Contents

• Overview
• 1. LEfSe (Galaxy)
• 2. LEfSe (Brew/Docker/VM)
• 3. Visualization
• Notes

---

Overview

The following figure shows LEfSe's workflow.

---

1. LEfSe (Galaxy)

For the purpose of this tutorial we will be using a sample input file (hmp_small_aerobiosis.txt).

• Go to the Huttenhower Galaxy Server: http://huttenhower.sph.harvard.edu/galaxy/
• Click on the Get Data -> Upload File link on the left pane and upload the demo file (hmp_small_aerobiosis.txt). You can do this by clicking on the Browse button, selecting the demo file, and then pressing the Start button. Select the format tabular.

• Click on the LEfSe -> Format Data for LEfSe link on the left pane, and select the specific rows for Class, Subclass and Subjects in your file, and press the Execute button as shown below:

• Click on the LEfSe -> LDA Effect Size (LEfSe) link on the left pane, and select parameter values according to your analysis requirements. Press Execute, when done.

• Once complete, you may now plot the LEfSe results, by click on the LEfSe -> Plot LEfSe Results link on the left pane, and press the Execute button as shown below:

• This will produce a figure, that will look like as shown below (To visualize the figure in the browser, click on the Eye symbol against the resulting output in the right pane).

• To plot a cladogram of your results, you may click on the Plot Cladogram link on the left pane, and press the Execute button when ready.

• This action will produce a cladogram, as shown below:

You may also plot differential features or one feature. Please refer to the LEfSe documentation for more information.

---

2. LEfSe (Brew/Docker/VM)

LEfSe can be installed with Homebrew or run from a Docker image. Please note, if you are using bioBakery (Vagrant VM or cloud) you do not need to install LEfSe because the tool and its dependencies are already installed.

Install with Homebrew: $ brew install biobakery/biobakery/lefse

Install with Docker: $ docker run -it biobakery/lefse bash

If you would like to install from source, refer to the LEfSe documentation (Step 4).

For the purpose of this tutorial we will be using a sample input file: hmp_small_aerobiosis.txt depicting the general format of the input file (two rows of metadata, one row of sample names and the corresponding microbial abundance table).

• Run the following command to format the input file (hmp_small_aerobiosis.txt). This will generate a file (hmp_aerobiosis_small.in).

$ format_input.py hmp_aerobiosis_small.txt hmp_aerobiosis_small.in -c 1 -s 2 -u 3 -o 1000000

• Run the following command, passing the file generated in the previous step as input. This will generate a file (hmp_aerobiosis_small.res) consisting of LEfSe analysis results.

$ run_lefse.py hmp_aerobiosis_small.in hmp_aerobiosis_small.res

---

3. Visualization

To visualize the results, LEfSe provides a couple of options. For all the options you will need the output from run_lefse.py (in this case: hmp_aerobiosis_small.res)

• To plot the results of the LEfSe analysis generated from the previous step, run the following command.

$ plot_res.py hmp_aerobiosis_small.res hmp_aerobiosis_small.png

• This will produce a figure as shown below:

• You may also choose to visualize the results in a Cladogram. Run the following command to generate the Cladogram figure. This will use the LEfSe results file generated previously.

$ plot_cladogram.py hmp_aerobiosis_small.res hmp_aerobiosis_small.cladogram.png --format png

• The resulting figure is shown below.

---

Notes

For information on more options, and further analyses, please refer to Step 4 in the MetaPhlAn Pipeline Tutorials.