Skip to content

loosolab/admire

master
Switch branches/tags

Name already in use

A tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Are you sure you want to create this branch?
Code

ADMIRE - Analysis of DNA methylation in genomic regions

ADMIRE is a semi-automatic analysis pipeline and visualization tool for Infinium HumanMethylation450K and Infinium MethylationEpic assays.

Use ADMIRE online: https://bioinformatics.mpi-bn.mpg.de

Features

  • Automatic filtering and normalization
  • Statistical testing and multiple testing correction
  • Supports arbitrary number of samples and sample groups
  • Differential methylation analysis on pre-calculated and individual genomic regions
  • Provides ready-to-plug-in files for genome browsers (like IGV)
  • Provides publication-ready figures for the most differentially methylated regions
  • Performs gene set enrichment analysis on predefined and individual gene sets

Documentation

We have a extensive documentation with a use case available here.

Installation and Command-line usage

We recommend to install prerequisites using the conda package manager. Make sure to have conda installed, e.g. via

  • Miniconda
    • download the Miniconda installer for Python 3
    • run bash Miniconda3-latest-Linux-x86_64.sh to install Miniconda
    • Answer the question "Do you wish the installer to prepend the Miniconda install location to PATH in your /home/.../.bashrc ?" with yes OR do PATH=dir/to/miniconda3:$PATH after installation process

Clone the ADMIRE repository and populate an environment with all prerequisites:

$ git clone https://github.molgen.mpg.de/loosolab/admire
$ conda env create -f admire/environment.yaml
$ export PATH=$PATH:dir/to/admire/src

Every time you intent to use ADMIRE, make sure the environment is activated:

$ source activate admire
$ admire -h
Usage: admire [options]

Available options:
-c | Comma separated sample definition file (SampleSheet.csv)
-s | Tab separated sample definition file (design.txt)
-z | Compressed input of idat files (requires -c).
-e | Create quality control report in PDF
-r | Region file in bed format (regions.bed), use multiple -r parameters to calculate for multiple region files
-p | Detection p-value to exclude probes prior to analysis (0.01)
-t | Exclude probes where more than t% samples failed according to the detection p-value. (0.4)
-n | Normalization method (fn,swan,noob,illumina,raw,quantile)
-b | In case of functional normalization, skip noob background correction step
-d | In case of noob or functional normalization, skip dye correction step
-f | In case of quantile normalization, skip fixing outliers prior to analysis
-l | In case of quantile normalization, label samples as bad if their median signals are below a given value (10.5)
-m | In case of quantile normalization, remove bad samples
-q | Q-value cutoff for multiple testing correction (0.05)
-i | Render advanced plots for the best i regions (20)
-g | Gene set file for enrichment analysis, use multiple -g parameters to calculate enrichment over many gene sets
-o | tar-gz compress output into file given
-h | shows this help message
-v | shows version information

Options -c and -s are mutually exclusive.

How to cite?

Please cite Preussner J, Bayer J, Kuenne C and Looso M. ADMIRE: ADMIRE: analysis and visualization of differential methylation in genomic regions using the Infinium HumanMethylation450 Assay. Epigenetics & Chromatin (2015), doi:10.1186/s13072-015-0045-1, when using admire in your work.

Contribute

  • Issue Tracker: github.molgen.mpg.de.com/loosolab/admire/issues
  • Source Code: github.molgen.mpg.de.com/loosolab/admire

Support

If you are having issues, please feel free to send an e-mail to Jens Preußner (jens.preussner@mpi-bn.mpg.de).

License

The project is licensed under the MIT license.