Welcome to irootlab page
irootLab is an open-source toolbox for vibrational spectroscopy data analysis in MATLAB. The project started in 2008 at Lancaster University, UK.
Downloads
Citation
If you find this software useful for you in your publication please cite the following paper:
Trevisan, J., Angelov, P.P., Scott, A.D., Carmichael, P.L. & Martin, F.L. (2013) "IRootLab: a free and open-source MATLAB toolbox for vibrational biospectroscopy data analysis". Bioinformatics 29(8), 1095-1097. doi: 10.1093/bioinformatics/btt084. http://bioinformatics.oxfordjournals.org/content/early/2013/03/12/bioinformatics.btt084.short
MATLAB code generation
irootlab is unique (to our knownledge) in its ability to generate MATLAB code as you operate on the toolbox GUIs. You can later take this auto-generated code as a basis for your own customized and/or systematic analysis.
Pipeline
irootlab provides routines in the following stages of the biospectroscopy data processing pipeline:
- Quality control
- Pre-processing
- Feature extraction
- Unsupervised clustering
- Classification
Visualization
Here are lots of different visualizations available. Here is a list of some of them:
- Scatter plots,
- Loadings plots,
- Feature histograms,
- Confusion matrices,
- Image maps,
- HTML reports,
- Decision surfaces,
- Biomarker-Location plots
- etc
Supported file types
As of today, the following file types are supported:
- Three different formats of CSV (text files);
- OPUS single spectrum files;
- OPUS image maps;
- Native .mat format.
Quick starter
- Download the most recent ZIP file from the official website and extract the file into a directory of your 2. Start MATLAB 3 Change MATLAB's "Current directory" to the one created above (which should contain a file called "startup.m")
-
In MATLAB's command line, enter
startup
The 'welcome' message shown contains links for some features (suggestion: check browse_demos)
System requirements
MATLAB
MATLAB (Windows/Linux/MacOS/etc), release >= r2007b tested
Specific features
Some routines contain "parfor" loops to speed up the process. To parallelize computation using parfor, the MATLAB Parallel Computing Toolbox (PCT) must be present. All routines that contain parfor loops can also run in serial mode without using the PCT.
Wavelet de-noising: this feature makes function calls to MATLAB Wavelet Toolbox.
Platform-specific binaries
- SVM classifier (LibSVM): LibSVM was successfully compiled for Windows 32-bit/Windows 64-bit; Linux 32-bit/64-bit.
- MySQL connector (mYm): mYm was currently compiled Windows 32-bit; Linux 32-bit/64-bit. Linux 64-bit: libmysqlclient.so.16 and libmysqlclient.so.18.
Manual
Tutorials
Here are some tutorials to take you through the steps of some possible pipelines and features.