IMS_project

Before using this package:

There are several depend libraries in R and Matlab that are needed. Please install these packages.

• R:
  1. MALDIquant
  2. MALDIquantForeign
  3. MassSpecWavelet
  4. mzR
• MATLAB:
  • For MOLDL
    1. glmnet
    2. SLEP
    3. minFunc
    4. Ipopt
  • For sparse-NNMF
    1. [The NMF MATLAB Toolbox] (https://sites.google.com/site/nmftool/)

Using this package:

There are several folders in this project that are relevant to the work in ISMB2015.

• Bruker_files_conversion
• dictionary_learning_ADMM
• dictionary_learning_analysis
• dictionary_learning_syntheticData
• example
• testFunctions
• utility

Preprocessing:

1. The input data, whaterever intruments of IMS is using, should be converted into the mzML format. This is an open XML-based format so our program can process it. To covert from the Bruker proprietary file format to the mzML, One can use msconvert. The details of how to do this is in Bruker_files_conversion\commands.txt. If you need the mzML file in the example, you can download them from: https://drive.google.com/open?id=0B06g-wOYKgZ8ald2VGtKUnJIYVE and https://drive.google.com/open?id=0B06g-wOYKgZ8amtnRmNLRnE1MDA.
2. Then we use Bruker_files_conversion\usePreprocessing.R to read mzML file and do peak picking. Again, the details of how to do this is in Bruker_files_conversion\commands.txt.
3. The steps afterwards are shown in exp_100831_348_136_12_40hr_0_1XLB_LN_basicSettings_v2.m and exp_100831_348_136_12_40hr_0_1XLB_LP_basicSettings_v2.m

Main program:

The example of using it can be seem in the file expScript_20150401.m under the folder "example\realExp_100831_348_136_12_40hr_0-1XLB_LN" or "example\realExp_100831_348_136_12_40hr_0-1XLB_LP".