The simplest form of the analysis is in a python session (or script):
import MRS.api as mrs
G = mrs.GABA(file_name)
G.fit_gaba()
Where file_name is a variable which includes the full path to a nifti file containing data organized as specified in ‘Organizing your data‘. Once these lines are executed, the object G will now contain several attributes that quantify the relative abundance of GABA and creatine, which can then be used in further analysis.
We provide several examples of data analysis as IPython notebooks. These can be viewed and downloaded here.
A command line interface (CLI) is available to conduct basic analysis of MRS data stored in a nifti files following the specification in ‘Organizing your data‘.
To run this interface run the following line in a shell session:
mrs-analyze ~/.mrs_data/12_1_PROBE_MEGA_L_Occ.nii.gz --plot True --out_file ~/tmp/mrs.csv
Where you can replace the full-path to the input file with the file you are analyzing. This command will analyze the data, produce a plot with the sum spectra (echo on + echo off), the difference spectra (echo on - echo off), and the fit of the creatine and GABA models to these data, together with their calculated areas under the curves. If you do not want to produce plots, exclude the –plot True. In addition, it would save a file under ~/tmp/mrs.csv with the frequency bands (in ppm) and the spectra (echo on, echo off and difference) as a function of frequency band. You can use this file for further analysis (e.g. using other modeling techniques).
To explore all the options in the CLI run the following line in a shell session:
mrs-analyze
This will print a list of the input options to the CLI.