LISA twosample test (vlisa_twosample)

The program vlisa_twosample performs a two-sample t-test on two groups of images including a correction for multiple comparisons using the LISA algorithm [2018_Lohmann]. For ease of use, the input images may be specified using wildcards as shown below. The output is a map thresholded such that FDR < alpha for every voxel. The default is alpha=0.05. The resulting image shows (1-FDR) so that larger values indicate higher significance.

The type of test can be specified using the option ‘-test’. The default (‘-test pooled’) is a twosample t-test based on pooled variance. The welch test (‘-test welch’) is a t-test applicable for unequal variances or unequal sample sizes. The paired test (‘-test paired’) can be used if the samples are paired. If wildcards are used to specify the input files, it is important to make sure that the pairs match.

Note that a region-of-interest mask is required. The mask should exclude non-brain voxels, and it may cover the entire brain. In the example below, the mask is in the file “braimmask.nii”.

vlisa_twosample -in1 images1_*.v -in2 images2_*.v -mask brainmask.nii -out result.v -test welch

Note that this program also accepts input images in Nifti format (”.nii” or “.nii.gz”), but the output is always in vista format. To convert the output to the Nifti format, use the following command:

vnifti -in result.v -out result.nii

Parameters of ‘vlisa_twosample’:

-help

Prints usage information.

-in1

Input files 1.

-in2

Input files 2.

-out

Output file.

-alpha

FDR significance level. Default: 0.05

-perm

Number of permutations. Default: 5000

-mask

Region of interest mask.

-test

Type of test to be performed [ pooled | paired | welch ]. Default: pooled

-seed

Seed for random number generation. Default: 99402622

-radius

Bilateral parameter (radius in voxels). Default: 2

-rvar

Bilateral parameter (radiometric). Default: 2.0

-svar

Bilateral parameter (spatial). Default: 2

-filteriterations

Bilateral parameter (number of iterations). Default: 2

-cleanup

Whether to remove isolated voxels. Default: true

-j

Number of processors to use, ‘0’ to use all. Default: 0

References

[2018_Lohmann]

Lohmann G., Stelzer J., Lacosse E., Kumar V.J., Mueller K., Kuehn E., Grodd W., Scheffler K. (2018). LISA improves statistical analysis for fMRI. Nature Communications 9:4014. (link)