Command-Line GingerALE
The command-line tools match the computational steps in the graphical version of GingerALE: ALE, Thresholding and Cluster Analysis. Each step requires GingerALE.jar
ALE & Testing Significance:
java -cp GingerALE.jar org.brainmap.meta.getALE2
Required parameters:
- Foci_Text, the text file of foci data to use
Optional parameters:
- -mask=Mask_Image, the NIfTI image to use as a mask
- Defaults to Talairach, More Conservative (more)
- -ale=ALE_Prefix, file name for the output NIfTI image of ALE values
- Defaults to foci name + "_ALE.nii"
- -pval=PVal_Prefix, file name for the output NIfTI image of P values
- Defaults to foci name + "_PVal.nii"
ALE Contrast:
java -cp GingerALE.jar org.brainmap.meta.getALE2Contrast
Required parameters:
- ALE_1, the thresholded ALE image of data set 1
- ALE_2, the thresholded ALE image of data set 2
- ALE_Pooled, the thresholded ALE image of combined data sets 1 & 2
Optional parameters:
- -mask=Mask_Image, the NIfTI image to use as a mask
- Defaults to Talairach, More Conservative (more)
- -out1=Set1_Output_Prefix, shortened name used in output files when referring to data set 1
- -out2=Set2_Output_Prefix, shortened name used in output files when referring to data set 2
- -foci1=Set1_Foci_Text, input foci for data set 1 (foci are usually embedded in GingerALE output images)
- -foci2=Set2_Foci_Text, input foci for data set 2
- -foci3=Pooled_Foci_Text, combined input foci for data set 1 & 2
- -nonadd, flag to change the ALE method to the non-additive method described in Turkeltaub, HBM 2011
Thresholding
java -cp GingerALE.jar org.brainmap.meta.getThreshold2
Required parameters:
- ALE_Image, the NIfTI image of ALE values from the previous step
- PVal_Image, the NIfTI image of P values from the previous step
- FDR_Value, the false discovery rate, a floating point value like 0.05
Optional parameters:
- -pID, flag to use pID in the FDR step
- -noDiagonals, flag to use more strict clustering algorithm
- -min=Min_Vol_MM, an integer value for the minimum cluster size
- Defaults to 1 mm3
- -mask=Mask_Image, the NIfTI image to use as a mask
- Defaults to Talairach, More Conservative (more)
- -thresh=Thresholded_Image_Prefix, filename for the output NIfTI image of thresholded ALE values
- Defaults to ALE_Image filename + "_thresh.nii"
- -clust=Cluster_Image_Prefix, filename for the output NIfTI image of clusters
- Defaults to ALE_Image filename + "_clust.nii"
Cluster Analysis for non-GingerALE images
Use this step to create a "cluster image" which is required in the cluster analysis step.
java -cp GingerALE.jar org.brainmap.meta.getClustersOnly
Required parameters:
- Input_Image, the thresholded NIfTI image to be clustered
- Min_Cluster, the minimum cluster size allowed in the cluster image
If you're not sure what the minimum cluster size should be, use 1 mm3 to leave all clusters in the image.
Cluster Analysis
java -cp GingerALE.jar org.brainmap.meta.getClustersStats
Required parameters:
- Foci_Text, the original text file of foci data
- Used to create experiment tables
- ALE_Image, the original or thresholded ALE values
- Used to find weighted centers and extrema
- Clust_Image, the NIfTI image of clusters from the previous step
Optional parameters:
- -mni, flag to transform locations to Talairach before looking up Talairach labels
- -limitExtrema, flag to remove local extrema from statistics
- -label=Talairach_Image, NIfTI image of Talairach labels
- Defaults to talairach.nii, which is included in GingerALE.jar like the masks
- -out=Output_Prefix, the file name prefix for text (.txt) and spreadsheet (.xls) output files
- Defaults to Foci_Text file name + "_clust"
Mask Options
Mask images and the Talairach label image are saved as NIfTI images within GingerALE.jar. The mask options are:
- Talairach, More Conservative: "new_mask_smaller.nii"
- Talairach, Less Conservative: "new_mask_bigger.nii"
- MNI, More Conservative: "Colin27_smaller.nii"
- MNI, Less Conservative: "Colin27_bigger.nii"
For example:
java -cp GingerALE.jar org.brainmap.meta.getALE2 example_foci.txt -mask=Colin27_smaller.nii
If you use BrainMap Sleuth to create your text file of foci data, and you use one of our masks, then each command-line step will double-check the reference spaces and give you a warning message if they don't match.