SOCR EduMaterials AnalysesCommandLineVolume2PairedSamples Wilcoxon RankSum
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Analyses Command-Line - Volume-based 2-Paired Samples Wilcoxon Rank-Sum Test
This page includes the information on how to access the Two-Paired Samples Wilcoxon Rank-Sum Test library for the purpose of computing VOLUME/IMAGE analyses. Access is provided via shell-based command-line interface on local machines. More information about other SOCR Analyses command-line interfaces is available here.
Introduction
In addition to the graphical user interfaces, via a web-browser, all SOCR Analyses allow command-line shell execution on local systems.
General Usage
- Get the latest SOCR JAR files from the SOCR page (http://socr.ucla.edu/htmls/jars/).
- The command-line interface to SOCR Analyses generally uses EXAMPLE 1 from the list of example data files for the corresponding analysis.
- All Input files are ASCII (see examples within each of the specific analyses).
- a -h flag at the end of the command-line indicates that the first row in all ASCII input data files is a HEADER row (so it's not interpreted as data)
- Number of variables can be indicated at the end (after -h flag). If no number of variables is specified, 3 is set as default.
Two-Paired Samples Wilcoxon Rank-Sum Test Usage
- Generic Setting:
java -cp /ifs/ccb/CCB_SW_Tools/others/Statistics/SOCR_Statistics/bin/SOCR_core.jar:/ifs/ccb/CCB_SW_Tools/others/Statistics/SOCR_Statistics/bin/SOCR_plugin.jar edu.ucla.stat.SOCR.analyses.command.volume.Volume_2PairedSamples_Wilcoxon_RankSum_test -dm DesignMatrix.txt -h -regressors [name=Label1,Label2] -dim Zmax Ymax XMax [-p filename] [-t filename] -data_type [0,1,2,3,4] -byteorder little
- Options:
- -help: print usage
- -dm [DesignMatrix.txt]: specify a tab-separated text file containing the design matrix. Note: Be careful with the construction of the design matrix ... The dm matrix file may need to be imported as an excel spreadsheet, first, and then recopied back to text edit using a PC/Windows machine. Mac and other platforms may introduce hidden characters (e.g., tab/return keys). So if you get an error like
Beginning the stat analyses ... VolumeMultipleRegression Error!!!!!!!!!!!!!!
, then please review your Design Matrix file. - -mask [Mask-volume.img]: specify a mask-volume (0 or 1 intensities) restricting the voxels, where the regression models are computed (optional), 1 Unsigned-Byte Analyze format volume of the same dimensions as the data (intensity spectrum [0:255], all intensities >0 are consuiderd part of the mask and processed)
- -h: DesignMatrix contains a header (first row)
- -regressors [name=Label1,Label2]: specify which column/variable should be used and what 2 values within this column discriminate the 2 (paired) groups!
- -dim Zmax Ymax XMax: specify the dimension-sizes (for 2D images use ZMax=1, for 1D, Zmax=Y_Max=1
- -p [PValue_Filename]: output the p-value volume (enter only the base of the filename)
- -t [Wstat_Filename]: output the W-Statistics for the group differences (enter only the base of the filename)
- -data_type [0,1,2,3,4]: Type=0 is for Unsigned Byte, Type=1 is for Signed Byte, Type=2 is for Unsigned Short Integer, Type=3 is for Signed Short Integer and Type=4 is for 4Byte=Float Volume Input;
- -byteorder string: string is one of {big, little, other}.
- big = BIG_ENDIAN processor
- little = LITTLE_ENDIAN processor
- other = default processor (java.nio.ByteOrder.nativeOrder())
- -byteswap: (deprecated) Only enter this flag if you want the input data to be read in and byteswapped! Note that -byteswap effects : input data, mask-volume and output results!
- Memory Use: Note that for some large file sizes, you may need to request more memory form the JVM. If your data is larger than 5003 and you have 100's of volumes, then use these parameters after the initial java call (-ms1000m -mx2000m), see the example below. This requests 1-2GB or RAM memory for this process. You may need more or less memory depending on the number of volumes and dimension sizes.
- Example: Edit a new file (Volume_2PairedSamples_Wilcoxon_RankSum_test.csh) using any editor and paste this inside (make sure the file has executable permissions). Some operating systems/platforms may require variants of this (C-shell) script.
#!/bin/csh
date
java -ms500m -mx1000m -cp /ifs/ccb/CCB_SW_Tools/others/Statistics/SOCR_Statistics/bin/SOCR_core.jar:/ifs/ccb/CCB_SW_Tools/others/Statistics/SOCR_Statistics/bin/SOCR_plugin.jar edu.ucla.stat.SOCR.analyses.command.volume.Volume_2PairedSamples_Wilcoxon_RankSum_test -dm /ifs/ccb/CCB_SW_Tools/Statistics/SOCR_Statistics/SOCR_CSV_test_Scripts_Data/DM_2SamplesTtest.txt -h -regressors GENDER=1,2 -dim 220 220 220 -p /ifs/ccb/CCB_SW_Tools/Statistics/SOCR_Statistics/SOCR_CSV_test_Scripts_Data/VolumeMultipleRegressionTest/P_Value_mask_2PairedSamplesW -mask /ifs/ccb/CCB_SW_Tools/Statistics/SOCR_Statistics/SOCR_CSV_test_Scripts_Data/VolumeMultipleRegressionTest/UC_mask_final8bit.img -t /ifs/ccb/CCB_SW_Tools/Statistics/SOCR_Statistics/SOCR_CSV_test_Scripts_Data/VolumeMultipleRegressionTest/W_Value_mask_2PairedSamplesW -data_type 2 -byteorder little
date
exit
Example Input data files
The design-matrix datafile must be provided as tab-separated ASCII/text file (DM.txt). The ASCII content of each of these files should follow the syntax below. Note that the first lines in these files are column headers. This requires the "-h" flag on the command line at execution so that these first lines are interpreted as column headers. The first two columns are the Subject Identifier and filenames for the corresponding imaging volumes, respectively. Columns 3 and on store the corresponding predictor variable (covariate) values. Typically there will be between 1 and 10 covariates.
SUBJECT_ID | FILENAME | SEX | GROUP_ID | AGE | CDR | MMSE |
---|---|---|---|---|---|---|
002_S_0413 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_002_S_0413.img | 1 | 0 | 76.38 | 0 | 29 |
002_S_0559 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_002_S_0559.img | 0 | 0 | 79.37 | 0 | 30 |
002_S_0729 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_002_S_0729.img | 1 | 1 | 65.22 | 0.5 | 27 |
002_S_0954 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_002_S_0954.img | 1 | 1 | 69.42 | 0.5 | 25 |
002_S_1018 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_002_S_1018.img | 1 | 2 | 70.75 | 0.5 | 26 |
002_S_1070 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_002_S_1070.img | 0 | 1 | 73.73 | 0.5 | 25 |
002_S_1261 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_002_S_1261.img | 1 | 0 | 71.2 | 0 | 30 |
002_S_1268 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_002_S_1268.img | 0 | 1 | 82.78 | 0.5 | 28 |
002_S_1280 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_002_S_1280.img | 1 | 0 | 70.8 | 0 | 30 |
005_S_0324 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_005_S_0324.img | 1 | 1 | 75.35 | 0.5 | 24 |
005_S_0448 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_005_S_0448.img | 0 | 1 | 85.65 | 0.5 | 26 |
005_S_0553 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_005_S_0553.img | 0 | 0 | 84.76 | 0 | 30 |
005_S_0572 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_005_S_0572.img | 0 | 1 | 78.87 | 0.5 | 26 |
005_S_0602 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_005_S_0602.img | 0 | 0 | 70.87 | 0 | 29 |
005_S_0814 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_005_S_0814.img | 1 | 2 | 71.12 | 0.5 | 21 |
007_S_1206 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_007_S_1206.img | 0 | 0 | 72.98 | 0 | 29 |
007_S_1222 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_007_S_1222.img | 1 | 0 | 73.44 | 0 | 30 |
007_S_1304 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_007_S_1304.img | 1 | 2 | 74.76 | 1 | 25 |
012_S_0689 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_012_S_0689.img | 0 | 2 | 63.65 | 0.5 | 22 |
012_S_1009 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_012_S_1009.img | 0 | 0 | 75.91 | 0 | 28 |
012_S_1212 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_012_S_1212.img | 1 | 0 | 75.4 | 0 | 27 |
012_S_1292 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_012_S_1292.img | 0 | 1 | 76.31 | 0.5 | 26 |
012_S_1321 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_012_S_1321.img | 0 | 1 | 83.24 | 0.5 | 28 |
013_S_0996 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_013_S_0996.img | 1 | 2 | 90.99 | 0.5 | 26 |
013_S_1035 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_013_S_1035.img | 0 | 0 | 87.33 | 0 | 30 |
013_S_1276 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_013_S_1276.img | 1 | 0 | 71.94 | 0 | 30 |
016_S_1117 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_016_S_1117.img | 1 | 1 | 68.98 | 0.5 | 26 |
016_S_1121 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_016_S_1121.img | 1 | 1 | 56.25 | 0.5 | 24 |
016_S_1138 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_016_S_1138.img | 0 | 1 | 67.49 | 0.5 | 27 |
016_S_1149 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_016_S_1149.img | 0 | 1 | 84.44 | 0.5 | 29 |
016_S_1326 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_016_S_1326.img | 0 | 1 | 66.37 | 0.5 | 28 |
018_S_0335 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_018_S_0335.img | 1 | 2 | 83.66 | 1 | 20 |
018_S_0369 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_018_S_0369.img | 0 | 0 | 76.11 | 0 | 30 |
018_S_0406 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_018_S_0406.img | 0 | 1 | 77.87 | 0.5 | 29 |
018_S_0450 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_018_S_0450.img | 0 | 1 | 68.54 | 0.5 | 30 |
018_S_0633 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_018_S_0633.img | 0 | 2 | 83.37 | 1 | 20 |
020_S_1288 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_020_S_1288.img | 0 | 0 | 59.98 | 0 | 30 |
021_S_0332 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_021_S_0332.img | 0 | 1 | 70.03 | 0.5 | 25 |
021_S_0753 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_021_S_0753.img | 0 | 2 | 65.56 | 1 | 24 |
023_S_0030 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_023_S_0030.img | 1 | 1 | 80.04 | 0.5 | 29 |
023_S_0031 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_023_S_0031.img | 1 | 0 | 77.81 | 0 | 30 |
023_S_0058 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_023_S_0058.img | 0 | 0 | 70.2 | 0 | 30 |
023_S_0061 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_023_S_0061.img | 1 | 0 | 77.14 | 0 | 29 |
023_S_0078 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_023_S_0078.img | 1 | 1 | 76.07 | 0.5 | 24 |
023_S_0139 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_023_S_0139.img | 1 | 2 | 65.94 | 0.5 | 25 |
023_S_0331 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_023_S_0331.img | 1 | 1 | 64.66 | 0.5 | 27 |
023_S_0376 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_023_S_0376.img | 0 | 1 | 70.55 | 0.5 | 28 |
023_S_0388 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_023_S_0388.img | 0 | 1 | 71.3 | 0.5 | 25 |
023_S_0604 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_023_S_0604.img | 0 | 1 | 86.59 | 0.5 | 25 |
023_S_0613 | /ifs/adni/3T/PERMS/IVO/JACOBIANS/3T_bl_023_S_0613.img | 1 | 1 | 84.09 | 0.5 | 24 |
References
- Che, Annie, Cui, Jenny, and Dinov, Ivo (2009). SOCR Analyses: Implementation and Demonstration of a New Graphical Statistics Educational Toolkit. JSS, Vol. 30, Issue 3, Apr 2009.
- Che, A, Cui, J, and Dinov, ID (2009) SOCR Analyses – an Instructional Java Web-based Statistical Analysis Toolkit, JOLT, 5(1), 1-19, March 2009.
- Dinov, ID. Statistics Online Computational Resource, Journal of Statistical Software, Vol. 16, No. 1, 1-16, October 2006.
- Details about the Wilcoxon Signed-Rank test can be found here.
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