Difference between revisions of "SOCR EduMaterials AnalysesCommandLineFDR Correction"
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==[[SOCR_EduMaterials_AnalysesCommandLine | Analyses Command-Line]] - False Discovery Rate (FDR) Corection== | ==[[SOCR_EduMaterials_AnalysesCommandLine | Analyses Command-Line]] - False Discovery Rate (FDR) Corection== | ||
− | This page includes the information on how to use the [http://socr.ucla.edu/htmls/SOCR_Analyses.html SOCR Analyses] library for the purpose of computing the ''False Discovery Rate (FDR)'' correction for multiple testing in volumetric | + | This page includes the information on how to use the [http://socr.ucla.edu/htmls/SOCR_Analyses.html SOCR Analyses] library for the purpose of computing the ''False Discovery Rate (FDR)'' correction for multiple testing in volumetric and shape-based analyses. Access is provided via shell-based command-line interface on local machines. More information about [[SOCR_EduMaterials_AnalysesCommandLine | other SOCR Analyses command-line interfaces is available here]]. |
− | |||
=== Introduction=== | === Introduction=== | ||
− | In addition to the graphical user interfaces, via a web-browser, all [http://socr.ucla.edu/htmls/SOCR_Analyses.html SOCR Analyses] allow command-line shell execution on local systems. | + | In addition to the graphical user interfaces, via a web-browser, all [http://socr.ucla.edu/htmls/SOCR_Analyses.html SOCR Analyses] allow command-line shell execution on local systems. |
+ | |||
+ | In a nutshell, FDR is a statistical method used in multiple hypothesis testing to correct the probability values for the effect of multiple comparisons. FDR controls the expected proportion of incorrectly rejected null hypotheses (i.e., FDR controls the type I error, <math>\alpha</math>). For example, if 1000 observations were experimentally predicted to be different, and a maximum FDR for these observations was ''q=0.10'', then 100 of these observations would be expected to be false positives. The ''q''-value is the FDR analogue of the p-value. The q-value of an individual hypothesis test is the minimum FDR at which the test may be called significant. One can directly estimate q-values or alternatively, fix a level at which to control the FDR. See the [[SOCR_EduMaterials_AnalysesCommandLineFDR_Correction#Supplementary_information | references below]] for more information on FDR. | ||
+ | |||
+ | Suppose we perform m simultaneous hypothesis tests with a common procedure (test). For any given procedure, we classify the results as shown below. Only these values are observed m, D, and N. The other ones are unknown. Let T=true, F=False, D=Discovery, and N=Nondiscovery. FDR provides a protocol that balances the | ||
+ | competing demands of [[AP_Statistics_Curriculum_2007_Hypothesis_Basics |sensitivity and specificity of the test]]. | ||
+ | |||
+ | <center> | ||
+ | {| class="wikitable" | ||
+ | |- | ||
+ | ! ||Ho Retained || Ho Rejected || Total | ||
+ | |- | ||
+ | | Ho True || TN || FD || To | ||
+ | |- | ||
+ | | Ho False || FN || TD || T1 | ||
+ | |- | ||
+ | | Total || N || D || m | ||
+ | |} | ||
+ | </center> | ||
+ | |||
+ | Then, FDR guarantees that the [[AP_Statistics_Curriculum_2007_Distrib_MeanVar |expectation]] of the relative-false-discovery (falsely-rejecting Ho, when it's true) is <math>E \left ( {FD \over D}\right ) \leq \alpha</math>. | ||
+ | |||
+ | The [[SOCR]] analysis implementation of FDR is based on [http://bioinformatics.oxfordjournals.org/cgi/content/full/21/12/2921 this article], see [[SOCR_EduMaterials_AnalysesCommandLineFDR_Correction#References|references below]]. | ||
===FDR Usage=== | ===FDR Usage=== | ||
* Get the latest SOCR JAR files from the SOCR page (http://socr.ucla.edu/htmls/jars/). | * Get the latest SOCR JAR files from the SOCR page (http://socr.ucla.edu/htmls/jars/). | ||
* Generic Setting: | * Generic Setting: | ||
− | <code> 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.Test_FDR -input | + | <code> 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.Test_FDR -input Input_PValues_File -output Output_PValuesCorrected_File [-type type] [-fdr_rate q] -number integer -byteorder string</code> |
*Options: | *Options: | ||
Line 16: | Line 37: | ||
** -v: verbose mode (will print all input/output data in standard output stream. | ** -v: verbose mode (will print all input/output data in standard output stream. | ||
** -input [InputFileName]: specify a file-name for an ASCII or binary file containing the raw p-values. | ** -input [InputFileName]: specify a file-name for an ASCII or binary file containing the raw p-values. | ||
− | ** -output [OutputFileName]: specify a file-name for the | + | ** -output [OutputFileName]: specify a file-name for the corresponding output file that will contain the FDR-corrected p-values. |
− | ** -type [0,1]: Type=0 is for ASCII text input file type, Type=1 is for binary 4Byte=Float Input file; | + | ** -type [0,1]: Type=0 is for ASCII text input file type, Type=1 is for binary 4Byte=Float Input file. |
+ | ** -mask [Mask-filename]: specify a mask-file (0 or 1 intensities) restricting the voxels where the p-values are FDR corrected (optional), | ||
+ | *** Mask for shape/geometry files are of the same type as the text p-values file (e.g., if the p-values file contains 1,000 p-values, 1 per line, then the mask must contain 1,000 lines of 0's and 1's | ||
+ | *** Masks for raw binary volumes must be binary 1-byte volumes of the exact same dimensions as the input volume of raw 4-byte floating p-values. | ||
+ | *** ''Dependence'': If this option is included, it must be preceded by "-type". | ||
+ | *** ''Caution'': Be careful with using masks to FDR correct p-values. P-values outside of the mask are ignored. The skeleton of the Masking and FDR-correction code is as follows: | ||
+ | ::: <code>if (mask_volume.readUnsignedByte()>0) maskVolumeBoolean[i]=true; // get mask</code> | ||
+ | ::: <code>if (maskVolumeBoolean[i]) maskedPValues[counter] = p_values[i]; // mask raw_p_values</code> | ||
+ | ::: <code>thresholdedPMap = FDR(maskedPValues, fdr_rate).getThresholdedArray(); // FDR threshold masked p_values</code> | ||
+ | ::: <code>if (maskVolumeBoolean[i]) FDR_corrected_PValues[i] = thresholdedPMap[counter]; // Save thresholded p_values</code> | ||
+ | ::: <code>else FDR_corrected_PValues[i] = 1.0;</code> | ||
** -fdr_rate [double]: the False Discovery Rate level (e.g., 0.05) | ** -fdr_rate [double]: the False Discovery Rate level (e.g., 0.05) | ||
** -number [int]: enter the number of P-values stored in the input file (output file will have the same number of floats). | ** -number [int]: enter the number of P-values stored in the input file (output file will have the same number of floats). | ||
+ | ** -byteorder string: ''string'' is one of {big, little, other}. | ||
+ | *** ''big'' = BIG_ENDIAN processor | ||
+ | *** ''little'' = LITTLE_ENDIAN processor | ||
+ | *** ''other'' = default processor (java.nio.ByteOrder.nativeOrder()) | ||
+ | ** -verbose: to report all input and corrected-output p-values (avoid!) | ||
+ | |||
+ | ===Try-It-Online=== | ||
+ | You can test the FDR functionality using the [http://ucla.in/Ie80ps Pipeline PWS Web-start server]. | ||
+ | |||
+ | ====Shape-based p-Value FDR correction example==== | ||
+ | Edit a new file (FDR_Correction.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. | ||
+ | [[Image:SOCR_Analyses_FDR_HippoShape_050909.png|200px|thumbnail|right| Results of FDR thresholding (right) the raw p-values (left) of comparing the local shape measures for hippocampal models for 2 groups]] | ||
− | |||
<code>#!/bin/csh</code> | <code>#!/bin/csh</code> | ||
<code>date</code> | <code>date</code> | ||
− | <code>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.Test_FDR -input /ifs/ccb/CCB_SW_Tools/Statistics/SOCR_Statistics/SOCR_CSV_test_Scripts_Data/FDR_Test_Input_PValues.txt -output /ifs/ccb/CCB_SW_Tools/Statistics/SOCR_Statistics/SOCR_CSV_test_Scripts_Data/FDR_Test_PValuesCorrected_Output.txt -type 0 -fdr_rate 0.05 -number 1000 | + | <code>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.Test_FDR -input /ifs/ccb/CCB_SW_Tools/Statistics/SOCR_Statistics/SOCR_CSV_test_Scripts_Data/FDR_Test_Input_PValues.txt -output /ifs/ccb/CCB_SW_Tools/Statistics/SOCR_Statistics/SOCR_CSV_test_Scripts_Data/FDR_Test_PValuesCorrected_Output.txt -type 0 -mask /ifs/ccb/CCB_SW_Tools/Statistics/SOCR_Statistics/SOCR_CSV_test_Scripts_Data/FDR_Test_Input_PValues_MASK.txt -fdr_rate 0.05 -number 1000 -byteorder little |
+ | </code> | ||
+ | |||
+ | <code>date</code> | ||
+ | |||
+ | <code>exit</code> | ||
+ | |||
+ | ====Volume-based p-Value FDR correction example==== | ||
+ | Edit a new file (FDR_Correction.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. | ||
+ | [[Image:SOCR_Analyses_FDR_Volume_051309.png|300px|thumbnail|right| Results of volumetric FDR thresholding (right) the raw p-values (left) obtained by comparing the Jacobians of the displacement fields of registering 2 groups of 3D MRI scans in a common anatomical atlas-space.]] | ||
+ | |||
+ | <code>#!/bin/csh</code> | ||
+ | |||
+ | <code>date</code> | ||
+ | |||
+ | <code>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.Test_FDR -input P_Value_mask_New_Reg_GROUP.img -output P_Value_mask_New_Reg_GROUP_FDRcorrected.img -type 1 -fdr_rate 0.05 -number 10648000 -byteorder little -mask P_Value_mask_New_Reg_GROUP_MASK.img | ||
</code> | </code> | ||
Line 2,042: | Line 2,099: | ||
|} | |} | ||
</center> | </center> | ||
+ | |||
+ | ===Validation=== | ||
+ | [[Image:SOCR_EduMaterials_AnalysesCommandLineFDR_Correction_Fig3.png|300px|thumbnail|right| Pipeline FDR Validation Protocol.]] | ||
+ | The SOCR FDR calculator was validated using the following protocol. The following [http://wiki.stat.ucla.edu/socr/uploads/9/99/FDR_Validation_June_2011.zip ZIP archive] contains data, validation protocol and a [http://pipeline.loni.ucla.edu pipeline graphical workflow] implementation of this validation protocol. This protocol uses the following data: | ||
+ | * Input Files: | ||
+ | : Raw_P.txt - 100 random numbers in (0,1) | ||
+ | : Mask.txt - mask file (1=inside, 0=outside) | ||
+ | : PreMasked_41_P.txt - applying the mask to the raw p-values (premasked_pvalue - raw_pvalue * mask) | ||
+ | * The protocol generates the following output FDR corrected p-value results: | ||
+ | : FDR_NoMask_PreMaskedRaw_P.txt | ||
+ | : FDR_q0.05_Raw_P.txt | ||
+ | : FDR_UsingMask_Raw_P_values.txt | ||
+ | * Explicit validation scripts: | ||
+ | : Calculation of FDR corrected p-values without masking (output: FDR_q0.05_Raw_P.txt): | ||
+ | :: <code>java -ms500m -mx1000m -cp /usr/local/loniJars/SOCR_Statistics/SOCR_core.jar:/usr/local/loniJars/SOCR_Statistics/SOCR_plugin.jar edu.ucla.stat.SOCR.analyses.command.volume.Test_FDR -input Raw_P.txt -output FDR_q0.05_Raw_P.txt -type 0 -fdr_rate 0.05 -number 100 -byteorder little</code> | ||
+ | : Calculation of FDR corrected p-values using the (manually) pre-masked p-values (output: FDR_NoMask_PreMaskedRaw_P.txt): | ||
+ | :: <code>java -ms500m -mx1000m -cp /usr/local/loniJars/SOCR_Statistics/SOCR_core.jar:/usr/local/loniJars/SOCR_Statistics/SOCR_plugin.jar edu.ucla.stat.SOCR.analyses.command.volume.Test_FDR -input PreMasked_41_P.txt -output FDR_NoMask_PreMaskedRaw_P.txt -type 0 -fdr_rate 0.05 -number 52 -byteorder little</code> | ||
+ | : Calculation of FDR corrected p-values by providing the mask file to the FDR-calculator (output: FDR_UsingMask_Raw_P_values.txt): | ||
+ | :: <code>java -ms500m -mx1000m -cp /usr/local/loniJars/SOCR_Statistics/SOCR_core.jar:/usr/local/loniJars/SOCR_Statistics/SOCR_plugin.jar edu.ucla.stat.SOCR.analyses.command.volume.Test_FDR -input Raw_P.txt -output FDR_UsingMask_Raw_P_values.txt -type 0 -fdr_rate 0.05 -number 100 -byteorder little -mask Mask.txt</code> | ||
===Supplementary information=== | ===Supplementary information=== | ||
− | * | + | * [[SMHS_CorrectionMultipleTesting#FDR_.28false_discovery_rate.29 |FDR Correction protocol, SMHS EBook]] |
+ | * [http://en.wikipedia.org/wiki/False_discovery_rate False Discovery Rate (FDR)] | ||
+ | * [http://lib.stat.cmu.edu/~genovese/talks/hannover1-04.pdf FDR Tutorial] | ||
+ | * [http://bioinformatics.oxfordjournals.org/cgi/content/full/21/12/2921 FDR/R implementation] | ||
+ | |||
+ | ===References=== | ||
+ | * Che, Annie, Cui, Jenny, and Dinov, Ivo (2009). [http://www.jstatsoft.org/v30/i03 SOCR Analyses: Implementation and Demonstration of a New Graphical Statistics Educational Toolkit]. JSS, Vol. 30, Issue 3, Apr 2009. | ||
+ | * Scheid, S and Spang, R. (2005) Gene expression: twilight; a Bioconductor package for estimating the local false discovery rate. Bioinformatics 21(12): 2921-2922, [http://bioinformatics.oxfordjournals.org/cgi/content/full/21/12/2921 doi:10.1093/bioinformatics/bti436] | ||
+ | * Che, A, Cui, J, and Dinov, ID (2009) [http://jolt.merlot.org/vol5no1/dinov_0309.htm SOCR Analyses – an Instructional Java Web-based Statistical Analysis Toolkit], JOLT, 5(1), 1-19, March 2009. | ||
+ | * Dinov, ID. [http://www.jstatsoft.org/v16/i11 Statistics Online Computational Resource], Journal of Statistical Software, Vol. 16, No. 1, 1-16, October 2006. | ||
{{translate|pageName=http://wiki.stat.ucla.edu/socr/index.php?title=SOCR_EduMaterials_AnalysesCommandLineFDR_Correction}} | {{translate|pageName=http://wiki.stat.ucla.edu/socr/index.php?title=SOCR_EduMaterials_AnalysesCommandLineFDR_Correction}} |
Latest revision as of 09:35, 3 February 2016
Contents
Analyses Command-Line - False Discovery Rate (FDR) Corection
This page includes the information on how to use the SOCR Analyses library for the purpose of computing the False Discovery Rate (FDR) correction for multiple testing in volumetric and shape-based 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.
In a nutshell, FDR is a statistical method used in multiple hypothesis testing to correct the probability values for the effect of multiple comparisons. FDR controls the expected proportion of incorrectly rejected null hypotheses (i.e., FDR controls the type I error, \(\alpha\)). For example, if 1000 observations were experimentally predicted to be different, and a maximum FDR for these observations was q=0.10, then 100 of these observations would be expected to be false positives. The q-value is the FDR analogue of the p-value. The q-value of an individual hypothesis test is the minimum FDR at which the test may be called significant. One can directly estimate q-values or alternatively, fix a level at which to control the FDR. See the references below for more information on FDR.
Suppose we perform m simultaneous hypothesis tests with a common procedure (test). For any given procedure, we classify the results as shown below. Only these values are observed m, D, and N. The other ones are unknown. Let T=true, F=False, D=Discovery, and N=Nondiscovery. FDR provides a protocol that balances the competing demands of sensitivity and specificity of the test.
Ho Retained | Ho Rejected | Total | |
---|---|---|---|
Ho True | TN | FD | To |
Ho False | FN | TD | T1 |
Total | N | D | m |
Then, FDR guarantees that the expectation of the relative-false-discovery (falsely-rejecting Ho, when it's true) is \(E \left ( {FD \over D}\right ) \leq \alpha\).
The SOCR analysis implementation of FDR is based on this article, see references below.
FDR Usage
- Get the latest SOCR JAR files from the SOCR page (http://socr.ucla.edu/htmls/jars/).
- Generic Setting:
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.Test_FDR -input Input_PValues_File -output Output_PValuesCorrected_File [-type type] [-fdr_rate q] -number integer -byteorder string
- Options:
- -help: prints usage
- -v: verbose mode (will print all input/output data in standard output stream.
- -input [InputFileName]: specify a file-name for an ASCII or binary file containing the raw p-values.
- -output [OutputFileName]: specify a file-name for the corresponding output file that will contain the FDR-corrected p-values.
- -type [0,1]: Type=0 is for ASCII text input file type, Type=1 is for binary 4Byte=Float Input file.
- -mask [Mask-filename]: specify a mask-file (0 or 1 intensities) restricting the voxels where the p-values are FDR corrected (optional),
- Mask for shape/geometry files are of the same type as the text p-values file (e.g., if the p-values file contains 1,000 p-values, 1 per line, then the mask must contain 1,000 lines of 0's and 1's
- Masks for raw binary volumes must be binary 1-byte volumes of the exact same dimensions as the input volume of raw 4-byte floating p-values.
- Dependence: If this option is included, it must be preceded by "-type".
- Caution: Be careful with using masks to FDR correct p-values. P-values outside of the mask are ignored. The skeleton of the Masking and FDR-correction code is as follows:
if (mask_volume.readUnsignedByte()>0) maskVolumeBoolean[i]=true; // get mask
if (maskVolumeBoolean[i]) maskedPValues[counter] = p_values[i]; // mask raw_p_values
thresholdedPMap = FDR(maskedPValues, fdr_rate).getThresholdedArray(); // FDR threshold masked p_values
if (maskVolumeBoolean[i]) FDR_corrected_PValues[i] = thresholdedPMap[counter]; // Save thresholded p_values
else FDR_corrected_PValues[i] = 1.0;
- -fdr_rate [double]: the False Discovery Rate level (e.g., 0.05)
- -number [int]: enter the number of P-values stored in the input file (output file will have the same number of floats).
- -byteorder string: string is one of {big, little, other}.
- big = BIG_ENDIAN processor
- little = LITTLE_ENDIAN processor
- other = default processor (java.nio.ByteOrder.nativeOrder())
- -verbose: to report all input and corrected-output p-values (avoid!)
Try-It-Online
You can test the FDR functionality using the Pipeline PWS Web-start server.
Shape-based p-Value FDR correction example
Edit a new file (FDR_Correction.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.Test_FDR -input /ifs/ccb/CCB_SW_Tools/Statistics/SOCR_Statistics/SOCR_CSV_test_Scripts_Data/FDR_Test_Input_PValues.txt -output /ifs/ccb/CCB_SW_Tools/Statistics/SOCR_Statistics/SOCR_CSV_test_Scripts_Data/FDR_Test_PValuesCorrected_Output.txt -type 0 -mask /ifs/ccb/CCB_SW_Tools/Statistics/SOCR_Statistics/SOCR_CSV_test_Scripts_Data/FDR_Test_Input_PValues_MASK.txt -fdr_rate 0.05 -number 1000 -byteorder little
date
exit
Volume-based p-Value FDR correction example
Edit a new file (FDR_Correction.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.Test_FDR -input P_Value_mask_New_Reg_GROUP.img -output P_Value_mask_New_Reg_GROUP_FDRcorrected.img -type 1 -fdr_rate 0.05 -number 10648000 -byteorder little -mask P_Value_mask_New_Reg_GROUP_MASK.img
date
exit
Example
The table below shows the results of applying FDR-correction to the P_values obtained by non-parametric statistical test comparing the hippocampi surfaces (consisting of 1,00 vertices) of 2 groups of subject(AD and MCI). The FDR-corrected p-values were obtained by the command line included above.
Index | Raw P-Values | FDR-Corrected P-values |
---|---|---|
1.00000000 | 0.00041800 | 0.00041800 |
2.00000000 | 0.00060500 | 0.00060500 |
3.00000000 | 0.06424300 | 0.00000000 |
4.00000000 | 0.14547100 | 0.00000000 |
5.00000000 | 0.78607900 | 0.00000000 |
6.00000000 | 0.08867100 | 0.00000000 |
7.00000000 | 0.38782900 | 0.00000000 |
8.00000000 | 0.04057200 | 0.00000000 |
9.00000000 | 0.07980900 | 0.00000000 |
10.00000000 | 0.00072400 | 0.00072400 |
11.00000000 | 0.53734700 | 0.00000000 |
12.00000000 | 0.38782900 | 0.00000000 |
13.00000000 | 0.00060500 | 0.00060500 |
14.00000000 | 0.00715900 | 0.00000000 |
15.00000000 | 0.33592200 | 0.00000000 |
16.00000000 | 0.78607900 | 0.00000000 |
17.00000000 | 0.20827100 | 0.00000000 |
18.00000000 | 0.33592200 | 0.00000000 |
19.00000000 | 0.00530200 | 0.00000000 |
20.00000000 | 0.00829000 | 0.00000000 |
21.00000000 | 0.01104300 | 0.00000000 |
22.00000000 | 0.01458000 | 0.00000000 |
23.00000000 | 0.01270300 | 0.00000000 |
24.00000000 | 0.94099500 | 0.00000000 |
25.00000000 | 0.07980900 | 0.00000000 |
26.00000000 | 0.00013100 | 0.00013100 |
27.00000000 | 0.94099500 | 0.00000000 |
28.00000000 | 0.05127400 | 0.00000000 |
29.00000000 | 0.00122800 | 0.00000000 |
30.00000000 | 0.19098200 | 0.00000000 |
31.00000000 | 0.28871400 | 0.00000000 |
32.00000000 | 0.00060500 | 0.00060500 |
33.00000000 | 0.07980900 | 0.00000000 |
34.00000000 | 0.00389200 | 0.00000000 |
35.00000000 | 0.00086600 | 0.00086600 |
36.00000000 | 0.36129100 | 0.00000000 |
37.00000000 | 0.00023700 | 0.00023700 |
38.00000000 | 0.03182800 | 0.00000000 |
39.00000000 | 0.28871400 | 0.00000000 |
40.00000000 | 0.36129100 | 0.00000000 |
41.00000000 | 0.12008600 | 0.00000000 |
42.00000000 | 0.03597400 | 0.00000000 |
43.00000000 | 0.14547100 | 0.00000000 |
44.00000000 | 0.00019500 | 0.00019500 |
45.00000000 | 0.00007100 | 0.00007100 |
46.00000000 | 0.14547100 | 0.00000000 |
47.00000000 | 0.00389200 | 0.00000000 |
48.00000000 | 0.00715900 | 0.00000000 |
49.00000000 | 0.44435000 | 0.00000000 |
50.00000000 | 0.00389200 | 0.00000000 |
51.00000000 | 0.22666800 | 0.00000000 |
52.00000000 | 0.00530200 | 0.00000000 |
53.00000000 | 0.00829000 | 0.00000000 |
54.00000000 | 0.00240700 | 0.00000000 |
55.00000000 | 0.78607900 | 0.00000000 |
56.00000000 | 0.00530200 | 0.00000000 |
57.00000000 | 0.19098200 | 0.00000000 |
58.00000000 | 0.86287800 | 0.00000000 |
59.00000000 | 0.07980900 | 0.00000000 |
60.00000000 | 0.05127400 | 0.00000000 |
61.00000000 | 0.03597400 | 0.00000000 |
62.00000000 | 0.63921900 | 0.00000000 |
63.00000000 | 0.26687300 | 0.00000000 |
64.00000000 | 0.78607900 | 0.00000000 |
65.00000000 | 0.67489200 | 0.00000000 |
66.00000000 | 0.36129100 | 0.00000000 |
67.00000000 | 0.74839900 | 0.00000000 |
68.00000000 | 0.09831000 | 0.00000000 |
69.00000000 | 0.00023700 | 0.00023700 |
70.00000000 | 0.00172700 | 0.00000000 |
71.00000000 | 0.31172900 | 0.00000000 |
72.00000000 | 0.02809800 | 0.00000000 |
73.00000000 | 0.01104300 | 0.00000000 |
74.00000000 | 0.00122800 | 0.00000000 |
75.00000000 | 0.17477300 | 0.00000000 |
76.00000000 | 0.17477300 | 0.00000000 |
77.00000000 | 0.00283200 | 0.00000000 |
78.00000000 | 0.00530200 | 0.00000000 |
79.00000000 | 0.00204100 | 0.00000000 |
80.00000000 | 0.36129100 | 0.00000000 |
81.00000000 | 0.01669800 | 0.00000000 |
82.00000000 | 0.94099500 | 0.00000000 |
83.00000000 | 0.53734700 | 0.00000000 |
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575.00000000 | 0.00454800 | 0.00000000 |
576.00000000 | 0.74839900 | 0.00000000 |
577.00000000 | 0.17477300 | 0.00000000 |
578.00000000 | 0.00829000 | 0.00000000 |
579.00000000 | 0.06424300 | 0.00000000 |
580.00000000 | 0.20827100 | 0.00000000 |
581.00000000 | 0.26687300 | 0.00000000 |
582.00000000 | 0.01669800 | 0.00000000 |
583.00000000 | 0.03182800 | 0.00000000 |
584.00000000 | 0.01104300 | 0.00000000 |
585.00000000 | 0.22666800 | 0.00000000 |
586.00000000 | 0.00103200 | 0.00000000 |
587.00000000 | 0.36129100 | 0.00000000 |
588.00000000 | 0.17477300 | 0.00000000 |
589.00000000 | 0.13230700 | 0.00000000 |
590.00000000 | 0.00283200 | 0.00000000 |
591.00000000 | 0.41552200 | 0.00000000 |
592.00000000 | 0.71131000 | 0.00000000 |
593.00000000 | 0.00172700 | 0.00000000 |
594.00000000 | 0.82426800 | 0.00000000 |
595.00000000 | 0.02175600 | 0.00000000 |
596.00000000 | 0.20827100 | 0.00000000 |
597.00000000 | 0.67489200 | 0.00000000 |
598.00000000 | 0.00145800 | 0.00000000 |
599.00000000 | 0.00103200 | 0.00000000 |
600.00000000 | 0.00172700 | 0.00000000 |
601.00000000 | 0.47428600 | 0.00000000 |
602.00000000 | 0.67489200 | 0.00000000 |
603.00000000 | 0.71131000 | 0.00000000 |
604.00000000 | 0.01669800 | 0.00000000 |
605.00000000 | 0.02175600 | 0.00000000 |
606.00000000 | 0.22666800 | 0.00000000 |
607.00000000 | 0.05745500 | 0.00000000 |
608.00000000 | 0.24619500 | 0.00000000 |
609.00000000 | 0.20827100 | 0.00000000 |
610.00000000 | 0.78607900 | 0.00000000 |
611.00000000 | 0.00530200 | 0.00000000 |
612.00000000 | 0.24619500 | 0.00000000 |
613.00000000 | 0.15961400 | 0.00000000 |
614.00000000 | 0.00005800 | 0.00005800 |
615.00000000 | 0.07168000 | 0.00000000 |
616.00000000 | 0.47428600 | 0.00000000 |
617.00000000 | 0.00103200 | 0.00000000 |
618.00000000 | 0.09831000 | 0.00000000 |
619.00000000 | 0.53734700 | 0.00000000 |
620.00000000 | 0.00530200 | 0.00000000 |
621.00000000 | 0.00072400 | 0.00072400 |
622.00000000 | 0.02475100 | 0.00000000 |
623.00000000 | 0.00715900 | 0.00000000 |
624.00000000 | 0.00332400 | 0.00000000 |
625.00000000 | 0.20827100 | 0.00000000 |
626.00000000 | 0.50529900 | 0.00000000 |
627.00000000 | 0.03597400 | 0.00000000 |
628.00000000 | 0.33592200 | 0.00000000 |
629.00000000 | 0.22666800 | 0.00000000 |
630.00000000 | 0.00283200 | 0.00000000 |
631.00000000 | 0.00050300 | 0.00050300 |
632.00000000 | 0.00016000 | 0.00016000 |
633.00000000 | 0.13230700 | 0.00000000 |
634.00000000 | 0.00240700 | 0.00000000 |
635.00000000 | 0.14547100 | 0.00000000 |
636.00000000 | 0.01669800 | 0.00000000 |
637.00000000 | 0.00715900 | 0.00000000 |
638.00000000 | 0.00086600 | 0.00086600 |
639.00000000 | 0.00957900 | 0.00000000 |
640.00000000 | 0.22666800 | 0.00000000 |
641.00000000 | 0.01270300 | 0.00000000 |
642.00000000 | 0.00008700 | 0.00008700 |
643.00000000 | 0.24619500 | 0.00000000 |
644.00000000 | 0.82426800 | 0.00000000 |
645.00000000 | 0.00010700 | 0.00010700 |
646.00000000 | 0.31172900 | 0.00000000 |
647.00000000 | 0.19098200 | 0.00000000 |
648.00000000 | 0.82426800 | 0.00000000 |
649.00000000 | 0.00715900 | 0.00000000 |
650.00000000 | 0.26687300 | 0.00000000 |
651.00000000 | 0.47428600 | 0.00000000 |
652.00000000 | 0.41552200 | 0.00000000 |
653.00000000 | 0.00010700 | 0.00010700 |
654.00000000 | 0.00086600 | 0.00086600 |
655.00000000 | 0.63921900 | 0.00000000 |
656.00000000 | 0.00616800 | 0.00000000 |
657.00000000 | 0.01908100 | 0.00000000 |
658.00000000 | 0.00616800 | 0.00000000 |
659.00000000 | 0.28871400 | 0.00000000 |
660.00000000 | 0.08867100 | 0.00000000 |
661.00000000 | 0.00957900 | 0.00000000 |
662.00000000 | 0.00530200 | 0.00000000 |
663.00000000 | 0.00240700 | 0.00000000 |
664.00000000 | 0.12008600 | 0.00000000 |
665.00000000 | 0.00007100 | 0.00007100 |
666.00000000 | 0.00957900 | 0.00000000 |
667.00000000 | 0.00050300 | 0.00050300 |
668.00000000 | 0.00389200 | 0.00000000 |
669.00000000 | 0.12008600 | 0.00000000 |
670.00000000 | 0.01908100 | 0.00000000 |
671.00000000 | 0.15961400 | 0.00000000 |
672.00000000 | 0.12008600 | 0.00000000 |
673.00000000 | 0.50529900 | 0.00000000 |
674.00000000 | 0.01669800 | 0.00000000 |
675.00000000 | 0.05745500 | 0.00000000 |
676.00000000 | 0.00050300 | 0.00050300 |
677.00000000 | 0.90181700 | 0.00000000 |
678.00000000 | 0.00172700 | 0.00000000 |
679.00000000 | 0.15961400 | 0.00000000 |
680.00000000 | 0.00172700 | 0.00000000 |
681.00000000 | 0.78607900 | 0.00000000 |
682.00000000 | 0.00086600 | 0.00086600 |
683.00000000 | 0.00454800 | 0.00000000 |
684.00000000 | 0.02175600 | 0.00000000 |
685.00000000 | 0.41552200 | 0.00000000 |
686.00000000 | 0.01458000 | 0.00000000 |
687.00000000 | 0.94099500 | 0.00000000 |
688.00000000 | 0.00122800 | 0.00000000 |
689.00000000 | 0.00172700 | 0.00000000 |
690.00000000 | 0.90181700 | 0.00000000 |
691.00000000 | 0.00103200 | 0.00000000 |
692.00000000 | 0.17477300 | 0.00000000 |
693.00000000 | 0.33592200 | 0.00000000 |
694.00000000 | 0.50529900 | 0.00000000 |
695.00000000 | 0.01908100 | 0.00000000 |
696.00000000 | 0.01458000 | 0.00000000 |
697.00000000 | 0.00829000 | 0.00000000 |
698.00000000 | 0.90181700 | 0.00000000 |
699.00000000 | 0.00389200 | 0.00000000 |
700.00000000 | 0.09831000 | 0.00000000 |
701.00000000 | 0.12008600 | 0.00000000 |
702.00000000 | 0.02175600 | 0.00000000 |
703.00000000 | 0.78607900 | 0.00000000 |
704.00000000 | 0.98031600 | 0.00000000 |
705.00000000 | 0.00086600 | 0.00086600 |
706.00000000 | 0.44435000 | 0.00000000 |
707.00000000 | 0.08867100 | 0.00000000 |
708.00000000 | 0.78607900 | 0.00000000 |
709.00000000 | 0.22666800 | 0.00000000 |
710.00000000 | 0.17477300 | 0.00000000 |
711.00000000 | 0.00715900 | 0.00000000 |
712.00000000 | 0.08867100 | 0.00000000 |
713.00000000 | 0.38782900 | 0.00000000 |
714.00000000 | 0.01908100 | 0.00000000 |
715.00000000 | 0.47428600 | 0.00000000 |
716.00000000 | 0.00010700 | 0.00010700 |
717.00000000 | 0.14547100 | 0.00000000 |
718.00000000 | 0.01669800 | 0.00000000 |
719.00000000 | 0.20827100 | 0.00000000 |
720.00000000 | 0.33592200 | 0.00000000 |
721.00000000 | 0.00041800 | 0.00041800 |
722.00000000 | 0.04057200 | 0.00000000 |
723.00000000 | 0.00072400 | 0.00072400 |
724.00000000 | 0.60436300 | 0.00000000 |
725.00000000 | 0.94099500 | 0.00000000 |
726.00000000 | 0.01270300 | 0.00000000 |
727.00000000 | 0.01104300 | 0.00000000 |
728.00000000 | 0.17477300 | 0.00000000 |
729.00000000 | 0.00283200 | 0.00000000 |
730.00000000 | 0.01270300 | 0.00000000 |
731.00000000 | 0.07980900 | 0.00000000 |
732.00000000 | 0.00023700 | 0.00023700 |
733.00000000 | 0.00008700 | 0.00008700 |
734.00000000 | 0.00103200 | 0.00000000 |
735.00000000 | 0.04565900 | 0.00000000 |
736.00000000 | 0.63921900 | 0.00000000 |
737.00000000 | 0.00172700 | 0.00000000 |
738.00000000 | 0.41552200 | 0.00000000 |
739.00000000 | 0.00145800 | 0.00000000 |
740.00000000 | 0.00072400 | 0.00072400 |
741.00000000 | 0.17477300 | 0.00000000 |
742.00000000 | 0.94099500 | 0.00000000 |
743.00000000 | 0.00005800 | 0.00005800 |
744.00000000 | 0.01908100 | 0.00000000 |
745.00000000 | 0.33592200 | 0.00000000 |
746.00000000 | 0.05745500 | 0.00000000 |
747.00000000 | 0.03597400 | 0.00000000 |
748.00000000 | 0.28871400 | 0.00000000 |
749.00000000 | 0.00204100 | 0.00000000 |
750.00000000 | 0.01270300 | 0.00000000 |
751.00000000 | 0.00023700 | 0.00023700 |
752.00000000 | 0.19098200 | 0.00000000 |
753.00000000 | 0.03597400 | 0.00000000 |
754.00000000 | 0.10876800 | 0.00000000 |
755.00000000 | 0.17477300 | 0.00000000 |
756.00000000 | 0.22666800 | 0.00000000 |
757.00000000 | 0.00050300 | 0.00050300 |
758.00000000 | 0.00957900 | 0.00000000 |
759.00000000 | 0.20827100 | 0.00000000 |
760.00000000 | 0.24619500 | 0.00000000 |
761.00000000 | 0.00050300 | 0.00050300 |
762.00000000 | 0.09831000 | 0.00000000 |
763.00000000 | 0.15961400 | 0.00000000 |
764.00000000 | 0.67489200 | 0.00000000 |
765.00000000 | 0.02809800 | 0.00000000 |
766.00000000 | 0.07980900 | 0.00000000 |
767.00000000 | 1.00000000 | 0.00000000 |
768.00000000 | 0.00530200 | 0.00000000 |
769.00000000 | 1.00000000 | 0.00000000 |
770.00000000 | 0.01458000 | 0.00000000 |
771.00000000 | 0.00957900 | 0.00000000 |
772.00000000 | 0.57038600 | 0.00000000 |
773.00000000 | 0.00086600 | 0.00086600 |
774.00000000 | 0.00122800 | 0.00000000 |
775.00000000 | 0.06424300 | 0.00000000 |
776.00000000 | 1.00000000 | 0.00000000 |
777.00000000 | 0.05745500 | 0.00000000 |
778.00000000 | 0.02809800 | 0.00000000 |
779.00000000 | 0.00103200 | 0.00000000 |
780.00000000 | 0.09831000 | 0.00000000 |
781.00000000 | 0.01669800 | 0.00000000 |
782.00000000 | 0.00204100 | 0.00000000 |
783.00000000 | 0.05745500 | 0.00000000 |
784.00000000 | 0.00050300 | 0.00050300 |
785.00000000 | 0.41552200 | 0.00000000 |
786.00000000 | 0.31172900 | 0.00000000 |
787.00000000 | 0.53734700 | 0.00000000 |
788.00000000 | 0.09831000 | 0.00000000 |
789.00000000 | 0.00103200 | 0.00000000 |
790.00000000 | 0.33592200 | 0.00000000 |
791.00000000 | 0.28871400 | 0.00000000 |
792.00000000 | 0.57038600 | 0.00000000 |
793.00000000 | 0.00172700 | 0.00000000 |
794.00000000 | 0.94099500 | 0.00000000 |
795.00000000 | 0.00008700 | 0.00008700 |
796.00000000 | 0.00957900 | 0.00000000 |
797.00000000 | 0.00060500 | 0.00060500 |
798.00000000 | 0.47428600 | 0.00000000 |
799.00000000 | 0.24619500 | 0.00000000 |
800.00000000 | 0.00204100 | 0.00000000 |
801.00000000 | 0.41552200 | 0.00000000 |
802.00000000 | 0.94099500 | 0.00000000 |
803.00000000 | 0.04565900 | 0.00000000 |
804.00000000 | 0.57038600 | 0.00000000 |
805.00000000 | 0.07980900 | 0.00000000 |
806.00000000 | 0.33592200 | 0.00000000 |
807.00000000 | 0.00240700 | 0.00000000 |
808.00000000 | 0.60436300 | 0.00000000 |
809.00000000 | 0.00715900 | 0.00000000 |
810.00000000 | 0.71131000 | 0.00000000 |
811.00000000 | 0.01104300 | 0.00000000 |
812.00000000 | 0.13230700 | 0.00000000 |
813.00000000 | 0.01669800 | 0.00000000 |
814.00000000 | 0.09831000 | 0.00000000 |
815.00000000 | 0.08867100 | 0.00000000 |
816.00000000 | 0.14547100 | 0.00000000 |
817.00000000 | 0.00283200 | 0.00000000 |
818.00000000 | 0.01669800 | 0.00000000 |
819.00000000 | 0.02475100 | 0.00000000 |
820.00000000 | 0.02475100 | 0.00000000 |
821.00000000 | 0.15961400 | 0.00000000 |
822.00000000 | 0.50529900 | 0.00000000 |
823.00000000 | 0.15961400 | 0.00000000 |
824.00000000 | 0.00715900 | 0.00000000 |
825.00000000 | 0.00019500 | 0.00019500 |
826.00000000 | 0.20827100 | 0.00000000 |
827.00000000 | 0.90181700 | 0.00000000 |
828.00000000 | 0.04057200 | 0.00000000 |
829.00000000 | 0.00454800 | 0.00000000 |
830.00000000 | 0.06424300 | 0.00000000 |
831.00000000 | 0.74839900 | 0.00000000 |
832.00000000 | 0.47428600 | 0.00000000 |
833.00000000 | 0.00122800 | 0.00000000 |
834.00000000 | 0.57038600 | 0.00000000 |
835.00000000 | 0.24619500 | 0.00000000 |
836.00000000 | 0.57038600 | 0.00000000 |
837.00000000 | 0.00530200 | 0.00000000 |
838.00000000 | 0.00050300 | 0.00050300 |
839.00000000 | 0.47428600 | 0.00000000 |
840.00000000 | 0.08867100 | 0.00000000 |
841.00000000 | 0.00829000 | 0.00000000 |
842.00000000 | 0.19098200 | 0.00000000 |
843.00000000 | 0.90181700 | 0.00000000 |
844.00000000 | 0.94099500 | 0.00000000 |
845.00000000 | 0.86287800 | 0.00000000 |
846.00000000 | 0.28871400 | 0.00000000 |
847.00000000 | 0.07980900 | 0.00000000 |
848.00000000 | 0.53734700 | 0.00000000 |
849.00000000 | 0.04565900 | 0.00000000 |
850.00000000 | 0.26687300 | 0.00000000 |
851.00000000 | 0.01669800 | 0.00000000 |
852.00000000 | 0.28871400 | 0.00000000 |
853.00000000 | 0.10876800 | 0.00000000 |
854.00000000 | 0.00145800 | 0.00000000 |
855.00000000 | 0.78607900 | 0.00000000 |
856.00000000 | 0.00530200 | 0.00000000 |
857.00000000 | 0.98031600 | 0.00000000 |
858.00000000 | 0.00086600 | 0.00086600 |
859.00000000 | 0.44435000 | 0.00000000 |
860.00000000 | 0.13230700 | 0.00000000 |
861.00000000 | 0.00715900 | 0.00000000 |
862.00000000 | 0.67489200 | 0.00000000 |
863.00000000 | 0.50529900 | 0.00000000 |
864.00000000 | 0.00060500 | 0.00060500 |
865.00000000 | 0.05745500 | 0.00000000 |
866.00000000 | 0.00389200 | 0.00000000 |
867.00000000 | 0.01458000 | 0.00000000 |
868.00000000 | 0.09831000 | 0.00000000 |
869.00000000 | 0.14547100 | 0.00000000 |
870.00000000 | 0.08867100 | 0.00000000 |
871.00000000 | 0.00028700 | 0.00028700 |
872.00000000 | 0.44435000 | 0.00000000 |
873.00000000 | 0.01908100 | 0.00000000 |
874.00000000 | 0.44435000 | 0.00000000 |
875.00000000 | 0.78607900 | 0.00000000 |
876.00000000 | 0.82426800 | 0.00000000 |
877.00000000 | 0.00122800 | 0.00000000 |
878.00000000 | 0.00145800 | 0.00000000 |
879.00000000 | 0.44435000 | 0.00000000 |
880.00000000 | 0.38782900 | 0.00000000 |
881.00000000 | 0.04565900 | 0.00000000 |
882.00000000 | 0.00240700 | 0.00000000 |
883.00000000 | 0.00332400 | 0.00000000 |
884.00000000 | 0.00060500 | 0.00060500 |
885.00000000 | 0.00122800 | 0.00000000 |
886.00000000 | 0.00122800 | 0.00000000 |
887.00000000 | 0.00283200 | 0.00000000 |
888.00000000 | 0.19098200 | 0.00000000 |
889.00000000 | 0.13230700 | 0.00000000 |
890.00000000 | 0.05127400 | 0.00000000 |
891.00000000 | 0.00019500 | 0.00019500 |
892.00000000 | 0.00023700 | 0.00023700 |
893.00000000 | 0.07980900 | 0.00000000 |
894.00000000 | 0.05127400 | 0.00000000 |
895.00000000 | 0.08867100 | 0.00000000 |
896.00000000 | 0.00530200 | 0.00000000 |
897.00000000 | 0.00010700 | 0.00010700 |
898.00000000 | 0.01908100 | 0.00000000 |
899.00000000 | 0.00240700 | 0.00000000 |
900.00000000 | 0.05127400 | 0.00000000 |
901.00000000 | 0.05745500 | 0.00000000 |
902.00000000 | 0.19098200 | 0.00000000 |
903.00000000 | 0.00086600 | 0.00086600 |
904.00000000 | 0.12008600 | 0.00000000 |
905.00000000 | 0.00283200 | 0.00000000 |
906.00000000 | 0.19098200 | 0.00000000 |
907.00000000 | 0.03182800 | 0.00000000 |
908.00000000 | 0.53734700 | 0.00000000 |
909.00000000 | 0.82426800 | 0.00000000 |
910.00000000 | 0.24619500 | 0.00000000 |
911.00000000 | 0.15961400 | 0.00000000 |
912.00000000 | 0.00122800 | 0.00000000 |
913.00000000 | 0.01908100 | 0.00000000 |
914.00000000 | 0.60436300 | 0.00000000 |
915.00000000 | 0.20827100 | 0.00000000 |
916.00000000 | 0.03182800 | 0.00000000 |
917.00000000 | 0.00715900 | 0.00000000 |
918.00000000 | 0.08867100 | 0.00000000 |
919.00000000 | 0.00530200 | 0.00000000 |
920.00000000 | 0.19098200 | 0.00000000 |
921.00000000 | 0.00957900 | 0.00000000 |
922.00000000 | 0.82426800 | 0.00000000 |
923.00000000 | 0.00050300 | 0.00050300 |
924.00000000 | 0.38782900 | 0.00000000 |
925.00000000 | 0.60436300 | 0.00000000 |
926.00000000 | 0.17477300 | 0.00000000 |
927.00000000 | 0.22666800 | 0.00000000 |
928.00000000 | 0.03182800 | 0.00000000 |
929.00000000 | 0.00145800 | 0.00000000 |
930.00000000 | 0.00019500 | 0.00019500 |
931.00000000 | 0.12008600 | 0.00000000 |
932.00000000 | 0.33592200 | 0.00000000 |
933.00000000 | 0.00034700 | 0.00034700 |
934.00000000 | 0.02475100 | 0.00000000 |
935.00000000 | 0.00145800 | 0.00000000 |
936.00000000 | 0.05745500 | 0.00000000 |
937.00000000 | 0.67489200 | 0.00000000 |
938.00000000 | 0.00145800 | 0.00000000 |
939.00000000 | 0.01669800 | 0.00000000 |
940.00000000 | 0.02809800 | 0.00000000 |
941.00000000 | 0.47428600 | 0.00000000 |
942.00000000 | 0.00072400 | 0.00072400 |
943.00000000 | 0.33592200 | 0.00000000 |
944.00000000 | 0.01270300 | 0.00000000 |
945.00000000 | 0.00283200 | 0.00000000 |
946.00000000 | 0.00072400 | 0.00072400 |
947.00000000 | 0.00283200 | 0.00000000 |
948.00000000 | 0.00034700 | 0.00034700 |
949.00000000 | 0.17477300 | 0.00000000 |
950.00000000 | 0.04057200 | 0.00000000 |
951.00000000 | 0.02175600 | 0.00000000 |
952.00000000 | 0.00715900 | 0.00000000 |
953.00000000 | 0.15961400 | 0.00000000 |
954.00000000 | 0.20827100 | 0.00000000 |
955.00000000 | 0.78607900 | 0.00000000 |
956.00000000 | 0.00145800 | 0.00000000 |
957.00000000 | 0.00016000 | 0.00016000 |
958.00000000 | 0.07168000 | 0.00000000 |
959.00000000 | 0.22666800 | 0.00000000 |
960.00000000 | 0.03182800 | 0.00000000 |
961.00000000 | 0.47428600 | 0.00000000 |
962.00000000 | 0.00103200 | 0.00000000 |
963.00000000 | 0.00829000 | 0.00000000 |
964.00000000 | 0.06424300 | 0.00000000 |
965.00000000 | 0.00008700 | 0.00008700 |
966.00000000 | 0.00389200 | 0.00000000 |
967.00000000 | 0.60436300 | 0.00000000 |
968.00000000 | 0.01458000 | 0.00000000 |
969.00000000 | 0.00016000 | 0.00016000 |
970.00000000 | 0.00172700 | 0.00000000 |
971.00000000 | 0.00060500 | 0.00060500 |
972.00000000 | 0.00283200 | 0.00000000 |
973.00000000 | 0.00028700 | 0.00028700 |
974.00000000 | 0.00028700 | 0.00028700 |
975.00000000 | 0.01270300 | 0.00000000 |
976.00000000 | 0.00034700 | 0.00034700 |
977.00000000 | 0.02475100 | 0.00000000 |
978.00000000 | 0.33592200 | 0.00000000 |
979.00000000 | 0.05745500 | 0.00000000 |
980.00000000 | 0.00122800 | 0.00000000 |
981.00000000 | 0.00530200 | 0.00000000 |
982.00000000 | 0.02175600 | 0.00000000 |
983.00000000 | 0.41552200 | 0.00000000 |
984.00000000 | 0.63921900 | 0.00000000 |
985.00000000 | 0.00389200 | 0.00000000 |
986.00000000 | 0.00028700 | 0.00028700 |
987.00000000 | 0.00332400 | 0.00000000 |
988.00000000 | 0.07168000 | 0.00000000 |
989.00000000 | 0.06424300 | 0.00000000 |
990.00000000 | 0.00103200 | 0.00000000 |
991.00000000 | 0.00028700 | 0.00028700 |
992.00000000 | 0.02475100 | 0.00000000 |
993.00000000 | 0.15961400 | 0.00000000 |
994.00000000 | 0.05745500 | 0.00000000 |
995.00000000 | 0.03597400 | 0.00000000 |
996.00000000 | 0.06424300 | 0.00000000 |
997.00000000 | 0.28871400 | 0.00000000 |
998.00000000 | 0.36129100 | 0.00000000 |
999.00000000 | 0.01104300 | 0.00000000 |
1000.00000000 | 0.00829000 | 0.00000000 |
Validation
The SOCR FDR calculator was validated using the following protocol. The following ZIP archive contains data, validation protocol and a pipeline graphical workflow implementation of this validation protocol. This protocol uses the following data:
- Input Files:
- Raw_P.txt - 100 random numbers in (0,1)
- Mask.txt - mask file (1=inside, 0=outside)
- PreMasked_41_P.txt - applying the mask to the raw p-values (premasked_pvalue - raw_pvalue * mask)
- The protocol generates the following output FDR corrected p-value results:
- FDR_NoMask_PreMaskedRaw_P.txt
- FDR_q0.05_Raw_P.txt
- FDR_UsingMask_Raw_P_values.txt
- Explicit validation scripts:
- Calculation of FDR corrected p-values without masking (output: FDR_q0.05_Raw_P.txt):
java -ms500m -mx1000m -cp /usr/local/loniJars/SOCR_Statistics/SOCR_core.jar:/usr/local/loniJars/SOCR_Statistics/SOCR_plugin.jar edu.ucla.stat.SOCR.analyses.command.volume.Test_FDR -input Raw_P.txt -output FDR_q0.05_Raw_P.txt -type 0 -fdr_rate 0.05 -number 100 -byteorder little
- Calculation of FDR corrected p-values using the (manually) pre-masked p-values (output: FDR_NoMask_PreMaskedRaw_P.txt):
java -ms500m -mx1000m -cp /usr/local/loniJars/SOCR_Statistics/SOCR_core.jar:/usr/local/loniJars/SOCR_Statistics/SOCR_plugin.jar edu.ucla.stat.SOCR.analyses.command.volume.Test_FDR -input PreMasked_41_P.txt -output FDR_NoMask_PreMaskedRaw_P.txt -type 0 -fdr_rate 0.05 -number 52 -byteorder little
- Calculation of FDR corrected p-values by providing the mask file to the FDR-calculator (output: FDR_UsingMask_Raw_P_values.txt):
java -ms500m -mx1000m -cp /usr/local/loniJars/SOCR_Statistics/SOCR_core.jar:/usr/local/loniJars/SOCR_Statistics/SOCR_plugin.jar edu.ucla.stat.SOCR.analyses.command.volume.Test_FDR -input Raw_P.txt -output FDR_UsingMask_Raw_P_values.txt -type 0 -fdr_rate 0.05 -number 100 -byteorder little -mask Mask.txt
Supplementary information
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.
- Scheid, S and Spang, R. (2005) Gene expression: twilight; a Bioconductor package for estimating the local false discovery rate. Bioinformatics 21(12): 2921-2922, doi:10.1093/bioinformatics/bti436
- 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.
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