Difference between revisions of "SOCR EduMaterials AnalysesCommandLineFDR Correction"

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(→‎Supplementary information)
 
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=== 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. See the [[SOCR_EduMaterials_AnalysesCommandLineFDR_Correction#Supplementary_information | references below]] for more information on FDR.
+
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===
Line 15: 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 corresponfing output file that will contain the FDR-corrected 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;
+
** -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).
Line 23: Line 55:
 
*** ''little'' = LITTLE_ENDIAN processor
 
*** ''little'' = LITTLE_ENDIAN processor
 
*** ''other'' = default processor (java.nio.ByteOrder.nativeOrder())
 
*** ''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====
 
====Shape-based p-Value FDR correction example====
Line 32: Line 68:
 
<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 -byteorder little
+
<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>
  
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<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 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
+
<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 2,063: 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://en.wikipedia.org/wiki/False_discovery_rate False Discovery Rate (FDR)]
 
* [http://lib.stat.cmu.edu/~genovese/talks/hannover1-04.pdf FDR Tutorial]
 
* [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

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

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.

Results of FDR thresholding (right) the raw p-values (left) of comparing the local shape measures for hippocampal models for 2 groups

#!/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.

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.

#!/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
84.00000000 0.17477300 0.00000000
85.00000000 0.00013100 0.00013100
86.00000000 0.00028700 0.00028700
87.00000000 0.00454800 0.00000000
88.00000000 0.00957900 0.00000000
89.00000000 0.13230700 0.00000000
90.00000000 0.02809800 0.00000000
91.00000000 0.00204100 0.00000000
92.00000000 0.20827100 0.00000000
93.00000000 0.05127400 0.00000000
94.00000000 0.74839900 0.00000000
95.00000000 0.41552200 0.00000000
96.00000000 0.03597400 0.00000000
97.00000000 0.07980900 0.00000000
98.00000000 0.00023700 0.00023700
99.00000000 0.00829000 0.00000000
100.00000000 0.36129100 0.00000000
101.00000000 0.41552200 0.00000000
102.00000000 0.98031600 0.00000000
103.00000000 0.12008600 0.00000000
104.00000000 0.14547100 0.00000000
105.00000000 0.08867100 0.00000000
106.00000000 0.20827100 0.00000000
107.00000000 0.00389200 0.00000000
108.00000000 0.00023700 0.00023700
109.00000000 0.00034700 0.00034700
110.00000000 0.98031600 0.00000000
111.00000000 0.00086600 0.00086600
112.00000000 0.01908100 0.00000000
113.00000000 0.14547100 0.00000000
114.00000000 0.00332400 0.00000000
115.00000000 0.00034700 0.00034700
116.00000000 0.00103200 0.00000000
117.00000000 0.19098200 0.00000000
118.00000000 0.10876800 0.00000000
119.00000000 0.05127400 0.00000000
120.00000000 0.00060500 0.00060500
121.00000000 0.00204100 0.00000000
122.00000000 0.60436300 0.00000000
123.00000000 0.07168000 0.00000000
124.00000000 0.00389200 0.00000000
125.00000000 0.07980900 0.00000000
126.00000000 0.01908100 0.00000000
127.00000000 0.24619500 0.00000000
128.00000000 0.00389200 0.00000000
129.00000000 0.00616800 0.00000000
130.00000000 0.00103200 0.00000000
131.00000000 0.00122800 0.00000000
132.00000000 0.08867100 0.00000000
133.00000000 0.24619500 0.00000000
134.00000000 0.15961400 0.00000000
135.00000000 0.00060500 0.00060500
136.00000000 0.28871400 0.00000000
137.00000000 0.02175600 0.00000000
138.00000000 0.02175600 0.00000000
139.00000000 0.05745500 0.00000000
140.00000000 0.31172900 0.00000000
141.00000000 0.00103200 0.00000000
142.00000000 0.10876800 0.00000000
143.00000000 0.14547100 0.00000000
144.00000000 0.71131000 0.00000000
145.00000000 0.02809800 0.00000000
146.00000000 0.00240700 0.00000000
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Validation

Pipeline FDR Validation Protocol.

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

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