ARACNe - Revision history

Smith: /* P-Value */

2015-01-30T22:26:23Z

‎P-Value

Smith: /* P-Value */

2015-01-30T22:25:33Z

‎P-Value

Smith: /* Preprocessing files included with geWorkbench */

2015-01-30T22:17:19Z

‎Preprocessing files included with geWorkbench

Smith: /* Preprocessing files included with geWorkbench */

2015-01-30T22:17:02Z

‎Preprocessing files included with geWorkbench

Smith: /* Preprocessing File Naming */

2015-01-30T22:12:35Z

‎Preprocessing File Naming

Smith: /* Preprocessing */

2015-01-30T22:11:21Z

‎Preprocessing

Smith: /* Adaptive Partitioning */

2015-01-30T22:10:08Z

‎Adaptive Partitioning

Smith: /* Setting up an ARACNe run */

2015-01-27T23:53:23Z

‎Setting up an ARACNe run

Smith: /* Correction */

2015-01-27T20:08:21Z

‎Correction

Smith: /* Correction */

2015-01-27T20:06:21Z

‎Correction

@@ Line 106: / Line 106: @@
 Use the raw MI value calculated by ARACNe.  Only interactions with MI above the threshold will be included in the final network.  the MI can be any positive value or zero, but not negative.
 ====P-Value====
-Use a p-value calculated from the MI values as the threshold.  For best results, the preprocessing step must be run first to generate the parameters needed to calculate p-values from MI values for the particular data set.  The P-value
+Use a p-value calculated from the MI values as the threshold.  For best results, the preprocessing step must be run first to generate the parameters needed to calculate p-values from MI values for the particular data set.
 ====Threshold====

@@ Line 106: / Line 106: @@
 Use the raw MI value calculated by ARACNe.  Only interactions with MI above the threshold will be included in the final network.  the MI can be any positive value or zero, but not negative.
 ====P-Value====
-Use a p-value calculated from the MI values as the threshold.  For best results, the preprocessing step must be run first to generate the parameters needed to calculate p-values from MI values for the particular data set.  The P-value should be a number between 0.0 and 1.0.
+Use a p-value calculated from the MI values as the threshold.  For best results, the preprocessing step must be run first to generate the parameters needed to calculate p-values from MI values for the particular data set.  The P-value
-* '''Note''' - no multiple testing correction is applied to the p-value.  You can apply a Bonferroni-type correction to the p-value itself if desired.  A built-in option for Bonferroni correction will be provided in release 2.3.0.
 ====Threshold====
 Enter the desired threshold value into the text field.

@@ Line 78: / Line 78: @@
 ====Preprocessing files included with geWorkbench====
-Preprocessing are no longer included with geWorkbench.
+Example preprocessing are no longer included with geWorkbench.
 ====DISCOVERY====

@@ Line 78: / Line 78: @@
 ====Preprocessing files included with geWorkbench====
-Preprocessing as described above was run on the Bcell-100.exp dataset included with geWorkbench.  The resulting ARACNe parameter files are also included in the geWorkbench root directory and ARACNe grid service root.  They will be used by default when the Bcell-100.exp dataset is used in tutorials.  Note that if you rerun the preprocessing step, the relevant file(s) will be overwritten.
+Preprocessing are no longer included with geWorkbench.
 ====DISCOVERY====

@@ Line 66: / Line 66: @@
 ====Preprocessing File Naming====
-As described just above, ARACNe preprocessing creates new parameter files in the geWorkbench installation directory.
+As described just above, ARACNe preprocessing creates new parameter files in the geWorkbench settings directory (~/.geworkbench/sys_data).
 Preprocessing parameter file names are formed by appending the following to the dataset name:

@@ Line 59: / Line 59: @@
 ====Preprocessing====
-In this mode, runtime parameters are calculated, but no MI calculation is performed.    Preprocessing for a given combination of dataset and algorithm need be run only once.  The results are written to one or two files in the geWorkbench root directory.  The names used for these files incorporate both the name of the dataset (taken from the name shown in the [[Workspace|Workspace]]) and the name of the algorithm, and thus are specific to the particular combination.  Each time ARACNe is run in Discovery mode, it will look for the dataset-specific parameter files in its root directory.  If the files are not found (Preprocessing has not been run), default parameter values will be used.
+In this mode, runtime parameters are calculated, but no MI calculation is performed.    Preprocessing for a given combination of dataset and algorithm need be run only once.  The results are written to one or two files in the geWorkbench settings directory (~/.geworkbench/sys_data).  The names used for these files incorporate both the name of the dataset (taken from the name shown in the [[Workspace|Workspace]]) and the name of the algorithm, and thus are specific to the particular combination.  Each time ARACNe is run in Discovery mode, it will look for the dataset-specific parameter files in its root directory.  If the files are not found (Preprocessing has not been run), default parameter values will be used.
 * '''Fixed Bandwidth (FBW) algorithm''' - two files are written to the geWorkbench root directory, one containing parameters for calculating the kernel width, and the other containing parameters for calculating a MI threshold from a specified P-value.
 * '''Adaptive Partitioning (AP) algorithm''' - only the parameter file for calculating a MI threshold from a specified P-value is written.  No kernel-width parameter is used.

@@ Line 47: / Line 47: @@
 ====Adaptive Partitioning====
-Adaptive Partitioning was added with the incorporation of the ARACNe2 code into geWorkbench ( as of version 1.7.0). Adaptive Partitioning is much faster than the original Fixed Bandwidth method, and is also considered to produce superior results under certain circumstances.  Unlike the Fixed Bandwidth method, it does not used a fixed kernel-width when calculating the MI.
+Adaptive Partitioning was added with the incorporation of the ARACNe2 code into geWorkbench. Adaptive Partitioning is much faster than the original Fixed Bandwidth method, and is also considered to produce superior results under certain circumstances.  Unlike the Fixed Bandwidth method, it does not used a fixed kernel-width when calculating the MI.
 ====Fixed Bandwidth====

@@ Line 35: / Line 35: @@
 * Load the microarray dataset into the [[Workspace|Workspace]].  If available, associate a gene annotation file with the dataset.  This will allow the results to be displayed in consolidated fashion in Cytoscape by gene rather than by marker (individual probeset) name.
 * '''Warning on too few arrays''' - if a dataset with fewer than 100 microarrays is submitted for ARACNe analysis, a warning message will appear notifying the user of the suggested minimum of 100 arrays.
 ==Parameters and Settings==

@@ Line 121: / Line 121: @@
 If the threshold type is chosen as P-Value, an option to apply the Bonferroni correction is offered in the adjacent pulldown menu.
-* '''No Correction''' (default) - the user can enter any desired threshold.  No additional correction is applied.
+* '''No Correction''' (default) - the user can enter any desired threshold into the P-value field.  No additional correction is applied.
 * '''Bonferroni Correction''' - divide the specified p-value threshold by the (number of markers)*(number of hub genes tested).

@@ Line 122: / Line 122: @@
 * '''No Correction''' (default) - the user can enter any desired threshold.  No additional correction is applied.
-* '''Correct by # of markers''' - if chosen, the input p-value is divided by the number of targets before being compared.
+* '''Bonferroni Correction''' - divide the specified p-value threshold by the (number of markers)*(number of hub genes tested).
-** '''Note''' - For a true Bonferroni correction based on the number of pairs tested, the correction should be given by markers*hubs. However, this has sometimes been found to be too strict.  If a stricter threshold is desired, it can be entered directly into the text field, and "No Correction" chosen.
 ===Kernel width===