User:Floratos/MRA - Revision history

Floratos: /* Setting up the parameters and starting MRA */

2009-10-23T15:24:46Z

‎Setting up the parameters and starting MRA

Floratos: /* Setting up the parameters and starting MRA */

2009-10-23T15:23:14Z

‎Setting up the parameters and starting MRA

Floratos: /* Prerequisites */

2009-10-23T15:21:45Z

‎Prerequisites

Floratos: /* Graph View */

2009-10-23T15:20:53Z

‎Graph View

Floratos: /* Detailed Listing */

2009-10-23T15:19:54Z

‎Detailed Listing

Floratos: /* Summary Listing */

2009-10-23T15:18:02Z

‎Summary Listing

Floratos: /* Summary Listing */

2009-10-23T15:12:42Z

‎Summary Listing

Floratos: /* Prerequisites */

2009-10-23T14:56:48Z

‎Prerequisites

Floratos: /* Prerequisites */

2009-10-23T14:45:32Z

‎Prerequisites

Floratos: /* Setting up the parameters and starting MRA */

2009-10-23T14:08:55Z

‎Setting up the parameters and starting MRA

@@ Line 121: / Line 121: @@
 ==Setting up the parameters and starting MRA==
 In the Analysis Panel, select the "MRA Analysis" entry and set the parameters as follows:
-* '''Load Network''': from the drop down choose the option "From File", click on the "Load" button, and select the file "adjacency matrix.adj" to open.
+* '''Load Network''': from the drop down choose the option "From File", click on the "Load" button, and select to open the file "Interaction_network.txt".
-* '''Master Regulators''': from the drop down choose the option "From File", click on the "Load" button, and select the file "master regulators.csv" to open.
+* '''Master Regulators''': from the drop down choose the option "From File", click on the "Load" button, and select to open the file "Master_regulators.csv".
 * '''T-test p-value (alpha)''': set the significance threshold to 0.01.
 [[Image:MRA_params_setting_1.png | 700px]]
-* Finally, click on the "T-test" tab and under '''Correction Method''' select the option titled "Standard Bonferroni", to indicate that the p-value of the t-test statistic for each gene should be family-wise corrected before compared to the p-value threshold (alpha) specified above.
+* Click on the "T-test" tab and under '''Correction Method''' select the option titled "Standard Bonferroni", to indicate that the p-value of the t-test statistic for each gene should be family-wise corrected before compared to the p-value threshold (alpha) specified above.
 [[Image:MRA_params_setting_2.png | 700px]]

@@ Line 120: / Line 120: @@
 ==Setting up the parameters and starting MRA==
-In the Analysis Panel, select the "MRA Analysis" entry and proceed to set the parameters as follows:
+In the Analysis Panel, select the "MRA Analysis" entry and set the parameters as follows:
 * '''Load Network''': from the drop down choose the option "From File", click on the "Load" button, and select the file "adjacency matrix.adj" to open.
 * '''Master Regulators''': from the drop down choose the option "From File", click on the "Load" button, and select the file "master regulators.csv" to open.

@@ Line 100: / Line 100: @@
 # Obtain the annotation file for the HG-U95Av2 array type from the Affymetrix NetAffx website (http://www.affymetrix.com/support/technical/byproduct.affx?product=hgu95). The name will be similar to "HG_U95Av2.na29.annot.csv", where na29 is the version number. Loading the annotation file associates gene names and other information with the Affymetrix probeset IDs (see the geWorkbench FAQ for details on obtaining these files).
 # Store in your disk the following 2 files:
-## [[Media:Interaction_network.txt | Interaction_network.txt]]: describes an interaction network with 1955 nodes and 3810 edges. The file has 1955 lines (one for each node, the node name is the first entry in every line) and each line lists the edges emanating from that node. Edges are describes as tab-delimited pairs where the first member of the pair is the name of the target edge and the second member is a number specifying a weight for the edge (MRA does not use the weight information but other geWorkbench components do). Node names correspond to marker ids.
+## [[Media:Interaction_network.txt | Interaction_network.txt]]: describes an interaction network with 1955 nodes and 3810 edges. The file has 1955 lines (one for each node, the node name is the first entry in every line) and each line lists the edges emanating from that node. Edges are describes as tab-delimited pairs where the first member of the pair is the name of the target node and the second member is a number specifying a weight for the edge (MRA does not use the weight information but other geWorkbench components do). Node names correspond to marker ids.
 ## [[Media:Master_regulators.csv | Master_regulators.csv]]: a list of master regulators. The marker ids in this file correspond to genes whose [http://www.geneontology.org/ Gene Ontology] annotation (under the Molecular Function category) lists them as transcription factors.

@@ Line 89: / Line 89: @@
 [[Image:MRA_graph_view.png|800px]]
-The red-blue gradient at the bottom of the graph represents the range between the highest (red) and the lowest (blue) t-test statistic recorded among the differentially expressed genes. The vertical bars correspond to the genes displayed in the table under the “Detailed listing” portion of the interface, i.e., the intersection between the differentially expressed genes and the regulon of the master regulator ''A'' currently selected within the “Summary listing” table. The relative location of a bar on the gradient represents the t-test statistic recorded for the corresponding gene. Further, the color of each bar provides information about the correlation between the expression levels of the target gene and the master regulator A (correlations are computed as Pearson’s r, using data from all microarrays in the experiment): black means that the two genes are positively correlated (r > 0) while orange means that correlation is negative (r < 0).
+The red-blue gradient at the bottom of the graph represents the range between the highest (red) and the lowest (blue) t-test statistic recorded among all differentially expressed genes. The vertical bars correspond to the genes displayed in the table under the “Detailed listing” portion of the interface, i.e., the intersection between the differentially expressed genes and the regulon of the master regulator ''A'' currently selected within the “Summary listing” table. The relative location of a bar on the gradient represents the t-test statistic recorded for the corresponding gene. Further, the color of each bar provides information about the correlation between the expression levels of the target gene and the master regulator A (correlations are computed as Pearson’s r, using data from all microarrays in the experiment): black means that the two genes are positively correlated (r > 0) while orange means that correlation is negative (r < 0).
 =Dataset History=

@@ Line 82: / Line 82: @@
 * '''Add to Set''': creates a set containing the markers that correspond to the genes currently displayed in the table. The new marker set appears in the Markers component and is named after the master regulator.
 * '''Export selected''': same as “Add to Set” but instead of being added to a marker set, the markers are stored into a file.
-* '''Export all''': stores into a file information for each of the master regulators (instead of only the one currently selected in the “Summary” view). Specifically, for each master regulator, the file lists the markers for all genes that are both differential expressed and also belong to the master regulator’s regulon.
+* '''Export all''': stores into a file information for all master regulators (instead of only the one currently selected in the “Summary” view). Specifically, for each master regulator, the file lists the markers for all genes that are both differential expressed and also belong to the master regulator’s regulon.
 ===Graph View===

@@ Line 61: / Line 61: @@
 Each row contains 4 columns:
-# '''Master Regulator''': This is either the master regulator gene name or the marker/probeset name identifying the corresponding array feature (depending on the selection of 2 radio buttons titled “Symbol” and “Probe set”).
+# '''Master Regulator''': This is either the master regulator gene name or the marker/probeset name identifying the corresponding array feature (depending on the selection of the radio buttons “Symbol” and “Probe set”).
 # '''P-value''': the p-value of fisher’s exact test. The test utilizes a 2x2 contingency table where rows classify markers as differentially expressed versus non-differentially expressed, while columns indicate if a marker belongs to the regulon of the master regulator or not. Counts are computed using all markers found in the input experiment data.
 # '''Genes in regulon''': The number of genes in the regulon of the master regulator (this comprises the set of genes that are first neighbors of the master regulator in the interaction network specified in the parameters panel).

@@ Line 99: / Line 99: @@
 ==Prerequisites==
 # Obtain the annotation file for the HG-U95Av2 array type from the Affymetrix NetAffx website (http://www.affymetrix.com/support/technical/byproduct.affx?product=hgu95). The name will be similar to "HG_U95Av2.na29.annot.csv", where na29 is the version number. Loading the annotation file associates gene names and other information with the Affymetrix probeset IDs (see the geWorkbench FAQ for details on obtaining these files).
 ==Loading and preparing the example data==