Master Regulator Analysis - Revision history

Smith: /* References */

2014-07-31T22:47:31Z

‎References

Smith: /* Load Network */

2014-04-22T18:40:36Z

‎Load Network

Smith at 23:47, 22 January 2014

2014-01-22T23:47:46Z

Smith: /* Overview */

2014-01-02T19:18:53Z

‎Overview

Smith: /* References */

2013-11-22T23:13:55Z

‎References

Smith: /* Main */

2013-10-14T20:31:10Z

‎Main

Smith: /* Gene Expression dataset */

2013-10-14T20:28:25Z

‎Gene Expression dataset

Smith: /* Overview */

2013-10-14T20:19:16Z

‎Overview

Smith: /* Overview */

2013-10-14T20:18:48Z

‎Overview

Smith: /* Prerequisites */

2013-10-14T20:15:08Z

‎Prerequisites

@@ Line 108: / Line 108: @@
 <span id="Basso2005"></span>
 * Basso K, Margolin AA, Stolovitzky G, Klein U, Dalla-Favera R, Califano A (2005). Reverse engineering of regulatory networks in human B cells. Nat Genet 37(4):382-390 ([http://www.nature.com/ng/journal/v37/n4/abs/ng1532.html link to paper]).
-* Carro MS, Lim WK, Alvarez MJ, Bollo RJ, Zhao X, Snyder EY, Sulman EP, Anne SL, Doetsch F, Colman H, Lasorella A, Aldape K, Califano A, Iavarone A  (2010)  The transcriptional network for mesenchymal transformation of brain tumors.  Nature 463(7279):318-25.
+* Carro MS, Lim WK, Alvarez MJ, Bollo RJ, Zhao X, Snyder EY, Sulman EP, Anne SL, Doetsch F, Colman H, Lasorella A, Aldape K, Califano A, Iavarone A  (2010)  The transcriptional network for mesenchymal transformation of brain tumors.  Nature 463(7279):318-25. PMID: [http://www.ncbi.nlm.nih.gov/pubmed/20032975 20032975].
 <span id="Lefebvre2010"></span>
-* Lefebvre C, Rajbhandari P, Alvarez MJ, Bandaru P, Lim WK, Sato M, Wang K, Sumazin P, Kustagi M, Bisikirska BC, Basso K, Beltrao P, Krogan N, Gautier J, Dalla-Favera R, Califano A (2010)  A human B-cell interactome identifies MYB and FOXM1 as master regulators of proliferation in germinal centers.  Mol Syst Biol.  6:377. PMID: 20531406 ([http://www.ncbi.nlm.nih.gov/pubmed/20531406 link to paper]).
+* Lefebvre C, Rajbhandari P, Alvarez MJ, Bandaru P, Lim WK, Sato M, Wang K, Sumazin P, Kustagi M, Bisikirska BC, Basso K, Beltrao P, Krogan N, Gautier J, Dalla-Favera R, Califano A (2010)  A human B-cell interactome identifies MYB and FOXM1 as master regulators of proliferation in germinal centers.  Mol Syst Biol.  6:377. PMID: [http://www.ncbi.nlm.nih.gov/pubmed/20531406 20531406].
 <span id="Lim2009"></span>
 * Lim WK, Lyashenko E, Califano A: Master regulators used as breast cancer metastasis classifier. Pac Symp Biocomput. 2009:504-15 ([http://psb.stanford.edu/psb-online/proceedings/psb09/lim.pdf link to paper]).
 * Phillips HS, Kharbanda S, Chen R, Forrest WF, Soriano RH, Wu TD, Misra A, Nigro JM, Colman H, Soroceanu L, Williams PM, Modrusan Z, Feuerstein BG, Aldape K (2006)  Molecular subclasses of high-grade glioma predict prognosis, delineate a pattern of disease progression, and resemble stages in neurogenesis.  Cancer Cell 9(3):157-73.

@@ Line 61: / Line 61: @@
 There are 2 ways to designate the interaction network, represented by an adjacency matrix, that will be used for computing the regulons of the candidate master regulator genes:
 * '''From File''': by choosing a file that describes a network.
-* '''From Workspace''': by selecting an adjacency matrix node from the Workspace component.
+* '''From Workspace''': by selecting an adjacency matrix node from the [[Workspace|Workspace]] component.
 =====Load Network from File=====
@@ Line 86: / Line 86: @@
 =====Load Network from Workspace=====
-Several analytical components in geWorkbench (e.g., [[ARACNe | ARACNe]], [[Cellular_Networks_KnowledgeBase | CNKB]]) produce adjacency matrix results nodes that can be utilized for this purpose.  Networks can also be loaded inot the Workspace directly from a file.
+Several analytical components in geWorkbench (e.g., [[ARACNe | ARACNe]], [[Cellular_Networks_KnowledgeBase | CNKB]]) produce adjacency matrix results nodes that can be utilized for this purpose.  Networks can also be loaded into the [[Workspace|Workspace]] directly from a file.
 * The pulldown menu for choosing an available adjacency matrix will become active.  Only adjacency matrices that are children of the current microarray dataset will be offered.

@@ Line 103: / Line 103: @@
 =Dataset History=
-Each results node stores the parameter settings used to setup the corresponding MRA run. The specific parameter values can be inspected within the Dataset History component, after clicking on the MRA results node in the Project Folders pane.
+Each results node stores the parameter settings used to setup the corresponding MRA run. The specific parameter values can be inspected within the Dataset History component, after clicking on the MRA results node in the [[Workspace]].
 =References=

@@ Line 7: / Line 7: @@
 Master Regulator analysis [[#Lefebvre2010 | [Lefebvre et al., 2010]]] is an algorithm used to identify transcription factors whose targets (e.g., as represented in an ARACNe-generated interactome) are enriched for a particular gene signature (e.g. a list of differentially expressed genes).  The enrichment is evaluated using a statistical test such as Fisher’s exact test or GSEA.  The objective is to place the signature genes within a regulatory context and identify the master regulators responsible for coordinating their activity, thus highlighting the regulatory apparatus driving phenotypic differentiation.
-Specifically, given an interaction network ''I'', a (presumed) master regulator gene ''A'', and a set of signature genes, MRA computes the intersection between two sets of genes:
+Specifically, given an interaction network ''I'', a (presumed) master regulator gene ''A'', and a set of signature genes, MRA computes the enrichment of the signature genes in the regulon of ''A'', where the regulon of ''A'' is defined as its neighbors in the interaction network ''I''.
 Interaction networks are represented as "adjacency matrices".  An adjacency matrix lists the connections that each node takes part in, and includes a measure of the strength of that interaction (e.g. the mutual information in the case of matrices generated by ARACNe).
-The MRA component supports two methods to evaluate the overlap of the signature and the regulon.  Either method will quantify how likely it is to encounter an intersection of (at least) the observed size by chance alone. A small p-value is taken to imply that gene ''A'' may play a significant role in mediating the regulatory program that leads to the differential phenotypes.  Another way to sort the results is by the number of genes in the overlap set.  This may give a better evaluation of the actual biological significance of the MR.  As the number of genes in each hub gene's regulon is different, the calculated p-values are not directly comparable to each other.
+Their are two master regulator analysis components implementing different methods to evaluate the enrichment of the signature in the regulon.  Either method will quantify how likely it is to encounter an enrichment of (at least) the observed size by chance alone. A small p-value is taken to imply that gene ''A'' may play a significant role in mediating the regulatory program that leads to the differential phenotypes.
 * '''[[MRA-FET|FET Method (local service)]]''' - this method use Fisher's Exact Test.  This method is implemented locally in geWorkbench.
 * '''[[MARINa|MARINa Method *(grid service)]]''' - this method uses GSEA and differs in substantial ways from the FET-based method.  This method is only implemented as a grid service and currently has restricted availability due to its computational cost.  A t-test between two phenotype classes is built in to the implementation to produce the gene signature.
 Please note that MARINa does not employ any of the special gene lists available for use with the GSEA algorithm, such as [http://www.broadinstitute.org/gsea/msigdb/index.jsp. MSigDB].  It uses only a calculated list of differentially expressed genes and the regulon of the TF being tested.

@@ Line 108: / Line 108: @@
 <span id="Basso2005"></span>
 * Basso K, Margolin AA, Stolovitzky G, Klein U, Dalla-Favera R, Califano A (2005). Reverse engineering of regulatory networks in human B cells. Nat Genet 37(4):382-390 ([http://www.nature.com/ng/journal/v37/n4/abs/ng1532.html link to paper]).
 <span id="Lefebvre2010"></span>
 * Lefebvre C, Rajbhandari P, Alvarez MJ, Bandaru P, Lim WK, Sato M, Wang K, Sumazin P, Kustagi M, Bisikirska BC, Basso K, Beltrao P, Krogan N, Gautier J, Dalla-Favera R, Califano A (2010)  A human B-cell interactome identifies MYB and FOXM1 as master regulators of proliferation in germinal centers.  Mol Syst Biol.  6:377. PMID: 20531406 ([http://www.ncbi.nlm.nih.gov/pubmed/20531406 link to paper]).
 <span id="Lim2009"></span>
 * Lim WK, Lyashenko E, Califano A: Master regulators used as breast cancer metastasis classifier. Pac Symp Biocomput. 2009:504-15 ([http://psb.stanford.edu/psb-online/proceedings/psb09/lim.pdf link to paper]).
 * Phillips HS, Kharbanda S, Chen R, Forrest WF, Soriano RH, Wu TD, Misra A, Nigro JM, Colman H, Soroceanu L, Williams PM, Modrusan Z, Feuerstein BG, Aldape K (2006)  Molecular subclasses of high-grade glioma predict prognosis, delineate a pattern of disease progression, and resemble stages in neurogenesis.  Cancer Cell 9(3):157-73.

@@ Line 57: / Line 57: @@
 The settings on this tab apply to both the FET and MARINa methods.
 ====Load Network====
 There are 2 ways to designate the interaction network, represented by an adjacency matrix, that will be used for computing the regulons of the candidate master regulator genes:
 * '''From File''': by choosing a file that describes a network.
-* '''From Project''': by selecting an adjacency matrix node from the Project Folders component.
+* '''From Workspace''': by selecting an adjacency matrix node from the Workspace component.
 =====Load Network from File=====
@@ Line 87: / Line 85: @@
 After the file has been loaded, its name will be displayed in the adjacent text field.
-=====Load Network from Project=====
+=====Load Network from Workspace=====
-Several analytical components in geWorkbench (e.g., [[ARACNe | ARACNe]], [[Cellular_Networks_KnowledgeBase | CNKB]]) produce adjacency matrix results nodes that can be utilized for this purpose.  Networks can also be loaded from a file directly into the Project.
+Several analytical components in geWorkbench (e.g., [[ARACNe | ARACNe]], [[Cellular_Networks_KnowledgeBase | CNKB]]) produce adjacency matrix results nodes that can be utilized for this purpose.  Networks can also be loaded inot the Workspace directly from a file.
 * The pulldown menu for choosing an available adjacency matrix will become active.  Only adjacency matrices that are children of the current microarray dataset will be offered.

@@ Line 31: / Line 31: @@
 ===Gene Expression dataset===
-A gene expression dataset in which the phenotypic signature was identified or can be demonstrated.  A t-test of differential expression will be run to generate the graphic "bar code" display of the effect of the master regulator on its regulon (FET method) or to generate the signature gene list (MARINa method).
+A gene expression dataset in which the phenotypic signature was identified or can be demonstrated.  A t-test of differential expression will be run to generate the graphic "bar code" display of the effect of the master regulator on its regulon  or to generate the signature gene list (MARINa method).
 ===Interaction Network===

@@ Line 20: / Line 20: @@
 Please note that MARINa does not employ any of the special gene lists available for use with the GSEA algorithm, such as [http://www.broadinstitute.org/gsea/msigdb/index.jsp. MSigDB].  It uses only a calculated list of differentially expressed genes and the regulon of the TF being tested.
 With the release of geWorkbench 2.5.0, MRA-FET and MRA-MARINa are located in two separate sets of components, which can be loaded in the [[Component_Configuration_Manager| CCM]].
 =Setting up an MRA run=

@@ Line 28: / Line 28: @@
 ==Prerequisites==
-* The Master Regulator Analysis (MRA) component must be loaded in the [[Component_Configuration_Manager | Component Configuration Manager]].
+* Either or both Master Regulator Analysis (MRA) components, MRA-FET and MRA-MARINa, must be loaded in the [[Component_Configuration_Manager | Component Configuration Manager]].
-MRA-FET and MRA-MARINa are now located in separate components.
+[[Image:MRA-MARINa-CCM.png]]
 ===Gene Expression dataset===