Revision as of 21:35, 27 February 2006 (view source) Smith (talk | contribs)		Revision as of 23:24, 27 February 2006 (view source) Smith (talk | contribs) Newer edit →
Line 1:		Line 1:
	{{TutorialsTopNav}}		{{TutorialsTopNav}}
		+
		+
		+	In this tutorial, you will:
		+
		+	* Get acquainted with the T Test and Multi T Test
		+	* Apply a T Test and Multi T Test
		+
		+
		+
		+	Before you can continue, geworkbench should be running.  Load the data as described in [[Tutorial - Projects and Data Files]].
		+
		+
		+
		+	==T Test==
		+
		+	T Test analysis identifies markers with statistically significant differential expression between sets of microarrays. The t-test determines for each marker if there is a significant difference between the two groups (case and control). To perform this analysis, you must classify the panels, set the analysis parameters and view the results in the visualization components. A detailed description of the T Test parameters is described in online help.
		+
		+
		+	===Classify the Sets===
		+
		+	This process has already been described in [[Tutorial - Data Subsets]].  Briefly,
		+
		+	1. Mark the '''Cardio''' phenotype a 'Case'. By default, panels are marked as control.  Panels classified Case are shown with a red thumbtack icon.
		+	* Right-click on '''Cardio''' phenotype.
		+	* Select '''Classification'''>'''Case'''.
		+	2. Activate the arrays '''Normal''' and '''Cardio''' by selecting the checkboxes next to the panel name.
		+
		+
		+
		+	[[Image:T_PhenotypeSettingCase.png]]
		+
		+	===Set Analysis Parameters===
		+	# From the Analysis Panel, select '''T-Test Analysis'''.
		+	# Populate the below parameters values and click on '''Analyze'''.
		+
		+	* Alpha-corrections tab:  Just Alpha.
		+	* P-Value Parameters tab: p-values based on t-distribution. Note that the default alpha (critical p-value) is set to 0.01.
		+	* Degree of Freedom tab: Welch approximation - unequal group variances.
		+
		+	[[Image:Ttest.gif]]<br>
		+
		+
		+
		+	===T-Test Results===
		+
		+
		+
		+	{|style="border: 1px solid lightGray"
		+	!|| ||
		+	|-
		+	|-
		+	|  Markers which met the significance test are included in a new gene panel called “Significant Genes”.  || [[Image:E_ttestgpanel.png]]
		+	|-
		+	|-
		+	| Ancillary dataset is created in the project window. ||  [[Image:Ed_ttestproj.png]]
		+	|-
		+	|}
		+
		+
		+	The values of the T-Test can be seen in the Color Mosaic panel and the Volcano Plot.
		+
		+
		+	{|style="border: 1px solid lightGray"
		+	!VOLCANO PLOT||COLOR MOSAIC||
		+	|-
		+	|-|-
		+	|-
		+	|-
		+	| [[Image:Vplot.png]]  ||  [[Image:Ed_cm.png]]
		+	|-
		+	|-
		+	|-
		+	| Clicking on any of the spots highlights the marker selected in the Marker Panel.  * Insert another description ||
		+	* The label to the right displays the Significance value ( lower the value, most likely different) and gene name for the displayed genes. The genes are displayed in ascending order by Significance Value.
		+
		+	* Gene height and width values can be altered to modify the display.
		+
		+	* The intensity slider is used to modify the intensity of the color codings.
		+
		+	* Accession: Includes the accesion number in the label.
		+
		+	* Printer Icon: Prints the displayed image.
		+
		+	* Display: Must be toggled on to display data.
		+
		+	*  ''Pat, Abs, Ratio Overlapping Pages Icon: Not the T Test display.''
		+
		+	|-
		+	|-
		+	|}

---

Revision as of 23:24, 27 February 2006

Home | Quick Start | Basics | Menu Bar | Preferences | Component Configuration Manager | Workspace | Information Panel | Local Data Files | File Formats | caArray | Array Sets | Marker Sets | Microarray Dataset Viewers | Filtering | Normalization | Tutorial Data | geWorkbench-web Tutorials

Analysis Framework | ANOVA | ARACNe | BLAST | Cellular Networks KnowledgeBase | CeRNA/Hermes Query | Classification (KNN, WV) | Color Mosaic | Consensus Clustering | Cytoscape | Cupid | DeMAND | Expression Value Distribution | Fold-Change | Gene Ontology Term Analysis | Gene Ontology Viewer | GenomeSpace | genSpace | Grid Services | GSEA | Hierarchical Clustering | IDEA | Jmol | K-Means Clustering | LINCS Query | Marker Annotations | MarkUs | Master Regulator Analysis | (MRA-FET Method) | (MRA-MARINa Method) | MatrixREDUCE | MINDy | Pattern Discovery | PCA | Promoter Analysis | Pudge | SAM | Sequence Retriever | SkyBase | SkyLine | SOM | SVM | T-Test | Viper Analysis | Volcano Plot

In this tutorial, you will:

• Get acquainted with the T Test and Multi T Test
• Apply a T Test and Multi T Test

Before you can continue, geworkbench should be running. Load the data as described in Tutorial - Projects and Data Files.

T Test

T Test analysis identifies markers with statistically significant differential expression between sets of microarrays. The t-test determines for each marker if there is a significant difference between the two groups (case and control). To perform this analysis, you must classify the panels, set the analysis parameters and view the results in the visualization components. A detailed description of the T Test parameters is described in online help.

Classify the Sets

This process has already been described in Tutorial - Data Subsets. Briefly,

1. Mark the Cardio phenotype a 'Case'. By default, panels are marked as control. Panels classified Case are shown with a red thumbtack icon.

• Right-click on Cardio phenotype.
• Select Classification>Case.

2. Activate the arrays Normal and Cardio by selecting the checkboxes next to the panel name.

Set Analysis Parameters

1. From the Analysis Panel, select T-Test Analysis.
2. Populate the below parameters values and click on Analyze.

• Alpha-corrections tab: Just Alpha.
• P-Value Parameters tab: p-values based on t-distribution. Note that the default alpha (critical p-value) is set to 0.01.
• Degree of Freedom tab: Welch approximation - unequal group variances.

T-Test Results

Markers which met the significance test are included in a new gene panel called “Significant Genes”.
Ancillary dataset is created in the project window.

The values of the T-Test can be seen in the Color Mosaic panel and the Volcano Plot.

VOLCANO PLOT	COLOR MOSAIC
Clicking on any of the spots highlights the marker selected in the Marker Panel. * Insert another description	The label to the right displays the Significance value ( lower the value, most likely different) and gene name for the displayed genes. The genes are displayed in ascending order by Significance Value. Gene height and width values can be altered to modify the display. The intensity slider is used to modify the intensity of the color codings. Accession: Includes the accesion number in the label. Printer Icon: Prints the displayed image. Display: Must be toggled on to display data. Pat, Abs, Ratio Overlapping Pages Icon: Not the T Test display.