Difference between revisions of "PCA (analysis)"

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Latest revision as of 18:15, 9 December 2020

Analysis title
Statistics-PCA-icon.png PCA
Provider
geneXplain GmbH
Class
PrincipalComponentAnalysis
Plugin
com.genexplain.analyses (geneXplain analyses)

Contents

[edit] Principal Component Analysis (PCA)

[edit] Parameters

  • Input table - Table with normalized measurement values
  • 1. Condition / group name - Name for first condition / group
  • 1. Columns - Columns assigned to first condition / group
  • 2. Condition / group name - Name for second condition / group
  • 2. Columns - Columns assigned to second condition / group
  • 3. Condition / group name - Name for third condition / group
  • 3. Columns - Columns assigned to third condition / group
  • 4. Condition / group name - Name for fourth condition / group
  • 4. Columns - Columns assigned to fourth condition / group
  • 5. Condition / group name - Name for fifth condition / group
  • 5. Columns - Columns assigned to fifth condition / group
  • Output folder - Folder to store output tables

Please note that unnamed groups are not considered. At least three data columns are required.

[edit] Output

The output consists of three files. The PCA Scatter plot shows the items of specified groups at their transformed coordinates according to the first two principal components. The entire set of coordinates is available in PCA Transformed coordinates. Finally, the table PCA Component importance provides information about the relative importance of each principal component with respect to the proportion of explained variance.

[edit] Description

The PCA tool applies Principal Component Analysis to a table of numerical data, e.g. to normalized microarray measurements. For visualization purposes one can assign columns to one of up to five groups, which will be differentially colored in the generated output (scatter plot).

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