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PCA

Principal Component Analysis Explore high-dimensional data sets. Color-code cohorts.

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Overview

Principle Component Analysis (PCA) provides a two dimensional view of sample similarity based on given molecular and gene sets, e.g. patterns in RNA expression for patients using all available genes. Users explore expression data in the PCA window. The PCA window allows users to visualize cohorts of patients by specific gene sets and/or expression data. Buttons in the control bars show or hide different areas of the application.

PCA
  • Patient Nodes: Select nodes by holding down the Shift key and selecting either individual or larger node groupings.
  • Control Bar: Collection of controls that operate over the patient areas.
  • Survival Curves: Survival curves correlate to each saved cohort above.
  • Cohorts and Collections: Snapshots of the various collections, either patient or gene (gene coming soon). Different filters include visualizing age at diagnosis, gender, race, ethnicity, vital status or tumor status. Also, includes the ability to save and push cohorts through the various tools. To learn more visit Oncoscape
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Use Cases

Show PCA plot of RNA expression colored by HPV status

Save and view cohorts with RNA expression colored by HPV status.

  1. PCA for Head and Neck: Default for H & N: PCA using CNV gistic scores for all genes based on UCSC data pipeline
  2. Change Input type to update Plot Layout: Load the PCA scores based on RNA expression data
  3. Color Patients by Clinical Indicator: Choose HPV Status P16 to color patients within the plot
  4. View Patterns among Patients: Refer to the legend to see patient categories
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Navigation

Gene Set
Data Source

Provides users the ability to select a gene set to operate over. More detail about the various genesets can be found in the Methods section. To apply a new geneset locate the Gene Set dropdown menu and make a selection.

Provides users the ability to select a data source. More information about the UCSC dataset can be found in the "Methods" section. To apply an a new data source locate the Data Source dropdown menu and make a selection.

PCA Type
Variance

Provides users the ability to select a PCA type. To apply a type other than the default (cnv) find the PCA Type dropdown menu and make a selection.

PCA, variance means summative variance or multivariate variability or overall variability or total variability. Below is the covariance matrix of some 2 variables.


Patient Colors

By clicking the Color Options button users are able to color code patient nodes based on several unique operators. A popup list will appear on the screen. Selections include the percentages of patient nodes that include the selection e.g. 100% of patient nodes have gender specified.

Patient Colors

Diagnosis

Gender

Tumor Grade

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Methods

Oncoscape hosts level 3 public TCGA datasets representing gene and patient data downloaded from UCSC Xena. To review this data in depth visit our data API. User planning to publish on the provided data must adhere to all publishing guideline set by the NIH. Datasets in Oncoscape are classified by disease type according to TCGA studies.

Data was generated using the R-package Principal Components Analysis

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Frequently Asked Questions

How do I export or print my graphs?

Currently, the export feature is only available on the Spreadsheet tool. Users can push saved cohorts to the spreadsheet tool by clicking the the Analysis Tool button at the top of the screen. Once there click the Export button. An Excel file will get generated.


How do I save my data for a return visit?

All data for selections and cohorts will be automatically saved for a return visit assuming users are on the same computer to login. User logins that allow stored sessions from any device will be deployed in a future release.