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Basic Tutorial: Section 1
Learn to create your first views in Xena

Description

This tutorial is intended for those who have never used Xena before. We will cover how to create your first Visual Spreadsheet with gene expression, mutation, and copy number variation data.

Prerequisites

This tutorial assumes a basic understanding of
  • cancer processes that can lead to altered gene expression, such as copy number variation or mutations
  • RNAseq gene expression, copy number variation, and mutational genomic sequencing data
  • The Cancer Genome Atlas (TCGA)
These resources can help you gain a basic understanding of these concepts:
https://connect.springerpub.com/content/book/978-0-8261-6868-9/chapter/ch01
connect.springerpub.com
What is functional genomics?
Functional genomics I
The Cancer Genome Atlas - Cancers Selected for Study
National Cancer Institute
The Cancer Genome Atlas - Data Types Collected
National Cancer Institute

Estimated time needed

Part A: 5 min
Part B: 10 min

Learning goals

Part A
  • Create a Visual Spreadsheet
  • Compare data across columns
Part B
  • Move columns
  • Resize columns
  • Zoom in and out

Tutorial

We are going to be examining EGFR aberrations in patients with lung adenocarcinomas using TCGA data. We will be looking at mutation and copy number aberrations and how they affect gene expression.

Part A

Our goal is to build a Visual Spreadsheet and understand the relationship between the columns of data.

​Ending Screenshot​

Steps

  1. 1.
    Start at our home page http://xena.ucsc.edu/ and click on 'Launch Xena'. You are now in our Visual Spreadsheet Wizard.
  2. 2.
    Type 'GDC TCGA Lung Adenocarcinoma (LUAD)', select this study from the drop down menu, and click 'Done'.
  3. 3.
    Type 'EGFR', select the checkboxes for Gene Expression, Copy Number, and Somatic Mutation, and click 'Done'.

Video of steps

How to read a Visual Spreadsheet

Samples are on the y-axis and your columns of data are on the x-axis. We line up columns so that each row is the same sample, allowing you to easily see trends in the data. Data is always sorted left to right and sub-sorted on columns thereafter.

Biological interpretation

We can see that samples from TCGA patients that have high expression of EGFR (red, column B) tend to either have amplifications of EGFR (red, column C) or mutations in EGFR (blue tick marks, column D)
More information
Making your own Visual Spreadsheet: Which TCGA study to choose
​There are 4 versions of the TCGA data in Xena. In this example we selected the TCGA data from the GDC. This page can help you decide which version of TCGA data to use for your own analysis.​

Part B

To further explore the relationship between the gene expression, mutation, and copy number variation data for EGFR, we will move columns to change the sort order, resize columns, and zoom in both for the entire Visual Spreadsheet and within a column.

Steps

  1. 1.
    Move columns. Click column C, copy number variation, and drag it to the left so that it becomes the first column after the samples column (i.e. column B). Note that the samples are now sorted by the values in this column.
  2. 2.
    Resize columns. Click the handle in the lower right corner of column D, mutation. Move it to the right to make the column bigger.
  3. 3.
    Zoom in on a column. Click and drag within column D. Release to zoom.
  4. 4.
    Zoom out on a column. Click the red zoom out text at the top of column D.
  5. 5.
    Zoom in on samples. Click and drag vertically in any column in the Visual Spreadsheet to zoom in on these samples.
  6. 6.
    Zoom out on samples. To zoom out click either 'Zoom out' or 'Clear zoom' at the top of the Visual Spreadsheet.

Video of step 1

Video of step 2

Video of steps 3-6

More information

Test your knowledge

Question 1
Answer 1
Create a Visual Spreadsheet looking at TP53 gene expression and mutation in samples from patients in the GDC TCGA Lower Grade Glioma study.
​Ending Screenshot​
Question 2
Answer 2
Change the Visual Spreadsheet from Question 1 so that the patient's samples are sorted by mutations rather than gene expression.
​Ending Screenshot​
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Basic Tutorial: Section 2
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Outline
Description
Prerequisites
Estimated time needed
Learning goals
Tutorial
Part A
Part B
Test your knowledge