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wiki:igv_visualization

Visualizing data using IGV

References

One of our goals is to visualize our RNA-seq data using a genome browser.

To prepare alignment data for upload to IGV, the RNAseq_analyzer script simply performed some file format conversions.

file.sam –> file.bam This compresses the .sam file into a binary file
file.bam –> file_sort.bam This sorts the .bam file by chromosome location
file_sort.bam.bai This makes a simple indexing reference file for the sorted .bam file
file.bam –> file.bx This creates a bigwig file

These files can be downloaded from summit using Cyberduck. They can then be opened with IGV.

First, we'll go through how to do this using IGV.


IGV Exercise

  • Open IGV
  • From the drop down menu, select C. elegans (ce11)
  • From JupyterHub, download EG01_sort.bam and EGO01_sort.bam.bai. You can do this by navigating to these files in the file structure, right clicking on them, and selecting Download.
  • From File, select Load from File
  • Within elect your EGO01_sort.bam file, making sure that the file EGO01_sort.bam.bai is located in the same directory.

A cautionary note about .bam files and scaling

You can not compare the heights of any genome browser plots until you have normalized their heights. This is because the height of each plot is proportional to the number of fragments that were sequenced over all. Until you normalize, .bam files from samples that were sequenced to 50 million reads will look twice as tall as those sequenced to 25 million reads.

To normalize the samples:

  • Go to View
  • Go to Preferences
  • Go to Tracks
  • Go to Normalize Coverage Data
  • Click on Normalize Coverage Data
  • Navigate to the SAVE box that is typically not visible at the bottom of the window.
  • Click SAVE

To remove autoscaling

  • Right click on the header for the track called sample01_sort.bam Coverage
  • Unclick autoscale
  • Click on Set Data Range..
  • Select the desired height

Exercise

  • Play around with the browser.
  • Check out cool genes: gst-7, nex-1,
  • Read about interesting genes you find.

Visualizing data using UCSC

wiki/igv_visualization.txt · Last modified: 2019/12/05 09:20 by erin