Per sequence GC content

GC content for each run position.

In a random library, you can expect there to be little or no difference between the different bases in a run, so the plotted line should be roughly horizontal. The overall GC content should reflect the GC content of the underlying genome.

If you see a bias that changes for different bases, it could indicate an overrepresented sequence and therefore contamination of your library. A consistent bias across all positions indicates either that the original library was biased or that there was a systematic problem during library sequencing.

Example of GC content

Warning

This module issues a warning if the GC content deviates by more than 5% from the average GC content.

Failure

This module will fail if the GC content deviates more than 10% from the average GC content.

Common reasons for warnings

The line in this plot should run horizontally across the graph. A ponctual bias is an overrepresented sequence which is contaminating your library. A consistent bias across all bases is a biased original library or a problem during sequencing of the library.

Example of good data for GC content

Good data: Nice and smooth distribution, no variation across read sequence.

Example of good data for GC content

Bad data:

  • Variation across read sequence.
  • Spike around 40% indicates that sequences with 40% GC-content are overrepresented in your sample.

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