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Old 11-14-2018, 01:09 AM   #3
nucacidhunter
Jafar Jabbari
 
Location: Melbourne

Join Date: Jan 2013
Posts: 1,232
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The plots that you are referring should show normal distribution around the GC content of genome in a random library. But IP is not expected to be random so there would be a bias. Extreme GC at the start of reads could also be due to library construction method where some non-template bases are added.

Stretches of G in NextSeq data indicates that there was not any signal in those cycles which could be due to short inserts and adapter dimers. F

From FastQC manual:

“This module measures the GC content across the whole length of each sequence in a file and compares it to a modelled normal distribution of GC content.”

“An unusually shaped distribution could indicate a contaminated library or some other kinds of biased subset. A normal distribution which is shifted indicates some systematic bias which is independent of base position. If there is a systematic bias which creates a shifted normal distribution then this won't be flagged as an error by the module since it doesn't know what your genome's GC content should be.”
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