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Old 11-01-2017, 03:44 AM   #1
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Default Lower quality when number of reads is way higher than spec?

According to UCSB, this is true for NextSeq. Is this the same for other machines?

If this is true, how do we deal with this problem? Can quality trimming help?
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Old 11-01-2017, 03:52 AM   #2
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Is this mostly a theoretical question?

Sometimes we encounter exceptional libraries that will sequences well even with read numbers above spec (rare). In general, over-clustering will lead to drop in Q scores. The drop may be spread across the run or may be more towards the ends of reads (if the run was borderline over-clustered).

Whether Q score trimming can help will depend on the data you have.
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