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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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by seqadmin
Despite advancements in sequencing platforms and related sample preparation technologies, certain sample types continue to present significant challenges that can compromise sequencing results. Pedro Echave, Senior Manager of the Global Business Segment at Revvity, explained that the success of a sequencing experiment ultimately depends on the amount and integrity of the nucleic acid template (RNA or DNA) obtained from a sample. “The better the quality of the nucleic acid isolated...-
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Channel: Articles
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