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. 2021 Mar 27;49(12):e67. doi: 10.1093/nar/gkab199

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© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

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Figure 4. — Distribution of mutants in the pool and the effect of sequencing error. (A) Relative abundance (counts) of sequences in the unreacted pool (four ribozyme families, total number of reads = 32 931 917), categorized by Hamming distance to its nearest family center. Observed abundance of different classes was similar to the expected number of counts (black dashed line). (B) The effect of different levels of sequencing error () to the expected observed abundance as the ratio to the true abundance for mutants with different orders () in a variant pool with 9% mutation rate. Due to the mixed effects of losing counts from being misidentified to a neighboring sequence and gaining counts from the misidentification of a neighboring sequence, the observed abundance for a sequence would either decrease () or first increase then decrease () as the sequencing error increases. See Supplementary Text S3 for calculation details.

Inline graphic — Distribution of mutants in the pool and the effect of sequencing error. (A) Relative abundance (counts) of sequences in the unreacted pool (four ribozyme families, total number of reads = 32 931 917), categorized by Hamming distance to its nearest family center. Observed abundance of different classes was similar to the expected number of counts (black dashed line). (B) The effect of different levels of sequencing error () to the expected observed abundance as the ratio to the true abundance for mutants with different orders () in a variant pool with 9% mutation rate. Due to the mixed effects of losing counts from being misidentified to a neighboring sequence and gaining counts from the misidentification of a neighboring sequence, the observed abundance for a sequence would either decrease () or first increase then decrease () as the sequencing error increases. See Supplementary Text S3 for calculation details.