P032

Error Rate Normalization to Establish Position-Specific
LoB & LoD in Next Generation Sequencing Assays
Julian D’Angelo.1, Stephanie Ferguson2, Zhiyi Xie1, Lisa Chamberlain1, Andrew Carson1, and Jeffrey E. Miller1,21Invivoscribe, Inc., San Diego, USA, 2 Lab PMM, LLC, San Diego, CA

Results:Introduction• Next-generation sequencing (NGS) continues to be the method of choice for high throughput
genetic assays. Many assays employ a uniform assay-specific limit of blank (LoB) and limit ofdetection (LoD) that tends to be overly conservative due to “worst-case” error and artifactrates (generated by PCR, sequencing and alignment errors, etc.).
• The process of differentiating sequencing artifacts from real, low-frequency variants isextremely important for clinical utility of NGS-based assays, especially as clinicians push for
tracking minimal residual disease (MRD).
• The motivation for this study was to identify a strategy for finding the inherent error-rate, atsingle base resolution, for our MyMRD® single site assay.
• This strategy dramatically improved the specificity and sensitivity of our MyMRD assay andcan be implemented in any NGS-based assay.

Materials and Methods• Extracted DNA from whole blood or cell lines for 209 samples• 36 control samples (GIAB: NA12878 replicates)• 173 clinical samples• NGS performed using Illumina’s MiSeq® instrument• All samples analyzed using custom In-house MyMRD® analysis pipeline• Interrogated every position across the panel for all samples• Targets were split into exonic (17,538 targets) and intronic (20,039 targets) sets and sameanalysis was run for both sets
• Counted observations of each base substitution and insertion/deletion (indel) event• Looked at the distributions of reference to alternate sequencing errors• Investigated for trends or extreme biases which can influence error rate
• i.e. repeat regions (using UCSC Genome Browser’s RepeatMasker), high GC%, etc.
• Determined more accurate LoB/LoD on a per position basis• Compared trends between exonic and intronic regions

Results:

Figure 1: This plot shows the average error rate frequencies (across samples) for each
substitution, for each reference base across targeted exonic positions. The control
samples are labeled in various shades of blue whereas the clinical samples are labeledin various shades of red. The average error rates are all well below the generalized
0.1% error rate of the sequencer.

Figure 3

TTCCCTTCCC

Figure 4

Figures 3 and 4: This plot shows the frequencies of each alternate call at +/- 5
bases from the start of the (TTCCC)n repeat. One of the repeats observed(TTCCCT)n had a clear affect on increased error rates in the surrounding area. The
circled point highlights a drastically increased indel error rate one base upstreamof the repeat start site. The observed indel was a deletion of the TTCCC repeat.
This is interesting and not unexpected due to the potential of slippage aroundsuch regions. This observation held for both clinical (Figure 3) and control (Figure4) samples.

Figure 5: This bar plot shows the percentage of targets that have abackground error rate below the 0.1% background error rate that many
sequencers claim to have. It is separated by exonic (blue bars) and intronic(red bars) targets. As is expected, intronic targets had high background error
rates in more positions compared with exonic targets.

Conclusions• This study showed the importance of both assay specific and position specific error rates for
LoB & LoD determinations due to high variability at each position• Error rates and general trends aligned with expectations:• Intronic targets showed a higher overall incidence of error rate as compared to exonictargets (especially true for indels).
• There was a simple repeat (TTCCC)n overlapping the MyMRD® targets that seemed toinfluence/increase error rates in the surrounding region.
• >97% of all targets positions (both introns and exons) had a background error rate below thegeneral 0.1% suggested error rate of the sequencing instrument.
• >98% of exonic targets• >95% of intronic targets
Figure 2: This plot shows the average error rate frequencies (across samples) for each
substitution, for each reference base across targeted intronic positions. The control
samples are labeled in various shades of blue whereas the clinical samples are labeled invarious shades of red. The average error rates are all well below the generalized 0.1% error
rate of the sequencer. Also note the higher frequency error rates in intronic positions forCA and GT.

AMP Global, May 16-18 2019, Hong Kong