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Table 1 Median error rates in MAQC data using shadow linear regression and smoothing spline approachesa

From: Empirical estimation of sequencing error rates using smoothing splines

Samples Expected ER SRER SRER Bias EER_CS EER_CS Bias EER_RS EER_RS Bias
SRR037452 0.3305 0.2578 0.0727 0.3104 0.0201 0.3096 0.0209
SRR037453 0.1917 0.1584 0.0333 0.1824 0.0093 0.1818 0.0099
SRR037454 0.2354 0.1515 0.0839 0.2060 0.0294 0.2059 0.0295
SRR037455 0.1759 0.1448 0.0311 0.1675 0.0084 0.1668 0.0091
SRR037456 0.2312 0.1622 0.0690 0.2037 0.0275 0.2035 0.0277
SRR037457 0.1841 0.1480 0.0361 0.1777 0.0064 0.1771 0.0070
SRR037458 0.2653 0.2321 0.0332 0.2582 0.0071 0.2575 0.0078
SRR037459 0.2371 0.1943 0.0428 0.2202 0.0169 0.2203 0.0168
SRR037460 0.2530 0.2018 0.0512 0.2503 0.0027 0.2490 0.0040
SRR037461 0.2180 0.1704 0.0476 0.2105 0.0075 0.2104 0.0076
SRR037462 0.2443 0.1734 0.0709 0.2322 0.0121 0.2308 0.0135
SRR037463 0.2154 0.1654 0.0500 0.2023 0.0131 0.2045 0.0109
SRR037464 0.2624 0.1666 0.0958 0.2392 0.0232 0.2403 0.0221
SRR037465 0.2145 0.1742 0.0403 0.2038 0.0107 0.2037 0.0108
  1. aBased on 1000 replicates. The frequency-based simulation approach was applied. For each replicate, we considered the top 1000 reads with the highest frequencies as the error-free reads and generated 1000 pairs of error-free read counts and shadow counts
  2. Expected ER expected error rate in simulation studies
  3. SRER error rate estimated using shadow regression
  4. SRER Bias the absolute value of the difference between SRER and Expected ER
  5. EER_CS empirical error rate estimated using cubic smoothing spline
  6. EER_CS Bias the absolute value of the difference between EER_CS and Expected ER
  7. EER_RS empirical error rate estimated using robust smoothing spline
  8. EER_RS Bias the absolute value of the difference between EER_RS and Expected ER