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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