TY - JOUR
T1 - Evaluating the necessity of PCR duplicate removal from next-generation sequencing data and a comparison of approaches
AU - Ebbert, Mark T.W.
AU - Wadsworth, Mark E.
AU - Staley, Lyndsay A.
AU - Hoyt, Kaitlyn L.
AU - Pickett, Brandon
AU - Miller, Justin
AU - Duce, John
AU - Kauwe, John S.K.
AU - Ridge, Perry G.
N1 - Publisher Copyright:
© 2016 The Author(s).
PY - 2016/7/25
Y1 - 2016/7/25
N2 - Background: Analyzing next-generation sequencing data is difficult because datasets are large, second generation sequencing platforms have high error rates, and because each position in the target genome (exome, transcriptome, etc.) is sequenced multiple times. Given these challenges, numerous bioinformatic algorithms have been developed to analyze these data. These algorithms aim to find an appropriate balance between data loss, errors, analysis time, and memory footprint. Typical analysis pipelines require multiple steps. If one or more of these steps is unnecessary, it would significantly decrease compute time and data manipulation to remove the step. One step in many pipelines is PCR duplicate removal, where PCR duplicates arise from multiple PCR products from the same template molecule binding on the flowcell. These are often removed because there is concern they can lead to false positive variant calls. Picard (MarkDuplicates) and SAMTools (rmdup) are the two main softwares used for PCR duplicate removal. Results: Approximately 92 % of the 17+ million variants called were called whether we removed duplicates with Picard or SAMTools, or left the PCR duplicates in the dataset. There were no significant differences between the unique variant sets when comparing the transition/transversion ratios (p = 1.0), percentage of novel variants (p = 0.99), average population frequencies (p = 0.99), and the percentage of protein-changing variants (p = 1.0). Results were similar for variants in the American College of Medical Genetics genes. Genotype concordance between NGS and SNP chips was above 99 % for all genotype groups (e.g., homozygous reference). Conclusions: Our results suggest that PCR duplicate removal has minimal effect on the accuracy of subsequent variant calls.
AB - Background: Analyzing next-generation sequencing data is difficult because datasets are large, second generation sequencing platforms have high error rates, and because each position in the target genome (exome, transcriptome, etc.) is sequenced multiple times. Given these challenges, numerous bioinformatic algorithms have been developed to analyze these data. These algorithms aim to find an appropriate balance between data loss, errors, analysis time, and memory footprint. Typical analysis pipelines require multiple steps. If one or more of these steps is unnecessary, it would significantly decrease compute time and data manipulation to remove the step. One step in many pipelines is PCR duplicate removal, where PCR duplicates arise from multiple PCR products from the same template molecule binding on the flowcell. These are often removed because there is concern they can lead to false positive variant calls. Picard (MarkDuplicates) and SAMTools (rmdup) are the two main softwares used for PCR duplicate removal. Results: Approximately 92 % of the 17+ million variants called were called whether we removed duplicates with Picard or SAMTools, or left the PCR duplicates in the dataset. There were no significant differences between the unique variant sets when comparing the transition/transversion ratios (p = 1.0), percentage of novel variants (p = 0.99), average population frequencies (p = 0.99), and the percentage of protein-changing variants (p = 1.0). Results were similar for variants in the American College of Medical Genetics genes. Genotype concordance between NGS and SNP chips was above 99 % for all genotype groups (e.g., homozygous reference). Conclusions: Our results suggest that PCR duplicate removal has minimal effect on the accuracy of subsequent variant calls.
KW - Next-Generation Sequencing
KW - PCR duplicate removal
KW - Picard
KW - SAMTools
UR - http://www.scopus.com/inward/record.url?scp=84979273070&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84979273070&partnerID=8YFLogxK
U2 - 10.1186/s12859-016-1097-3
DO - 10.1186/s12859-016-1097-3
M3 - Article
C2 - 27454357
AN - SCOPUS:84979273070
SN - 1471-2105
VL - 17
JO - BMC Bioinformatics
JF - BMC Bioinformatics
M1 - 239
ER -