Abstract
As high-throughput sequencing continues to increase in speed and throughput, routine clinical and industrial application draws closer. These 'production' settings will require enhanced quality monitoring and quality control to optimize output and reduce costs. We developed SeqControl, a framework for predicting sequencing quality and coverage using a set of 15 metrics describing overall coverage, coverage distribution, basewise coverage and basewise quality. Using whole-genome sequences of 27 prostate cancers and 26 normal references, we derived multivariate models that predict sequencing quality and depth. SeqControl robustly predicted how much sequencing was required to reach a given coverage depth (area under the curve (AUC) = 0.993), accurately classified clinically relevant formalin-fixed, paraffin-embedded samples, and made predictions from as little as one-eighth of a sequencing lane (AUC = 0.967). These techniques can be immediately incorporated into existing sequencing pipelines to monitor data quality in real time. SeqControl is available at http://labs.oicr.on.ca/Boutros-lab/software/SeqControl/.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1071-1075 |
| Number of pages | 5 |
| Journal | Nature Methods |
| Volume | 11 |
| Issue number | 10 |
| DOIs | |
| State | Published - Jan 1 2014 |
| Externally published | Yes |
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ASJC Scopus subject areas
- Biotechnology
- Molecular Biology
- Biochemistry
- Cell Biology
- Medicine(all)
Cite this
SeqControl : Process control for DNA sequencing. / Chong, Lauren C.; Albuquerque, Marco A.; Harding, Nicholas J.; Caloian, Cristian; Chan-Seng-Yue, Michelle; De Borja, Richard; Fraser, Michael; Denroche, Robert E.; Beck, Timothy A.; Van Der Kwast, Theodorus; Bristow, Robert G.; Mcpherson, John Douglas; Boutros, Paul C.
In: Nature Methods, Vol. 11, No. 10, 01.01.2014, p. 1071-1075.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - SeqControl
T2 - Process control for DNA sequencing
AU - Chong, Lauren C.
AU - Albuquerque, Marco A.
AU - Harding, Nicholas J.
AU - Caloian, Cristian
AU - Chan-Seng-Yue, Michelle
AU - De Borja, Richard
AU - Fraser, Michael
AU - Denroche, Robert E.
AU - Beck, Timothy A.
AU - Van Der Kwast, Theodorus
AU - Bristow, Robert G.
AU - Mcpherson, John Douglas
AU - Boutros, Paul C.
PY - 2014/1/1
Y1 - 2014/1/1
N2 - As high-throughput sequencing continues to increase in speed and throughput, routine clinical and industrial application draws closer. These 'production' settings will require enhanced quality monitoring and quality control to optimize output and reduce costs. We developed SeqControl, a framework for predicting sequencing quality and coverage using a set of 15 metrics describing overall coverage, coverage distribution, basewise coverage and basewise quality. Using whole-genome sequences of 27 prostate cancers and 26 normal references, we derived multivariate models that predict sequencing quality and depth. SeqControl robustly predicted how much sequencing was required to reach a given coverage depth (area under the curve (AUC) = 0.993), accurately classified clinically relevant formalin-fixed, paraffin-embedded samples, and made predictions from as little as one-eighth of a sequencing lane (AUC = 0.967). These techniques can be immediately incorporated into existing sequencing pipelines to monitor data quality in real time. SeqControl is available at http://labs.oicr.on.ca/Boutros-lab/software/SeqControl/.
AB - As high-throughput sequencing continues to increase in speed and throughput, routine clinical and industrial application draws closer. These 'production' settings will require enhanced quality monitoring and quality control to optimize output and reduce costs. We developed SeqControl, a framework for predicting sequencing quality and coverage using a set of 15 metrics describing overall coverage, coverage distribution, basewise coverage and basewise quality. Using whole-genome sequences of 27 prostate cancers and 26 normal references, we derived multivariate models that predict sequencing quality and depth. SeqControl robustly predicted how much sequencing was required to reach a given coverage depth (area under the curve (AUC) = 0.993), accurately classified clinically relevant formalin-fixed, paraffin-embedded samples, and made predictions from as little as one-eighth of a sequencing lane (AUC = 0.967). These techniques can be immediately incorporated into existing sequencing pipelines to monitor data quality in real time. SeqControl is available at http://labs.oicr.on.ca/Boutros-lab/software/SeqControl/.
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U2 - 10.1038/nmeth.3094
DO - 10.1038/nmeth.3094
M3 - Article
C2 - 25173705
AN - SCOPUS:84921758024
VL - 11
SP - 1071
EP - 1075
JO - PLoS Medicine
JF - PLoS Medicine
SN - 1549-1277
IS - 10
ER -