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Whole genome and exome sequencing reference datasets from a multi-center and cross-platform benchmark study
by
Lu, Charles
, Zhao, Yongmei
, Chen, Xiongfong
, Petitjean, Virginie
, Sultan, Marc
, Shetty, Jyoti
, Gasparotto, Daniela
, Shi, Leming
, Xiao, Chunlin
, Choudhari, Sulbha
, Scherer, Andreas
, Peters, Eric
, Fang, Li Tai
, Hung, Tiffany
, Kriga, Yuliya
, Ren, Luyao
, Meerzaman, Daoud
, Zheng, Yuanting
, Talsania, Keyur
, Vojta, Petr
, Drabek, Jiri
, Hong, Huixiao
, Mason, Christopher E.
, Maestro, Roberta
, Idler, Kenneth
, Reimann, Ene
, Liljedahl, Ulrika
, Xiao, Wenming
, Jaeger, Erich
, Kõks, Sulev
, Tran, Bao
, Foox, Jonathan
, Zhu, Bin
, Chen, Wanqiu
, Nordlund, Jessica
, Shen, Tsai-wei
, Wang, Charles
, Chen, Zhong
in
631/114/1314
/ 631/553/2697
/ 631/61/212/2166
/ Benchmarking
/ Bioinformatics
/ Cancer
/ Cell Line, Tumor
/ Computational Biology
/ Data Descriptor
/ Genome, Human
/ Genomes
/ Genomics
/ Humanities and Social Sciences
/ Humans
/ multidisciplinary
/ Mutation
/ Neoplasms - genetics
/ Next-generation sequencing
/ Oncology
/ Precision Medicine
/ Reproducibility
/ Science
/ Science (multidisciplinary)
/ Tumors
/ Whole Exome Sequencing
/ Whole Genome Sequencing
2021
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Whole genome and exome sequencing reference datasets from a multi-center and cross-platform benchmark study
by
Lu, Charles
, Zhao, Yongmei
, Chen, Xiongfong
, Petitjean, Virginie
, Sultan, Marc
, Shetty, Jyoti
, Gasparotto, Daniela
, Shi, Leming
, Xiao, Chunlin
, Choudhari, Sulbha
, Scherer, Andreas
, Peters, Eric
, Fang, Li Tai
, Hung, Tiffany
, Kriga, Yuliya
, Ren, Luyao
, Meerzaman, Daoud
, Zheng, Yuanting
, Talsania, Keyur
, Vojta, Petr
, Drabek, Jiri
, Hong, Huixiao
, Mason, Christopher E.
, Maestro, Roberta
, Idler, Kenneth
, Reimann, Ene
, Liljedahl, Ulrika
, Xiao, Wenming
, Jaeger, Erich
, Kõks, Sulev
, Tran, Bao
, Foox, Jonathan
, Zhu, Bin
, Chen, Wanqiu
, Nordlund, Jessica
, Shen, Tsai-wei
, Wang, Charles
, Chen, Zhong
in
631/114/1314
/ 631/553/2697
/ 631/61/212/2166
/ Benchmarking
/ Bioinformatics
/ Cancer
/ Cell Line, Tumor
/ Computational Biology
/ Data Descriptor
/ Genome, Human
/ Genomes
/ Genomics
/ Humanities and Social Sciences
/ Humans
/ multidisciplinary
/ Mutation
/ Neoplasms - genetics
/ Next-generation sequencing
/ Oncology
/ Precision Medicine
/ Reproducibility
/ Science
/ Science (multidisciplinary)
/ Tumors
/ Whole Exome Sequencing
/ Whole Genome Sequencing
2021
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Whole genome and exome sequencing reference datasets from a multi-center and cross-platform benchmark study
by
Lu, Charles
, Zhao, Yongmei
, Chen, Xiongfong
, Petitjean, Virginie
, Sultan, Marc
, Shetty, Jyoti
, Gasparotto, Daniela
, Shi, Leming
, Xiao, Chunlin
, Choudhari, Sulbha
, Scherer, Andreas
, Peters, Eric
, Fang, Li Tai
, Hung, Tiffany
, Kriga, Yuliya
, Ren, Luyao
, Meerzaman, Daoud
, Zheng, Yuanting
, Talsania, Keyur
, Vojta, Petr
, Drabek, Jiri
, Hong, Huixiao
, Mason, Christopher E.
, Maestro, Roberta
, Idler, Kenneth
, Reimann, Ene
, Liljedahl, Ulrika
, Xiao, Wenming
, Jaeger, Erich
, Kõks, Sulev
, Tran, Bao
, Foox, Jonathan
, Zhu, Bin
, Chen, Wanqiu
, Nordlund, Jessica
, Shen, Tsai-wei
, Wang, Charles
, Chen, Zhong
in
631/114/1314
/ 631/553/2697
/ 631/61/212/2166
/ Benchmarking
/ Bioinformatics
/ Cancer
/ Cell Line, Tumor
/ Computational Biology
/ Data Descriptor
/ Genome, Human
/ Genomes
/ Genomics
/ Humanities and Social Sciences
/ Humans
/ multidisciplinary
/ Mutation
/ Neoplasms - genetics
/ Next-generation sequencing
/ Oncology
/ Precision Medicine
/ Reproducibility
/ Science
/ Science (multidisciplinary)
/ Tumors
/ Whole Exome Sequencing
/ Whole Genome Sequencing
2021
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Whole genome and exome sequencing reference datasets from a multi-center and cross-platform benchmark study
Journal Article
Whole genome and exome sequencing reference datasets from a multi-center and cross-platform benchmark study
2021
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Overview
With the rapid advancement of sequencing technologies, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples and generated whole-genome (WGS) and whole-exome sequencing (WES) data using sixteen library protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies.
Measurement(s)
Somatic Mutation Analysis
Technology Type(s)
whole genome sequencing • Whole Exome Sequencing
Factor Type(s)
sequencing platform • sample prepration • library preparation • bioinformatics method
Sample Characteristic - Organism
Homo sapiens
Machine-accessible metadata file describing the reported data:
https://doi.org/10.6084/m9.figshare.16713655
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