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Performance assessment of DNA sequencing platforms in the ABRF Next-Generation Sequencing Study
by
Sedlazeck, Fritz J.
, Herbert, Zachary T.
, Nicolet, Charles M.
, Grills, George S.
, Levy, Shawn
, Tighe, Scott W.
, Farmerie, William
, Lu, Haorong
, Khayat, Michael M.
, Laaguiby, Phoebe K.
, Teng, Fei
, Alonso, Alicia
, Xiang, Jenny
, Byrska-Bishop, Marta
, Mason, Christopher E.
, Clarke, Wayne E.
, Zhao, Xia
, Baldwin, Don A.
, Warner, Derek
, Zook, Justin M.
, Mahmoud, Medhat
, Jen, Jin
, Zhang, Wenwei
, Zhao, Yonggang
, Foox, Jonathan
, Narzisi, Giuseppe
, Schroth, Gary P.
in
631/1647/48
/ 631/208/514/2254
/ 631/61/212
/ 631/61/514/1948
/ Agriculture
/ Analysis
/ Base Pair Mismatch
/ Benchmarking
/ Benchmarks
/ Bioinformatics
/ Biomedical and Life Sciences
/ Biomedical Engineering/Biotechnology
/ Biomedicine
/ Biotechnology
/ Deoxyribonucleic acid
/ Design of experiments
/ DNA
/ DNA - genetics
/ DNA sequencing
/ DNA, Bacterial - genetics
/ Experimental design
/ Forecasts and trends
/ Gene mapping
/ Genetic testing
/ Genome, Bacterial
/ Genome, Human
/ High-Throughput Nucleotide Sequencing - methods
/ High-Throughput Nucleotide Sequencing - standards
/ Humans
/ Insertion
/ Life Sciences
/ Mapping
/ Metagenomics
/ Methods
/ Next-generation sequencing
/ Nucleotide sequencing
/ Performance assessment
/ Performance-based assessment
/ Platforms
/ Reference materials
/ Sequence Analysis, DNA - methods
/ Sequence Analysis, DNA - standards
2021
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Performance assessment of DNA sequencing platforms in the ABRF Next-Generation Sequencing Study
by
Sedlazeck, Fritz J.
, Herbert, Zachary T.
, Nicolet, Charles M.
, Grills, George S.
, Levy, Shawn
, Tighe, Scott W.
, Farmerie, William
, Lu, Haorong
, Khayat, Michael M.
, Laaguiby, Phoebe K.
, Teng, Fei
, Alonso, Alicia
, Xiang, Jenny
, Byrska-Bishop, Marta
, Mason, Christopher E.
, Clarke, Wayne E.
, Zhao, Xia
, Baldwin, Don A.
, Warner, Derek
, Zook, Justin M.
, Mahmoud, Medhat
, Jen, Jin
, Zhang, Wenwei
, Zhao, Yonggang
, Foox, Jonathan
, Narzisi, Giuseppe
, Schroth, Gary P.
in
631/1647/48
/ 631/208/514/2254
/ 631/61/212
/ 631/61/514/1948
/ Agriculture
/ Analysis
/ Base Pair Mismatch
/ Benchmarking
/ Benchmarks
/ Bioinformatics
/ Biomedical and Life Sciences
/ Biomedical Engineering/Biotechnology
/ Biomedicine
/ Biotechnology
/ Deoxyribonucleic acid
/ Design of experiments
/ DNA
/ DNA - genetics
/ DNA sequencing
/ DNA, Bacterial - genetics
/ Experimental design
/ Forecasts and trends
/ Gene mapping
/ Genetic testing
/ Genome, Bacterial
/ Genome, Human
/ High-Throughput Nucleotide Sequencing - methods
/ High-Throughput Nucleotide Sequencing - standards
/ Humans
/ Insertion
/ Life Sciences
/ Mapping
/ Metagenomics
/ Methods
/ Next-generation sequencing
/ Nucleotide sequencing
/ Performance assessment
/ Performance-based assessment
/ Platforms
/ Reference materials
/ Sequence Analysis, DNA - methods
/ Sequence Analysis, DNA - standards
2021
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Performance assessment of DNA sequencing platforms in the ABRF Next-Generation Sequencing Study
by
Sedlazeck, Fritz J.
, Herbert, Zachary T.
, Nicolet, Charles M.
, Grills, George S.
, Levy, Shawn
, Tighe, Scott W.
, Farmerie, William
, Lu, Haorong
, Khayat, Michael M.
, Laaguiby, Phoebe K.
, Teng, Fei
, Alonso, Alicia
, Xiang, Jenny
, Byrska-Bishop, Marta
, Mason, Christopher E.
, Clarke, Wayne E.
, Zhao, Xia
, Baldwin, Don A.
, Warner, Derek
, Zook, Justin M.
, Mahmoud, Medhat
, Jen, Jin
, Zhang, Wenwei
, Zhao, Yonggang
, Foox, Jonathan
, Narzisi, Giuseppe
, Schroth, Gary P.
in
631/1647/48
/ 631/208/514/2254
/ 631/61/212
/ 631/61/514/1948
/ Agriculture
/ Analysis
/ Base Pair Mismatch
/ Benchmarking
/ Benchmarks
/ Bioinformatics
/ Biomedical and Life Sciences
/ Biomedical Engineering/Biotechnology
/ Biomedicine
/ Biotechnology
/ Deoxyribonucleic acid
/ Design of experiments
/ DNA
/ DNA - genetics
/ DNA sequencing
/ DNA, Bacterial - genetics
/ Experimental design
/ Forecasts and trends
/ Gene mapping
/ Genetic testing
/ Genome, Bacterial
/ Genome, Human
/ High-Throughput Nucleotide Sequencing - methods
/ High-Throughput Nucleotide Sequencing - standards
/ Humans
/ Insertion
/ Life Sciences
/ Mapping
/ Metagenomics
/ Methods
/ Next-generation sequencing
/ Nucleotide sequencing
/ Performance assessment
/ Performance-based assessment
/ Platforms
/ Reference materials
/ Sequence Analysis, DNA - methods
/ Sequence Analysis, DNA - standards
2021
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Performance assessment of DNA sequencing platforms in the ABRF Next-Generation Sequencing Study
Journal Article
Performance assessment of DNA sequencing platforms in the ABRF Next-Generation Sequencing Study
2021
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Overview
Assessing the reproducibility, accuracy and utility of massively parallel DNA sequencing platforms remains an ongoing challenge. Here the Association of Biomolecular Resource Facilities (ABRF) Next-Generation Sequencing Study benchmarks the performance of a set of sequencing instruments (HiSeq/NovaSeq/paired-end 2 × 250-bp chemistry, Ion S5/Proton, PacBio circular consensus sequencing (CCS), Oxford Nanopore Technologies PromethION/MinION, BGISEQ-500/MGISEQ-2000 and GS111) on human and bacterial reference DNA samples. Among short-read instruments, HiSeq 4000 and X10 provided the most consistent, highest genome coverage, while BGI/MGISEQ provided the lowest sequencing error rates. The long-read instrument PacBio CCS had the highest reference-based mapping rate and lowest non-mapping rate. The two long-read platforms PacBio CCS and PromethION/MinION showed the best sequence mapping in repeat-rich areas and across homopolymers. NovaSeq 6000 using 2 × 250-bp read chemistry was the most robust instrument for capturing known insertion/deletion events. This study serves as a benchmark for current genomics technologies, as well as a resource to inform experimental design and next-generation sequencing variant calling.
Next-generation sequencing platforms are benchmarked using human, bacterial and metagenomics reference materials.
Publisher
Nature Publishing Group US,Nature Publishing Group
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