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What is the impact of assay failure in your laboratory and how do you monitor for it? The advancement of next-generation sequencing has provided invaluable resources to researchers in multiple industries and disciplines, and will be a major driver during the personalized medicine revolution that is upon us. However, while the cost of generating sequencing data continues to decrease this does not take into account the significant costs associated with the infrastructure and expertise that are required to develop a robust, routine NGS pipeline. Specifically, as predicted by Sboner, et al in 2011, the cost of the sequencing portion of the experiment continues to decrease and the costs associated with upfront experimental design and downstream analysis dominate the cost of each assay. This is true whether you are performing a pre-clinical R&D project, and perhaps even more so for clinical assays. In the paper, the authors note the unpredictable and considerable ‘human time’ spent on the upstream design and downstream analysis. Here at Horizon, we aim to develop tools that help researchers and clinicians optimize these workflows to make NGS more reliable and ultimately, more affordable by streamlining these resource intensive areas.
Understanding and controlling for sample and platform biases in NGS assays
Understanding and controlling for sample and platform biases in NGS assays
Candy Smellie
High throughput sequencing technologies has made whole genome sequencing and resequencing available to many more researchers and projects. Cost and time have been greatly reduced. The error profiles and limitations of the new platforms differ significantly from those of previous sequencing technologies. The selection of an appropriate sequencing platform for particular types of experiments is an important consideration. NGS sequencing errors focuses mainly on the following points: 1.Low quality bases 2.PCR errors 3.High Error rate NGS has inherent limitations they are as follows : 1.Sequence properties and algorithmic challenges 2.Contamination or new insertions 3.Repeat content 4.Segmental duplications 5.Missing and fragmented genes 6.Reference index
Errors and Limitaions of Next Generation Sequencing
Errors and Limitaions of Next Generation Sequencing
Nixon Mendez
Aug2015 deanna church analytical validation
Aug2015 deanna church analytical validation
Aug2015 deanna church analytical validation
GenomeInABottle
Illumina-General-Overview-Q1-17
Illumina-General-Overview-Q1-17
Matthew Holguin
Talk on High-Throughput Sequencing: Overview and Selected Applications for Masters students. Nov 9th 2011
High-Throughput Sequencing
High-Throughput Sequencing
Mark Pallen
Tutorial for the analysis of DNA-seq data. Application in Hereditary cancer.
Bioinformatics tools for NGS data analysis
Bioinformatics tools for NGS data analysis
Despoina Kalfakakou
Course: Bioinformatics for Biomedical Research (2014). Session: 2.1.2- Next Generation Sequencing. Technologies and Applications. Part II: NGS Applications I. Statistics and Bioinformatisc Unit (UEB) & High Technology Unit (UAT) from Vall d'Hebron Research Institute (www.vhir.org), Barcelona.
NGS Applications I (UEB-UAT Bioinformatics Course - Session 2.1.2 - VHIR, Bar...
NGS Applications I (UEB-UAT Bioinformatics Course - Session 2.1.2 - VHIR, Bar...
VHIR Vall d’Hebron Institut de Recerca
Since its inception, next-generation sequencing has found utility in a diverse set of industries, from biomarker discovery in pharma to ancestral identification in archeology. Across the board, NGS has the advantage of allowing us to answer questions that require a lot of data. Next-generation sequencing provides orders of magnitude more data than traditional Sanger sequencing as hundreds of “lanes” analyzed in parallel vs. hundreds of millions of “clusters” which allows for many samples to be multiplexed on a single-run. By starting with different genetic material and following specific experimental workflows, NGS can be applied to many applications. Here we focus on DNA resequencing applications, which implies the data generated will be compared to an existing reference sequence (such as the human genome). Specifically, we’ll focus on how we can analyze patient-derived material to identify onco-relevant mutations including single-nucleotide variants, insertions-deletions, copy number variants and translocations. We’ll also focus on how known reference standards have been shown to be vital in ensuring data generated from NGS assays is accurate and reproducible.
Molecular QC: Using Reference Standards in NGS Pipelines
Molecular QC: Using Reference Standards in NGS Pipelines
Candy Smellie
Empfohlen
What is the impact of assay failure in your laboratory and how do you monitor for it? The advancement of next-generation sequencing has provided invaluable resources to researchers in multiple industries and disciplines, and will be a major driver during the personalized medicine revolution that is upon us. However, while the cost of generating sequencing data continues to decrease this does not take into account the significant costs associated with the infrastructure and expertise that are required to develop a robust, routine NGS pipeline. Specifically, as predicted by Sboner, et al in 2011, the cost of the sequencing portion of the experiment continues to decrease and the costs associated with upfront experimental design and downstream analysis dominate the cost of each assay. This is true whether you are performing a pre-clinical R&D project, and perhaps even more so for clinical assays. In the paper, the authors note the unpredictable and considerable ‘human time’ spent on the upstream design and downstream analysis. Here at Horizon, we aim to develop tools that help researchers and clinicians optimize these workflows to make NGS more reliable and ultimately, more affordable by streamlining these resource intensive areas.
Understanding and controlling for sample and platform biases in NGS assays
Understanding and controlling for sample and platform biases in NGS assays
Candy Smellie
High throughput sequencing technologies has made whole genome sequencing and resequencing available to many more researchers and projects. Cost and time have been greatly reduced. The error profiles and limitations of the new platforms differ significantly from those of previous sequencing technologies. The selection of an appropriate sequencing platform for particular types of experiments is an important consideration. NGS sequencing errors focuses mainly on the following points: 1.Low quality bases 2.PCR errors 3.High Error rate NGS has inherent limitations they are as follows : 1.Sequence properties and algorithmic challenges 2.Contamination or new insertions 3.Repeat content 4.Segmental duplications 5.Missing and fragmented genes 6.Reference index
Errors and Limitaions of Next Generation Sequencing
Errors and Limitaions of Next Generation Sequencing
Nixon Mendez
Aug2015 deanna church analytical validation
Aug2015 deanna church analytical validation
Aug2015 deanna church analytical validation
GenomeInABottle
Illumina-General-Overview-Q1-17
Illumina-General-Overview-Q1-17
Matthew Holguin
Talk on High-Throughput Sequencing: Overview and Selected Applications for Masters students. Nov 9th 2011
High-Throughput Sequencing
High-Throughput Sequencing
Mark Pallen
Tutorial for the analysis of DNA-seq data. Application in Hereditary cancer.
Bioinformatics tools for NGS data analysis
Bioinformatics tools for NGS data analysis
Despoina Kalfakakou
Course: Bioinformatics for Biomedical Research (2014). Session: 2.1.2- Next Generation Sequencing. Technologies and Applications. Part II: NGS Applications I. Statistics and Bioinformatisc Unit (UEB) & High Technology Unit (UAT) from Vall d'Hebron Research Institute (www.vhir.org), Barcelona.
NGS Applications I (UEB-UAT Bioinformatics Course - Session 2.1.2 - VHIR, Bar...
NGS Applications I (UEB-UAT Bioinformatics Course - Session 2.1.2 - VHIR, Bar...
VHIR Vall d’Hebron Institut de Recerca
Since its inception, next-generation sequencing has found utility in a diverse set of industries, from biomarker discovery in pharma to ancestral identification in archeology. Across the board, NGS has the advantage of allowing us to answer questions that require a lot of data. Next-generation sequencing provides orders of magnitude more data than traditional Sanger sequencing as hundreds of “lanes” analyzed in parallel vs. hundreds of millions of “clusters” which allows for many samples to be multiplexed on a single-run. By starting with different genetic material and following specific experimental workflows, NGS can be applied to many applications. Here we focus on DNA resequencing applications, which implies the data generated will be compared to an existing reference sequence (such as the human genome). Specifically, we’ll focus on how we can analyze patient-derived material to identify onco-relevant mutations including single-nucleotide variants, insertions-deletions, copy number variants and translocations. We’ll also focus on how known reference standards have been shown to be vital in ensuring data generated from NGS assays is accurate and reproducible.
Molecular QC: Using Reference Standards in NGS Pipelines
Molecular QC: Using Reference Standards in NGS Pipelines
Candy Smellie
Next generation sequencing
overview on Next generation sequencing in breast csncer
overview on Next generation sequencing in breast csncer
Seham Al-Shehri
ABRF update
Aug2014 abrf interlaboratory study plans
Aug2014 abrf interlaboratory study plans
GenomeInABottle
As next generation sequencing has moved into the clinic, there is an increased demand for accuracy and reproducibility. Target enrichment is needed for applications where high read depth is critical, but some performance limitations, especially in GC-rich regions of the genome, have raised questions about the overall usefulness of target capture methods. In this presentation, Dr Kristina Giorda presents a method using individually synthesized and quality checked capture baits that performs well, even for GC-rich sequences, and delivers accurate coverage of the target space. Dr Giorda covers library preparation and target capture, and shares informative data generated using our xGen® Exome Research Panel.
Analyzing the exome—focusing your NGS analysis with high performance target c...
Analyzing the exome—focusing your NGS analysis with high performance target c...
Integrated DNA Technologies
Next Generation Sequencing for Cancer Genomics 101
20170209 ngs for_cancer_genomics_101
20170209 ngs for_cancer_genomics_101
Ino de Bruijn
140127 abrf interlaboratory study proposal
140127 abrf interlaboratory study proposal
GenomeInABottle
Presented at Cornell Symbiosis symposium. Workflow for processing amplicon based 16S/ITS sequences as well as whole genome shotgun sequences are described. Slides include short description and links for each tool. DISCLAIMER: This is a small subset of tools out there. No disrespect to methods not mentioned.
Tools for Metagenomics with 16S/ITS and Whole Genome Shotgun Sequences
Tools for Metagenomics with 16S/ITS and Whole Genome Shotgun Sequences
Surya Saha
Aug2013 Heidi Rehm integrating large scale sequencing into clinical practice
Aug2013 Heidi Rehm integrating large scale sequencing into clinical practice
GenomeInABottle
This slidedeck details two comprehensive informatics solutions — the Biomedical Genomics Workbench and Ingenuity Knowledge Base Variant Analysis platforms. We show the intuitive user interface of CLC Cancer Research Workbench and demonstrate how the rich biological content from Ingenuity Knowledge Base helps you rapidly identify critical variants in your samples.
Advanced NGS Data Analysis & Interpretation- BGW + IVA: NGS Tech Overview Web...
Advanced NGS Data Analysis & Interpretation- BGW + IVA: NGS Tech Overview Web...
QIAGEN
Over the past 5 years, single-cell genomics have become a powerful technology for studying small samples and rare cells, and for dissecting complex populations such as heterogeneous tumors. Single-cell technology is enabling many new insights into diverse research areas from oncology, immunology and microbiology to neuroscience, stem cell and developmental biology. This webinar introduces single-cell technology and summarizes the newest scientific applications in various research areas, all in the context of current literature.
Advances and Applications Enabled by Single Cell Technology
Advances and Applications Enabled by Single Cell Technology
QIAGEN
High sequencing depth may increase the sensitivity of variant detection for bulk samples, but it has not proven appropriate for single cell sequencing. What’s more, it makes whole genome sequencing prohibitively expensive. For variant detection in rare cells, such as circulating tumor cells, Zhang et al. recently presented a brilliant way to overcome these challenges: low depth sequencing of multiple single cells and census-based variant detection. For your convenience, we’ve summarized the concept in a new infographic.
Achieve improved variant detection in single cell sequencing infographic
Achieve improved variant detection in single cell sequencing infographic
QIAGEN
Sophie F. summer Poster Final
Sophie F. summer Poster Final
Sophie Friedheim
Summary trends of NGS in PGS
Next generation sequencing in preimplantation genetic screening (NGS in PGS)
Next generation sequencing in preimplantation genetic screening (NGS in PGS)
Mahidol University, Thailand
ASLO 2017 Aquatic Sciences Meeting: Mountains to the Sea; Feb 26 - Mar 3; Honolulu, Hawai’i, USA; Invited talk
A decade into Next Generation Sequencing on marine non-model organisms: curre...
A decade into Next Generation Sequencing on marine non-model organisms: curre...
Alexander Jueterbock
Ngs part ii 2013
Ngs part ii 2013
Elsa von Licy
Next generation sequencing: research opportunities and bioinformatic challenges. A seminar I gave for the Computational Life Science (Univ. of Oslo) seminar series, March 2, 2011
NGS: bioinformatic challenges
NGS: bioinformatic challenges
Lex Nederbragt
Metagenomics is the study of metagenomes, genetic material recovered directly from environmental samples. The broad field was referred to as environmental genomics, ecogenomics or community genomics. Recent studies use "shotgun" Sanger sequencing or next generation sequencing (NGS) to get largely unbiased samples of all genes from all the members of the sampled communities.
Metagenomics sequencing
Metagenomics sequencing
cdgenomics525
Infectious diseases are a major public health concern causing over 3.5 million deaths worldwide. Diagnosing patients as quickly and effectively as possible is crucial for managing disease outbreaks. Next-generation sequencing (NGS) provides unique capabilities to understand the genetic profile of infectious disease patients that no other technology can match. Whole-genome metagenomics allows clinicians to take a deeper dive into pathogens by generating big-data about their characteristics. This data can be rapidly analyzed using complex bioinformatics software algorithms to achieve clinical-grade diagnostic accuracy. In a healthcare system shifting towards personalized medicine, NGS can provide clinicians the tools that they need to prescribe individualized treatments to save patients who were previously untreatable. The result is improved quality of care, better treatment regimes, and cost-saving healthcare.
NGS for Infectious Disease Diagnostics: An Opportunity for Growth
NGS for Infectious Disease Diagnostics: An Opportunity for Growth
Alira Health
SANGER SEQUENCING - 1st generation sequencing Sanger Sequencing Workflow: PCR amplification (target enrichment) PCR purification (primer, dNTPs) Sequencing reaction (bi-directional) Sequencing purification (primer, dNTPs, ddNTPs) Electrophoretic run on sequencer Sequencing lecture Alignment to reference SANGER SEQUENCING: LIMITATIONS Analytical sensitivity*: 99% PCR-Based no detection deletion/duplication rearrangements del/dup BRCA = 4-28% of all BRCA mutations in most population** Level of mosaicism > 20% Low throughput (82496 capillary tubes) Labor intensive Time consuming High cost (large size gene or more genes)
20160219 - S. De Toffol - Dal Sanger al NGS nello studio delle mutazioni BRCA