SlideShare a Scribd company logo
[MIT] Introduction to 2GS data analysis Drink faster ! June 23, 2011
Production Informatics and Bioinformatics June 23, 2011 Produce raw sequence reads Basic Production Informatics Map to genome and generate raw genomic features (e.g. SNPs) Advanced  Production Inform. Analyze the data; Uncover the biological meaning Bioinformatics Research Per one-flowcell project
First Generation: Sanger sequencing ,[object Object],Third Generation: single molecule sequencing Brief history of sequencing  June 23, 2011 * * * Discussion about category
What steps are involved in sequencing ? June 23, 2011 sequencing by synthesis (SBS) technology Fragmentation Library generation Amplification Sequencing Analysis Illumina Marketing:  “3h 10 minutes wet-lab 30 minutes dry lab”
Illumina sequencing: Library + Amplification June 23, 2011 “Illumina Sequencing Technology” booklet
Illumina Sequencing: Synthesis + Imaging June 23, 2011 “Illumina Sequencing Technology” booklet
Output: 1.5 Terabyte of data June 23, 2011 Inspired by anzska information booklet
Sequencer Output Conversion: Production Informatics 1.5 TB data : 6 billion clusters with 100 bp reads  	= 600 billion data points  June 23, 2011 HiSeq CASAVA … × read length For HiSeq: images are converted to flat files (*.bcl or *.cif)  visualpharm.com Maysoft
Multiplexing 6 billion reads: 750 million reads per lane Currently 12-plex (soon 96-plex): One run   June 23, 2011 Oliver Twardowski
Demultiplexing June 23, 2011 CASAVA … … × samples × read length visualpharm.com
CASAVA1.8.0 program call June 23, 2011 configureBclToFastq.pl br />	--input-dir Data/Intensities/BaseCalls/ br />    -output-dir Data/Unaligned br />	--sample-sheet SampleSheet.csv  	--use-bases-mask y100,I6nn,Y100 >file.log 2>&1 cd Data/Unaligned qsub -pe make 16 -jy -v $MYPATH –oqsub.out -cwd –N fastq -by br />    make -j 16 Runtime: ~ 6h
Fastq files June 23, 2011 @HWI-ST301_0112:1:1:1169:2044#0/1 CCATAAGGCCACGTATTTTGCAAGCTATTTAACTGGCGGCGAT +HWI-ST301_0112:1:1:1169:2044#0/1 dddcd^dd`acacdacd`ecdedabdcdddcc`bTabr />36 36 36 35 28 … ASCII       @ .. ~ DEC        64 .. 126 PHRED     0 .. 62 Phred scores are estimates only !  Cock PJ, Fields CJ, Goto N, Heuer ML, Rice PM. The Sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ variants. Nucleic Acids Res. 2010 Apr;38(6):1767-71. PMID:20015970
Fastq – PHRED quality Pathological June 23, 2011
Fastq: Quality control Base-pair quality score  Adapter contamination Uneven Amplification  June 23, 2011
Three things to remember Don’t be fooled by marketing Fastqfiles are not directly usable Basic-run QC can be made from fastq file June 23, 2011 “All modern genomics projects are now bottlenecked at the stage of data analysis rather than data production” 							Ewan Birney 		      European Bioinformatics Institute Wellcome Trust  David S. Roos  Bioinformatics--Trying to Swim in a Sea of Data;Science 16 February 2001: Vol. 291 no. 5507 pp. 1260-1261 DOI: 10.1126/science.291.5507.1260
Next Week: June 23, 2011 Abstract: This session will focus on identifying SNPs from whole genome, exome capture or targeted resequencing data. The approaches of mapping, local realigment, recalibration, SNP calling, and SNP recalibration will be introduced and quality metrics discussed.
Walk-in-clinic June 23, 2011
First Generation: Sanger sequencing ,[object Object],Third Generation: single molecule sequencing Brief history of sequencing  June 23, 2011 * * * Discussion about category
Helicos true Single Molecule Sequencing(tSMS)™ technology Sequencing by synthesis but much more sensitive so no amplification June 23, 2011
Life Technology - Ion Torrent Hydrogen Ion is released by the incorporation of a nucleotide, which is measured by a semiconductor Depending on which nucleotide wash cycle the signal coincides June 23, 2011
PacBio Immobilized polymerase at the bottom of a well Fluorescent nucleotides float around and if they are incorporated they are held still for tens of milliseconds, which is the signal that is recorded No upper limit on the length   June 23, 2011 http://www.pacificbiosciences.com/smrt-biology/smrt-technology?page=4
Nanopore Molecule is sucked through a poor and the change in the membrane charge due to the different nucleotides is recorded. June 23, 2011 http://www.nanoporetech.com/sections/index/82

More Related Content

What's hot

Dna sequencing and its types
Dna sequencing and its typesDna sequencing and its types
Dna sequencing and its types
Yuvaraj neelakandan
 
Pyrosequencing
PyrosequencingPyrosequencing
Pyrosequencing
Maheen Shamim
 
Nanopore sequencing
Nanopore sequencingNanopore sequencing
Nanopore sequencing
Leelesh singh
 
shotgun sequncing
 shotgun sequncing shotgun sequncing
shotgun sequncing
SAIFALI444
 
PCR Primer desining
PCR Primer desiningPCR Primer desining
PCR Primer desining
Karan Veer Singh
 
Next Generation Sequencing of DNA
Next Generation Sequencing of DNANext Generation Sequencing of DNA
Next Generation Sequencing of DNA
maryamshah13
 
Whole genome sequencing
Whole genome sequencingWhole genome sequencing
Whole genome sequencing
qadardana kakar
 
Finding ORF
Finding ORFFinding ORF
Finding ORF
Sabahat Ali
 
Genome sequencing
Genome sequencingGenome sequencing
Genome sequencing
Shital Pal
 
Illumina Sequencing
Illumina SequencingIllumina Sequencing
Illumina Sequencing
USD Bioinformatics
 
Third Generation Sequencing
Third Generation Sequencing Third Generation Sequencing
Third Generation Sequencing
priyanka raviraj
 
Conventional and next generation sequencing ppt
Conventional and next generation sequencing pptConventional and next generation sequencing ppt
Conventional and next generation sequencing ppt
Ashwini R
 
Ion torrent and SOLiD Sequencing Techniques
Ion torrent and SOLiD Sequencing Techniques Ion torrent and SOLiD Sequencing Techniques
Ion torrent and SOLiD Sequencing Techniques
fikrem24yahoocom6261
 
Pyrosequencing
PyrosequencingPyrosequencing
Pyrosequencing
qadardana kakar
 
DNA MICROARRAY TECHNIQUES
DNA MICROARRAY TECHNIQUESDNA MICROARRAY TECHNIQUES
DNA MICROARRAY TECHNIQUES
gayathryp1
 
Pyrosequencing
PyrosequencingPyrosequencing
Pyrosequencing
Ashfaq Ahmad
 
DNA microarray
DNA microarrayDNA microarray
DNA microarray
manojjeya
 
Next generation sequencing
Next generation sequencingNext generation sequencing
Next generation sequencing
Swathi Prabakar
 
Types of PCR
Types of PCRTypes of PCR
Types of PCR
Microbiology
 
Ion torrent sequencing
Ion torrent sequencingIon torrent sequencing
Ion torrent sequencing
SureshniFernando
 

What's hot (20)

Dna sequencing and its types
Dna sequencing and its typesDna sequencing and its types
Dna sequencing and its types
 
Pyrosequencing
PyrosequencingPyrosequencing
Pyrosequencing
 
Nanopore sequencing
Nanopore sequencingNanopore sequencing
Nanopore sequencing
 
shotgun sequncing
 shotgun sequncing shotgun sequncing
shotgun sequncing
 
PCR Primer desining
PCR Primer desiningPCR Primer desining
PCR Primer desining
 
Next Generation Sequencing of DNA
Next Generation Sequencing of DNANext Generation Sequencing of DNA
Next Generation Sequencing of DNA
 
Whole genome sequencing
Whole genome sequencingWhole genome sequencing
Whole genome sequencing
 
Finding ORF
Finding ORFFinding ORF
Finding ORF
 
Genome sequencing
Genome sequencingGenome sequencing
Genome sequencing
 
Illumina Sequencing
Illumina SequencingIllumina Sequencing
Illumina Sequencing
 
Third Generation Sequencing
Third Generation Sequencing Third Generation Sequencing
Third Generation Sequencing
 
Conventional and next generation sequencing ppt
Conventional and next generation sequencing pptConventional and next generation sequencing ppt
Conventional and next generation sequencing ppt
 
Ion torrent and SOLiD Sequencing Techniques
Ion torrent and SOLiD Sequencing Techniques Ion torrent and SOLiD Sequencing Techniques
Ion torrent and SOLiD Sequencing Techniques
 
Pyrosequencing
PyrosequencingPyrosequencing
Pyrosequencing
 
DNA MICROARRAY TECHNIQUES
DNA MICROARRAY TECHNIQUESDNA MICROARRAY TECHNIQUES
DNA MICROARRAY TECHNIQUES
 
Pyrosequencing
PyrosequencingPyrosequencing
Pyrosequencing
 
DNA microarray
DNA microarrayDNA microarray
DNA microarray
 
Next generation sequencing
Next generation sequencingNext generation sequencing
Next generation sequencing
 
Types of PCR
Types of PCRTypes of PCR
Types of PCR
 
Ion torrent sequencing
Ion torrent sequencingIon torrent sequencing
Ion torrent sequencing
 

Viewers also liked

Introduction to next generation sequencing
Introduction to next generation sequencingIntroduction to next generation sequencing
Introduction to next generation sequencing
VHIR Vall d’Hebron Institut de Recerca
 
New Generation Sequencing Technologies: an overview
New Generation Sequencing Technologies: an overviewNew Generation Sequencing Technologies: an overview
New Generation Sequencing Technologies: an overview
Paolo Dametto
 
Ngs microbiome
Ngs microbiomeNgs microbiome
Ngs microbiome
jukais
 
2013 july 25 systems biology rna seq v2
2013 july 25 systems biology rna seq v22013 july 25 systems biology rna seq v2
2013 july 25 systems biology rna seq v2
Anne Deslattes Mays
 
Variant (SNPs/Indels) calling in DNA sequences, Part 2
Variant (SNPs/Indels) calling in DNA sequences, Part 2Variant (SNPs/Indels) calling in DNA sequences, Part 2
Variant (SNPs/Indels) calling in DNA sequences, Part 2
Denis C. Bauer
 
Variant (SNPs/Indels) calling in DNA sequences, Part 1
Variant (SNPs/Indels) calling in DNA sequences, Part 1 Variant (SNPs/Indels) calling in DNA sequences, Part 1
Variant (SNPs/Indels) calling in DNA sequences, Part 1
Denis C. Bauer
 
Functionally annotate genomic variants
Functionally annotate genomic variantsFunctionally annotate genomic variants
Functionally annotate genomic variants
Denis C. Bauer
 
GRUTER가 들려주는 Big Data Platform 구축 전략과 적용 사례: Bioinformatics Data를 위한 Hadoop기반...
GRUTER가 들려주는 Big Data Platform 구축 전략과 적용 사례: Bioinformatics Data를 위한 Hadoop기반...GRUTER가 들려주는 Big Data Platform 구축 전략과 적용 사례: Bioinformatics Data를 위한 Hadoop기반...
GRUTER가 들려주는 Big Data Platform 구축 전략과 적용 사례: Bioinformatics Data를 위한 Hadoop기반...
Gruter
 
How to sequence a large eukaryotic genome
How to sequence a large eukaryotic genomeHow to sequence a large eukaryotic genome
How to sequence a large eukaryotic genome
Lex Nederbragt
 
Bridge Amplification Part 1
Bridge Amplification Part 1Bridge Amplification Part 1
Bridge Amplification Part 1
USD Bioinformatics
 
Amplicon sequencing slides - Trina McMahon - MEWE 2013
Amplicon sequencing slides - Trina McMahon - MEWE 2013Amplicon sequencing slides - Trina McMahon - MEWE 2013
Amplicon sequencing slides - Trina McMahon - MEWE 2013
mcmahonUW
 
Esa 2014 qiime
Esa 2014 qiimeEsa 2014 qiime
Esa 2014 qiime
Zech Xu
 
Histology Portfolio
Histology Portfolio Histology Portfolio
Histology Portfolio
Flavia Nodarse-Martinez
 
Introduction to Bioinformatics
Introduction to BioinformaticsIntroduction to Bioinformatics
Introduction to Bioinformatics
Denis C. Bauer
 
Genome
GenomeGenome
Genome
Gowthami R
 
Evolution of DNA Sequencing - talk by Jonathan Eisen for the Bodega Workshop ...
Evolution of DNA Sequencing - talk by Jonathan Eisen for the Bodega Workshop ...Evolution of DNA Sequencing - talk by Jonathan Eisen for the Bodega Workshop ...
Evolution of DNA Sequencing - talk by Jonathan Eisen for the Bodega Workshop ...
Jonathan Eisen
 
Data Management for Quantitative Biology - Data sources (Next generation tech...
Data Management for Quantitative Biology - Data sources (Next generation tech...Data Management for Quantitative Biology - Data sources (Next generation tech...
Data Management for Quantitative Biology - Data sources (Next generation tech...
QBiC_Tue
 
Part 1 of RNA-seq for DE analysis: Defining the goal
Part 1 of RNA-seq for DE analysis: Defining the goalPart 1 of RNA-seq for DE analysis: Defining the goal
Part 1 of RNA-seq for DE analysis: Defining the goal
Joachim Jacob
 
Feulgen stain
Feulgen stainFeulgen stain
Feulgen stain
Fatma Adel
 
Uses of Artificial Intelligence in Bioinformatics
Uses of Artificial Intelligence in BioinformaticsUses of Artificial Intelligence in Bioinformatics
Uses of Artificial Intelligence in Bioinformatics
Pragya Pai
 

Viewers also liked (20)

Introduction to next generation sequencing
Introduction to next generation sequencingIntroduction to next generation sequencing
Introduction to next generation sequencing
 
New Generation Sequencing Technologies: an overview
New Generation Sequencing Technologies: an overviewNew Generation Sequencing Technologies: an overview
New Generation Sequencing Technologies: an overview
 
Ngs microbiome
Ngs microbiomeNgs microbiome
Ngs microbiome
 
2013 july 25 systems biology rna seq v2
2013 july 25 systems biology rna seq v22013 july 25 systems biology rna seq v2
2013 july 25 systems biology rna seq v2
 
Variant (SNPs/Indels) calling in DNA sequences, Part 2
Variant (SNPs/Indels) calling in DNA sequences, Part 2Variant (SNPs/Indels) calling in DNA sequences, Part 2
Variant (SNPs/Indels) calling in DNA sequences, Part 2
 
Variant (SNPs/Indels) calling in DNA sequences, Part 1
Variant (SNPs/Indels) calling in DNA sequences, Part 1 Variant (SNPs/Indels) calling in DNA sequences, Part 1
Variant (SNPs/Indels) calling in DNA sequences, Part 1
 
Functionally annotate genomic variants
Functionally annotate genomic variantsFunctionally annotate genomic variants
Functionally annotate genomic variants
 
GRUTER가 들려주는 Big Data Platform 구축 전략과 적용 사례: Bioinformatics Data를 위한 Hadoop기반...
GRUTER가 들려주는 Big Data Platform 구축 전략과 적용 사례: Bioinformatics Data를 위한 Hadoop기반...GRUTER가 들려주는 Big Data Platform 구축 전략과 적용 사례: Bioinformatics Data를 위한 Hadoop기반...
GRUTER가 들려주는 Big Data Platform 구축 전략과 적용 사례: Bioinformatics Data를 위한 Hadoop기반...
 
How to sequence a large eukaryotic genome
How to sequence a large eukaryotic genomeHow to sequence a large eukaryotic genome
How to sequence a large eukaryotic genome
 
Bridge Amplification Part 1
Bridge Amplification Part 1Bridge Amplification Part 1
Bridge Amplification Part 1
 
Amplicon sequencing slides - Trina McMahon - MEWE 2013
Amplicon sequencing slides - Trina McMahon - MEWE 2013Amplicon sequencing slides - Trina McMahon - MEWE 2013
Amplicon sequencing slides - Trina McMahon - MEWE 2013
 
Esa 2014 qiime
Esa 2014 qiimeEsa 2014 qiime
Esa 2014 qiime
 
Histology Portfolio
Histology Portfolio Histology Portfolio
Histology Portfolio
 
Introduction to Bioinformatics
Introduction to BioinformaticsIntroduction to Bioinformatics
Introduction to Bioinformatics
 
Genome
GenomeGenome
Genome
 
Evolution of DNA Sequencing - talk by Jonathan Eisen for the Bodega Workshop ...
Evolution of DNA Sequencing - talk by Jonathan Eisen for the Bodega Workshop ...Evolution of DNA Sequencing - talk by Jonathan Eisen for the Bodega Workshop ...
Evolution of DNA Sequencing - talk by Jonathan Eisen for the Bodega Workshop ...
 
Data Management for Quantitative Biology - Data sources (Next generation tech...
Data Management for Quantitative Biology - Data sources (Next generation tech...Data Management for Quantitative Biology - Data sources (Next generation tech...
Data Management for Quantitative Biology - Data sources (Next generation tech...
 
Part 1 of RNA-seq for DE analysis: Defining the goal
Part 1 of RNA-seq for DE analysis: Defining the goalPart 1 of RNA-seq for DE analysis: Defining the goal
Part 1 of RNA-seq for DE analysis: Defining the goal
 
Feulgen stain
Feulgen stainFeulgen stain
Feulgen stain
 
Uses of Artificial Intelligence in Bioinformatics
Uses of Artificial Intelligence in BioinformaticsUses of Artificial Intelligence in Bioinformatics
Uses of Artificial Intelligence in Bioinformatics
 

Similar to Introduction to second generation sequencing

Mouse Genomes Project Summary June 2010
Mouse Genomes Project Summary June 2010Mouse Genomes Project Summary June 2010
Mouse Genomes Project Summary June 2010
Thomas Keane
 
Apollo Collaborative genome annotation editing
Apollo Collaborative genome annotation editing Apollo Collaborative genome annotation editing
Apollo Collaborative genome annotation editing
Monica Munoz-Torres
 
Genome Assembly
Genome AssemblyGenome Assembly
Genome Assembly
Aureliano Bombarely
 
DNA sequencing: rapid improvements and their implications
DNA sequencing: rapid improvements and their implicationsDNA sequencing: rapid improvements and their implications
DNA sequencing: rapid improvements and their implications
Jeffrey Funk
 
Processing Amplicon Sequence Data for the Analysis of Microbial Communities
Processing Amplicon Sequence Data for the Analysis of Microbial CommunitiesProcessing Amplicon Sequence Data for the Analysis of Microbial Communities
Processing Amplicon Sequence Data for the Analysis of Microbial Communities
Martin Hartmann
 
03_Microbio590B_sequencing_2022.pdf
03_Microbio590B_sequencing_2022.pdf03_Microbio590B_sequencing_2022.pdf
03_Microbio590B_sequencing_2022.pdf
Kristen DeAngelis
 
2015 09-29-sbc322-methods.key
2015 09-29-sbc322-methods.key2015 09-29-sbc322-methods.key
2015 09-29-sbc322-methods.key
Yannick Wurm
 
The Transformation of Systems Biology Into A Large Data Science
The Transformation of Systems Biology Into A Large Data ScienceThe Transformation of Systems Biology Into A Large Data Science
The Transformation of Systems Biology Into A Large Data Science
Robert Grossman
 
Comparison between RNASeq and Microarray for Gene Expression Analysis
Comparison between RNASeq and Microarray for Gene Expression AnalysisComparison between RNASeq and Microarray for Gene Expression Analysis
Comparison between RNASeq and Microarray for Gene Expression Analysis
Yaoyu Wang
 
Jan2016 pac bio giab
Jan2016 pac bio giabJan2016 pac bio giab
Jan2016 pac bio giab
GenomeInABottle
 
White Paper: Next-Generation Genome Sequencing Using EMC Isilon Scale-Out NAS...
White Paper: Next-Generation Genome Sequencing Using EMC Isilon Scale-Out NAS...White Paper: Next-Generation Genome Sequencing Using EMC Isilon Scale-Out NAS...
White Paper: Next-Generation Genome Sequencing Using EMC Isilon Scale-Out NAS...
EMC
 
Introduction to Next-Generation Sequencing (NGS) Technology
Introduction to Next-Generation Sequencing (NGS) TechnologyIntroduction to Next-Generation Sequencing (NGS) Technology
Introduction to Next-Generation Sequencing (NGS) Technology
QIAGEN
 
Avila et al 2010 wnt 3
Avila et al 2010 wnt 3Avila et al 2010 wnt 3
Avila et al 2010 wnt 3
Jorge Parodi
 
Examining gene expression and methylation with next gen sequencing
Examining gene expression and methylation with next gen sequencingExamining gene expression and methylation with next gen sequencing
Examining gene expression and methylation with next gen sequencing
Stephen Turner
 
A Journey Through The History Of DNA Sequencing
A Journey Through The History Of DNA Sequencing A Journey Through The History Of DNA Sequencing
A Journey Through The History Of DNA Sequencing
Eurofins Genomics Germany GmbH
 
BioSB meeting 2015
BioSB meeting 2015BioSB meeting 2015
BioSB meeting 2015
hansjansen9999
 
Microarray biotechnologg ppy dna microarrays
Microarray biotechnologg ppy dna microarraysMicroarray biotechnologg ppy dna microarrays
Microarray biotechnologg ppy dna microarrays
ayeshasattarsandhu
 
GMI proficiency testing- Progress report 2016
GMI proficiency testing- Progress report 2016GMI proficiency testing- Progress report 2016
GMI proficiency testing- Progress report 2016
ExternalEvents
 
Sequence based Markers
Sequence based MarkersSequence based Markers
Sequence based Markers
sukruthaa
 
EVE161: Microbial Phylogenomics - Class 2 - Evolution of DNA Sequencing
EVE161: Microbial Phylogenomics - Class 2 - Evolution of DNA SequencingEVE161: Microbial Phylogenomics - Class 2 - Evolution of DNA Sequencing
EVE161: Microbial Phylogenomics - Class 2 - Evolution of DNA Sequencing
Jonathan Eisen
 

Similar to Introduction to second generation sequencing (20)

Mouse Genomes Project Summary June 2010
Mouse Genomes Project Summary June 2010Mouse Genomes Project Summary June 2010
Mouse Genomes Project Summary June 2010
 
Apollo Collaborative genome annotation editing
Apollo Collaborative genome annotation editing Apollo Collaborative genome annotation editing
Apollo Collaborative genome annotation editing
 
Genome Assembly
Genome AssemblyGenome Assembly
Genome Assembly
 
DNA sequencing: rapid improvements and their implications
DNA sequencing: rapid improvements and their implicationsDNA sequencing: rapid improvements and their implications
DNA sequencing: rapid improvements and their implications
 
Processing Amplicon Sequence Data for the Analysis of Microbial Communities
Processing Amplicon Sequence Data for the Analysis of Microbial CommunitiesProcessing Amplicon Sequence Data for the Analysis of Microbial Communities
Processing Amplicon Sequence Data for the Analysis of Microbial Communities
 
03_Microbio590B_sequencing_2022.pdf
03_Microbio590B_sequencing_2022.pdf03_Microbio590B_sequencing_2022.pdf
03_Microbio590B_sequencing_2022.pdf
 
2015 09-29-sbc322-methods.key
2015 09-29-sbc322-methods.key2015 09-29-sbc322-methods.key
2015 09-29-sbc322-methods.key
 
The Transformation of Systems Biology Into A Large Data Science
The Transformation of Systems Biology Into A Large Data ScienceThe Transformation of Systems Biology Into A Large Data Science
The Transformation of Systems Biology Into A Large Data Science
 
Comparison between RNASeq and Microarray for Gene Expression Analysis
Comparison between RNASeq and Microarray for Gene Expression AnalysisComparison between RNASeq and Microarray for Gene Expression Analysis
Comparison between RNASeq and Microarray for Gene Expression Analysis
 
Jan2016 pac bio giab
Jan2016 pac bio giabJan2016 pac bio giab
Jan2016 pac bio giab
 
White Paper: Next-Generation Genome Sequencing Using EMC Isilon Scale-Out NAS...
White Paper: Next-Generation Genome Sequencing Using EMC Isilon Scale-Out NAS...White Paper: Next-Generation Genome Sequencing Using EMC Isilon Scale-Out NAS...
White Paper: Next-Generation Genome Sequencing Using EMC Isilon Scale-Out NAS...
 
Introduction to Next-Generation Sequencing (NGS) Technology
Introduction to Next-Generation Sequencing (NGS) TechnologyIntroduction to Next-Generation Sequencing (NGS) Technology
Introduction to Next-Generation Sequencing (NGS) Technology
 
Avila et al 2010 wnt 3
Avila et al 2010 wnt 3Avila et al 2010 wnt 3
Avila et al 2010 wnt 3
 
Examining gene expression and methylation with next gen sequencing
Examining gene expression and methylation with next gen sequencingExamining gene expression and methylation with next gen sequencing
Examining gene expression and methylation with next gen sequencing
 
A Journey Through The History Of DNA Sequencing
A Journey Through The History Of DNA Sequencing A Journey Through The History Of DNA Sequencing
A Journey Through The History Of DNA Sequencing
 
BioSB meeting 2015
BioSB meeting 2015BioSB meeting 2015
BioSB meeting 2015
 
Microarray biotechnologg ppy dna microarrays
Microarray biotechnologg ppy dna microarraysMicroarray biotechnologg ppy dna microarrays
Microarray biotechnologg ppy dna microarrays
 
GMI proficiency testing- Progress report 2016
GMI proficiency testing- Progress report 2016GMI proficiency testing- Progress report 2016
GMI proficiency testing- Progress report 2016
 
Sequence based Markers
Sequence based MarkersSequence based Markers
Sequence based Markers
 
EVE161: Microbial Phylogenomics - Class 2 - Evolution of DNA Sequencing
EVE161: Microbial Phylogenomics - Class 2 - Evolution of DNA SequencingEVE161: Microbial Phylogenomics - Class 2 - Evolution of DNA Sequencing
EVE161: Microbial Phylogenomics - Class 2 - Evolution of DNA Sequencing
 

More from Denis C. Bauer

Cloud-native machine learning - Transforming bioinformatics research
Cloud-native machine learning - Transforming bioinformatics research Cloud-native machine learning - Transforming bioinformatics research
Cloud-native machine learning - Transforming bioinformatics research
Denis C. Bauer
 
Translating genomics into clinical practice - 2018 AWS summit keynote
Translating genomics into clinical practice - 2018 AWS summit keynoteTranslating genomics into clinical practice - 2018 AWS summit keynote
Translating genomics into clinical practice - 2018 AWS summit keynote
Denis C. Bauer
 
Going Server-less for Web-Services that need to Crunch Large Volumes of Data
Going Server-less for Web-Services that need to Crunch Large Volumes of DataGoing Server-less for Web-Services that need to Crunch Large Volumes of Data
Going Server-less for Web-Services that need to Crunch Large Volumes of Data
Denis C. Bauer
 
How novel compute technology transforms life science research
How novel compute technology transforms life science researchHow novel compute technology transforms life science research
How novel compute technology transforms life science research
Denis C. Bauer
 
How novel compute technology transforms life science research
How novel compute technology transforms life science researchHow novel compute technology transforms life science research
How novel compute technology transforms life science research
Denis C. Bauer
 
VariantSpark: applying Spark-based machine learning methods to genomic inform...
VariantSpark: applying Spark-based machine learning methods to genomic inform...VariantSpark: applying Spark-based machine learning methods to genomic inform...
VariantSpark: applying Spark-based machine learning methods to genomic inform...
Denis C. Bauer
 
Population-scale high-throughput sequencing data analysis
Population-scale high-throughput sequencing data analysisPopulation-scale high-throughput sequencing data analysis
Population-scale high-throughput sequencing data analysis
Denis C. Bauer
 
Trip Report Seattle
Trip Report SeattleTrip Report Seattle
Trip Report Seattle
Denis C. Bauer
 
Allelic Imbalance for Pre-capture Whole Exome Sequencing
Allelic Imbalance for Pre-capture Whole Exome SequencingAllelic Imbalance for Pre-capture Whole Exome Sequencing
Allelic Imbalance for Pre-capture Whole Exome Sequencing
Denis C. Bauer
 
Centralizing sequence analysis
Centralizing sequence analysisCentralizing sequence analysis
Centralizing sequence analysis
Denis C. Bauer
 
Qbi Centre for Brain genomics (Informatics side)
Qbi Centre for Brain genomics (Informatics side)Qbi Centre for Brain genomics (Informatics side)
Qbi Centre for Brain genomics (Informatics side)
Denis C. Bauer
 
Differential gene expression
Differential gene expressionDifferential gene expression
Differential gene expression
Denis C. Bauer
 
Transcript detection in RNAseq
Transcript detection in RNAseqTranscript detection in RNAseq
Transcript detection in RNAseq
Denis C. Bauer
 
The missing data issue for HiSeq runs
The missing data issue for HiSeq runsThe missing data issue for HiSeq runs
The missing data issue for HiSeq runs
Denis C. Bauer
 
Deciphering the regulatory code in the genome
Deciphering the regulatory code in the genomeDeciphering the regulatory code in the genome
Deciphering the regulatory code in the genome
Denis C. Bauer
 
ReliF
ReliFReliF
STAR: Recombination site prediction
STAR: Recombination site predictionSTAR: Recombination site prediction
STAR: Recombination site prediction
Denis C. Bauer
 
SUMOylation site prediction
SUMOylation site predictionSUMOylation site prediction
SUMOylation site prediction
Denis C. Bauer
 

More from Denis C. Bauer (18)

Cloud-native machine learning - Transforming bioinformatics research
Cloud-native machine learning - Transforming bioinformatics research Cloud-native machine learning - Transforming bioinformatics research
Cloud-native machine learning - Transforming bioinformatics research
 
Translating genomics into clinical practice - 2018 AWS summit keynote
Translating genomics into clinical practice - 2018 AWS summit keynoteTranslating genomics into clinical practice - 2018 AWS summit keynote
Translating genomics into clinical practice - 2018 AWS summit keynote
 
Going Server-less for Web-Services that need to Crunch Large Volumes of Data
Going Server-less for Web-Services that need to Crunch Large Volumes of DataGoing Server-less for Web-Services that need to Crunch Large Volumes of Data
Going Server-less for Web-Services that need to Crunch Large Volumes of Data
 
How novel compute technology transforms life science research
How novel compute technology transforms life science researchHow novel compute technology transforms life science research
How novel compute technology transforms life science research
 
How novel compute technology transforms life science research
How novel compute technology transforms life science researchHow novel compute technology transforms life science research
How novel compute technology transforms life science research
 
VariantSpark: applying Spark-based machine learning methods to genomic inform...
VariantSpark: applying Spark-based machine learning methods to genomic inform...VariantSpark: applying Spark-based machine learning methods to genomic inform...
VariantSpark: applying Spark-based machine learning methods to genomic inform...
 
Population-scale high-throughput sequencing data analysis
Population-scale high-throughput sequencing data analysisPopulation-scale high-throughput sequencing data analysis
Population-scale high-throughput sequencing data analysis
 
Trip Report Seattle
Trip Report SeattleTrip Report Seattle
Trip Report Seattle
 
Allelic Imbalance for Pre-capture Whole Exome Sequencing
Allelic Imbalance for Pre-capture Whole Exome SequencingAllelic Imbalance for Pre-capture Whole Exome Sequencing
Allelic Imbalance for Pre-capture Whole Exome Sequencing
 
Centralizing sequence analysis
Centralizing sequence analysisCentralizing sequence analysis
Centralizing sequence analysis
 
Qbi Centre for Brain genomics (Informatics side)
Qbi Centre for Brain genomics (Informatics side)Qbi Centre for Brain genomics (Informatics side)
Qbi Centre for Brain genomics (Informatics side)
 
Differential gene expression
Differential gene expressionDifferential gene expression
Differential gene expression
 
Transcript detection in RNAseq
Transcript detection in RNAseqTranscript detection in RNAseq
Transcript detection in RNAseq
 
The missing data issue for HiSeq runs
The missing data issue for HiSeq runsThe missing data issue for HiSeq runs
The missing data issue for HiSeq runs
 
Deciphering the regulatory code in the genome
Deciphering the regulatory code in the genomeDeciphering the regulatory code in the genome
Deciphering the regulatory code in the genome
 
ReliF
ReliFReliF
ReliF
 
STAR: Recombination site prediction
STAR: Recombination site predictionSTAR: Recombination site prediction
STAR: Recombination site prediction
 
SUMOylation site prediction
SUMOylation site predictionSUMOylation site prediction
SUMOylation site prediction
 

Recently uploaded

Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfUnlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Malak Abu Hammad
 
Video Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the FutureVideo Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the Future
Alpen-Adria-Universität
 
20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 202420240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
Matthew Sinclair
 
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracyGraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
Tomaz Bratanic
 
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of GermanyPresentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
innovationoecd
 
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup SlidesProgramming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
Zilliz
 
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with SlackLet's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
shyamraj55
 
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
名前 です男
 
Serial Arm Control in Real Time Presentation
Serial Arm Control in Real Time PresentationSerial Arm Control in Real Time Presentation
Serial Arm Control in Real Time Presentation
tolgahangng
 
“I’m still / I’m still / Chaining from the Block”
“I’m still / I’m still / Chaining from the Block”“I’m still / I’m still / Chaining from the Block”
“I’m still / I’m still / Chaining from the Block”
Claudio Di Ciccio
 
Pushing the limits of ePRTC: 100ns holdover for 100 days
Pushing the limits of ePRTC: 100ns holdover for 100 daysPushing the limits of ePRTC: 100ns holdover for 100 days
Pushing the limits of ePRTC: 100ns holdover for 100 days
Adtran
 
Mind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AIMind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AI
Kumud Singh
 
How to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptxHow to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptx
danishmna97
 
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
Neo4j
 
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfObservability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Paige Cruz
 
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success StoryDriving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Safe Software
 
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceAI 101: An Introduction to the Basics and Impact of Artificial Intelligence
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
IndexBug
 
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
Neo4j
 
Uni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems Copilot event_05062024_C.Vlachos.pdfUni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems S.M.S.A.
 
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
Neo4j
 

Recently uploaded (20)

Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdfUnlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
Unlock the Future of Search with MongoDB Atlas_ Vector Search Unleashed.pdf
 
Video Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the FutureVideo Streaming: Then, Now, and in the Future
Video Streaming: Then, Now, and in the Future
 
20240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 202420240605 QFM017 Machine Intelligence Reading List May 2024
20240605 QFM017 Machine Intelligence Reading List May 2024
 
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracyGraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
 
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of GermanyPresentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
 
Programming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup SlidesProgramming Foundation Models with DSPy - Meetup Slides
Programming Foundation Models with DSPy - Meetup Slides
 
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with SlackLet's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slack
 
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
みなさんこんにちはこれ何文字まで入るの?40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの?えこ...
 
Serial Arm Control in Real Time Presentation
Serial Arm Control in Real Time PresentationSerial Arm Control in Real Time Presentation
Serial Arm Control in Real Time Presentation
 
“I’m still / I’m still / Chaining from the Block”
“I’m still / I’m still / Chaining from the Block”“I’m still / I’m still / Chaining from the Block”
“I’m still / I’m still / Chaining from the Block”
 
Pushing the limits of ePRTC: 100ns holdover for 100 days
Pushing the limits of ePRTC: 100ns holdover for 100 daysPushing the limits of ePRTC: 100ns holdover for 100 days
Pushing the limits of ePRTC: 100ns holdover for 100 days
 
Mind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AIMind map of terminologies used in context of Generative AI
Mind map of terminologies used in context of Generative AI
 
How to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptxHow to Get CNIC Information System with Paksim Ga.pptx
How to Get CNIC Information System with Paksim Ga.pptx
 
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
GraphSummit Singapore | Graphing Success: Revolutionising Organisational Stru...
 
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfObservability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdf
 
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success StoryDriving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success Story
 
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
AI 101: An Introduction to the Basics and Impact of Artificial IntelligenceAI 101: An Introduction to the Basics and Impact of Artificial Intelligence
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
 
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
GraphSummit Singapore | Enhancing Changi Airport Group's Passenger Experience...
 
Uni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems Copilot event_05062024_C.Vlachos.pdfUni Systems Copilot event_05062024_C.Vlachos.pdf
Uni Systems Copilot event_05062024_C.Vlachos.pdf
 
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024GraphSummit Singapore | The Art of the  Possible with Graph - Q2 2024
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024
 

Introduction to second generation sequencing

  • 1. [MIT] Introduction to 2GS data analysis Drink faster ! June 23, 2011
  • 2. Production Informatics and Bioinformatics June 23, 2011 Produce raw sequence reads Basic Production Informatics Map to genome and generate raw genomic features (e.g. SNPs) Advanced Production Inform. Analyze the data; Uncover the biological meaning Bioinformatics Research Per one-flowcell project
  • 3.
  • 4. What steps are involved in sequencing ? June 23, 2011 sequencing by synthesis (SBS) technology Fragmentation Library generation Amplification Sequencing Analysis Illumina Marketing: “3h 10 minutes wet-lab 30 minutes dry lab”
  • 5. Illumina sequencing: Library + Amplification June 23, 2011 “Illumina Sequencing Technology” booklet
  • 6. Illumina Sequencing: Synthesis + Imaging June 23, 2011 “Illumina Sequencing Technology” booklet
  • 7. Output: 1.5 Terabyte of data June 23, 2011 Inspired by anzska information booklet
  • 8. Sequencer Output Conversion: Production Informatics 1.5 TB data : 6 billion clusters with 100 bp reads = 600 billion data points June 23, 2011 HiSeq CASAVA … × read length For HiSeq: images are converted to flat files (*.bcl or *.cif) visualpharm.com Maysoft
  • 9. Multiplexing 6 billion reads: 750 million reads per lane Currently 12-plex (soon 96-plex): One run June 23, 2011 Oliver Twardowski
  • 10. Demultiplexing June 23, 2011 CASAVA … … × samples × read length visualpharm.com
  • 11. CASAVA1.8.0 program call June 23, 2011 configureBclToFastq.pl br /> --input-dir Data/Intensities/BaseCalls/ br /> -output-dir Data/Unaligned br /> --sample-sheet SampleSheet.csv --use-bases-mask y100,I6nn,Y100 >file.log 2>&1 cd Data/Unaligned qsub -pe make 16 -jy -v $MYPATH –oqsub.out -cwd –N fastq -by br /> make -j 16 Runtime: ~ 6h
  • 12. Fastq files June 23, 2011 @HWI-ST301_0112:1:1:1169:2044#0/1 CCATAAGGCCACGTATTTTGCAAGCTATTTAACTGGCGGCGAT +HWI-ST301_0112:1:1:1169:2044#0/1 dddcd^dd`acacdacd`ecdedabdcdddcc`bTabr />36 36 36 35 28 … ASCII @ .. ~ DEC 64 .. 126 PHRED 0 .. 62 Phred scores are estimates only ! Cock PJ, Fields CJ, Goto N, Heuer ML, Rice PM. The Sanger FASTQ file format for sequences with quality scores, and the Solexa/Illumina FASTQ variants. Nucleic Acids Res. 2010 Apr;38(6):1767-71. PMID:20015970
  • 13. Fastq – PHRED quality Pathological June 23, 2011
  • 14. Fastq: Quality control Base-pair quality score Adapter contamination Uneven Amplification June 23, 2011
  • 15. Three things to remember Don’t be fooled by marketing Fastqfiles are not directly usable Basic-run QC can be made from fastq file June 23, 2011 “All modern genomics projects are now bottlenecked at the stage of data analysis rather than data production” Ewan Birney European Bioinformatics Institute Wellcome Trust David S. Roos Bioinformatics--Trying to Swim in a Sea of Data;Science 16 February 2001: Vol. 291 no. 5507 pp. 1260-1261 DOI: 10.1126/science.291.5507.1260
  • 16. Next Week: June 23, 2011 Abstract: This session will focus on identifying SNPs from whole genome, exome capture or targeted resequencing data. The approaches of mapping, local realigment, recalibration, SNP calling, and SNP recalibration will be introduced and quality metrics discussed.
  • 18.
  • 19. Helicos true Single Molecule Sequencing(tSMS)™ technology Sequencing by synthesis but much more sensitive so no amplification June 23, 2011
  • 20. Life Technology - Ion Torrent Hydrogen Ion is released by the incorporation of a nucleotide, which is measured by a semiconductor Depending on which nucleotide wash cycle the signal coincides June 23, 2011
  • 21. PacBio Immobilized polymerase at the bottom of a well Fluorescent nucleotides float around and if they are incorporated they are held still for tens of milliseconds, which is the signal that is recorded No upper limit on the length June 23, 2011 http://www.pacificbiosciences.com/smrt-biology/smrt-technology?page=4
  • 22. Nanopore Molecule is sucked through a poor and the change in the membrane charge due to the different nucleotides is recorded. June 23, 2011 http://www.nanoporetech.com/sections/index/82

Editor's Notes

  1. http://2.bp.blogspot.com/_BPr6hpMG0tg/TSZdkYDcRvI/AAAAAAAAAjY/ReScIkWNySg/s1600/drink.jpg
  2. PCR where a labeled nucleotide is incorporated at random that terminates the PCR reaction. These fragments of different length are then separated on a gel and the sequence can be manually read from the labeled end nucleotides.
  3. Some of you have done some library prep already so you have a feel for how realistic 3h10 min are for this. This seminar goes through the analysis steps that are required to answer the question the data was generated for. So by the end of this seminar series you’ll have also a feel for how realistic 30 minutes is for the data analysis.
  4. PCR where a labeled nucleotide is incorporated at random that terminates the PCR reaction. These fragments of different length are then separated on a gel and the sequence can be manually read from the labeled end nucleotides.
  5. http://www.helicosbio.com/Technology/TrueSingleMoleculeSequencing/tabid/64/Default.aspx
  6. http://www.nanoporetech.com/sections/index/82