SlideShare a Scribd company logo

RNA-seq: A High-resolution View of the Transcriptome

•Download as PPTX, PDF•
•
Sean Davis
Sean Davis

The molecular microscopes that we use to examine human biology have advanced significantly with the advent of next generation sequencing. RNA-seq is one application of this technology that leads to a very high-resolution view of the transcriptome. With these new technologies come increased data analysis and data handling burdens as well as the promise of new discovery. These slides present a high-level overview of the RNA-seq technology with a focus on the analysis approaches, quality control challenges, and experimental design.

Science
1 of 88
Sean Davis, M.D., Ph.D. Genetics Branch, Center for Cancer Research National Cancer Institute National Institutes of Health RNA-seq: A high-resolution View of the Transcriptome
Normal Karyotype Tumor Karyotype
The Central Dogma
phenotype Gene Copy Number Sequence Variation Chromatin Structure and Function Gene Expression Transcriptional Regulation DNA Methylation Patient and Population Characteristics
Your Nature Paper
High Throughput Sequencing AKA, NGS
DNA (0.1-1.0 ug) Single molecule array Sample preparation Cluster growth 5’ 5’3’ G T C A G T C A G T C A C A G T C A T C A C C T A G C G T A G T 1 2 3 7 8 94 5 6 Image acquisition Base calling T G C T A C G A T … Sequencing Illumina SBS Technology Reversible Terminator Chemistry Foundation © Illumina, Inc.http://www.illumina.com/technology/sequencing_technology.ilmn http://seqanswers.com/forums/showthread.php?t=21
Single end vs paired end sequencing Illumina Paired-end sequencingPaired-end: useful for RRBS, essential for RNA-seq, not useful for ChIP- seq
What comes out of the machine: short reads in fastq format @D3B4KKQ1_0166:8:1101:1960:2190#CGATGT/1 CTCCTGGAAAACGCTTTGGTAGATTTGGCCAGGAGCTTTCTTTTATGTAAATTG +D3B4KKQ1_0166:8:1101:1960:2190#CGATGT/1 [^^cedeefee`cghhhfcRX`_gfghf^bZbecg^eeb[caef`ef^a_`eXa @D3B4KKQ1_0166:8:1101:2154:2137#CGATGT/1 TCCANCCATGGCAAATTCCATGGCACCGTCAAGGCTGAGAACGGGAAGCTTGTC +D3B4KKQ1_0166:8:1101:2154:2137#CGATGT/1 ab_eBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB @D3B4KKQ1_0166:8:1101:2249:2171#CGATGT/1 TACAAGTGCAGCATCAAGGAGCGAATGCTCTACTCCAGCTGCAAGAGCCGCCTC +D3B4KKQ1_0166:8:1101:2249:2171#CGATGT/1 _[_ceeec[^eeghdffffhh^efh_egfhfgeec_fbafhhhhd`caegfheh @D3B4KKQ1_0166:8:1101:2043:2187#CGATGT/1 GAAGGAGAGAAGGGGAGGAGGGCGGGGGGCACCTACTACATCGCCCTCCACATC +D3B4KKQ1_0166:8:1101:2043:2187#CGATGT/1 ^_accceg`gga`f[fgcb`Ucgfaa_LVV^[bbbbbRWW`W^Y[_[^bbbbb @D3B4KKQ1_0166:8:1101:2188:2232#CGATGT/1 GTGGCCGATTCCTGAGCTGTGTTTGAGGAGAGGGCGGAGTGCCATCTGGGTAGC +D3B4KKQ1_0166:8:1101:2188:2232#CGATGT/1 QS to int In R: as.integer(ch arToRaw(‘e')) -33
Pair end sequencing s_8_1_sequence.txt.gz s_8_2_sequence.txt.gz @D3B4KKQ1_0166:8:1101:1960:2190#CGATGT/1 CTCCTGGAAAACGCTTTGGTAGATTTGGCCAGGAGCTTTCTTTTATGTAAATTG +D3B4KKQ1_0166:8:1101:1960:2190#CGATGT/1 [^^cedeefee`cghhhfcRX`_gfghf^bZbecg^eeb[caef`ef^a_`eXa @D3B4KKQ1_0166:8:1101:2154:2137#CGATGT/1 TCCANCCATGGCAAATTCCATGGCACCGTCAAGGCTGAGAACGGGAAGCTTGTC +D3B4KKQ1_0166:8:1101:2154:2137#CGATGT/1 ab_eBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBBB @D3B4KKQ1_0166:8:1101:2249:2171#CGATGT/1 TACAAGTGCAGCATCAAGGAGCGAATGCTCTACTCCAGCTGCAAGAGCCGCCTC +D3B4KKQ1_0166:8:1101:2249:2171#CGATGT/1 _[_ceeec[^eeghdffffhh^efh_egfhfgeec_fbafhhhhd`caegfheh @D3B4KKQ1_0166:8:1101:2043:2187#CGATGT/1 GAAGGAGAGAAGGGGAGGAGGGCGGGGGGCACCTACTACATCGCCCTCCACATC +D3B4KKQ1_0166:8:1101:2043:2187#CGATGT/1 ^_accceg`gga`f[fgcb`Ucgfaa_LVV^[bbbbbRWW`W^Y[_[^bbbbb @D3B4KKQ1_0166:8:1101:2188:2232#CGATGT/1 GTGGCCGATTCCTGAGCTGTGTTTGAGGAGAGGGCGGAGTGCCATCTGGGTAGC +D3B4KKQ1_0166:8:1101:2188:2232#CGATGT/1 aa_eeeeegggggihhiiifgeghfeghbgcghifiidg^dbgggeeeee`dcd @D3B4KKQ1_0166:8:1101:1960:2190#CGATGT/2 GGCATATTTAACAGCATTGAACAGAATTCTGTGTCCTGTAAAAAAATTAGCTTA +D3B4KKQ1_0166:8:1101:1960:2190#CGATGT/2 a__aaa`ce`cgcffdf_acda^ea]befffbeged`g[a`e_caaac]cb`gb @D3B4KKQ1_0166:8:1101:2154:2137#CGATGT/2 TTGAGGCTGTTGTCATACTTCTCATGGTTCACACCCATGACGAACATGGGGGCG +D3B4KKQ1_0166:8:1101:2154:2137#CGATGT/2 a__eeeeeggegefhhhiiihhhhhiieghhhghhiiffhiififhhiihegic @D3B4KKQ1_0166:8:1101:2249:2171#CGATGT/2 CGGGGTGCACCTCGTCGTAGAGGAACTCTGCCGTCAGCTCTGCCCCATCGCCAA +D3B4KKQ1_0166:8:1101:2249:2171#CGATGT/2 ^__ee__cge`cghghhfgddgfgi]ehhfffff^ec[beegidffhhfhadba @D3B4KKQ1_0166:8:1101:2043:2187#CGATGT/2 CTTAGTCTCAGTTTTCCTCCAGCAGCCTGAGGAAACTCAAAGGCACAGTTCCCA +D3B4KKQ1_0166:8:1101:2043:2187#CGATGT/2 _abeaaacg^g^eghhhhgafghhdfghfedeghfiiicfbgdHYagfeecggf @D3B4KKQ1_0166:8:1101:2188:2232#CGATGT/2 TAGGCTCAAAGTCTAACGCCAATCCCGAACCTGGGCATCTGTACACACACACAC +D3B4KKQ1_0166:8:1101:2188:2232#CGATGT/2 abbeceeegggcghiihiihhhhiifhiiiiihiiiiiiihegh`eggfebfhg … …
RNA-seq protocol schematic
Our First Experiment
Overview of BAC in the Genome
Sequencing a BAC
Sequence Coverage
Repeats
Repeats
Repeats are not created equal
Approaches to RNA-seq Nature Biotech (2010) 28, 421-423
Alignment
RNA-seq Alignment
Run Time
Alignment Yield
Splice Read Placement Accuracy
Impact on Transcript Assembly
Transcript Quantification
Models for RNA-seq • Count-based models • Multi-reads (isoform resolution) • Paired-end reads (include length resolution step) • Positional bias along transcript length • Sequence bias
Read Counting
Mortazavi, 2008, NMeth
L. Pachter (2011) arXiv:1104.3889v
Sequence Bias--priming Hansen (2010), NAR
Sample-specific Sequence Bias
Models for RNA-seq
Result of Quantification
Clustering and Visualization
Hierarchical Clustering Gene 1 Gene 2 Gene 3 Gene 4 Gene 5 Gene 6 Gene 7 Gene 8
Hierarchical Clustering Gene 1 Gene 2 Gene 3 Gene 4 Gene 5 Gene 6 Gene 7 Gene 8
Hierarchical Clustering Gene 1 Gene 2 Gene 3 Gene 4 Gene 5 Gene 6 Gene 7 Gene 8
Hierarchical Clustering Gene 1 Gene 2 Gene 3 Gene 4 Gene 5 Gene 6 Gene 7 Gene 8
Distance Metrics  Euclidean distance  Manhattan distance  Minkowski distance (generalized distance)
Distance Metrics • Correlation – maximum value of 1 if X and Y are perfectly correlated – minimum value of -1 if X and Y are exactly opposite – d(X,Y) = 1 – rxy • Many, many others • Choice of distance metric can be driven by underlying data (eg., binary data, categorical data, outliers, etc.)
Example of Distance Metric Choice
Example • dat = matrix(rnorm(10000),ncol=20) • dat[1:100,1:10] = dat[1:100,1:10]+1 • hclust • dist • as.dist(1-cor)
Differential Expression
MA Plot
64
65
66
67
68
DE False Positive Rates
DE Evaluation
DE Software Runtime
RNA-seq workflow as proposed by Anders et al. in Nature Protocols
MA Plot
Fusion Gene Detection
Fusion gene schematic
Fusion Detection
False Positive Fusion Detection
Experimental Design • What are my goals? – Differential expression? – Transcriptome assembly? – Identify rare, novel trancripts? • System characteristics? – Large, expanded genome? – Intron/exon structures complex? – No reference genome or transcriptome
Experimental Design • Technical replicates – Probably not needed due to low technical variation • Biological replicates – Not explicitly needed for transcript assembly – Essential for differential expression analysis – Number of replicates often driven by sample availability for human studies – More is almost always better
Links of Interest • http://bioconductor.org • http://biostars.org • http://www.rna-seqblog.com/ • https://genome.ucsc.edu/ENCODE/ • http://www.ncbi.nlm.nih.gov/gds/
Visualizing Splicing

Recommended

RNAseq Analysis
RNAseq AnalysisRNAseq Analysis
RNAseq AnalysisAureliano Bombarely
 
So you want to do a: RNAseq experiment, Differential Gene Expression Analysis
So you want to do a: RNAseq experiment, Differential Gene Expression AnalysisSo you want to do a: RNAseq experiment, Differential Gene Expression Analysis
So you want to do a: RNAseq experiment, Differential Gene Expression AnalysisUniversity of California, Davis
 
Introduction to RNA-seq and RNA-seq Data Analysis (UEB-UAT Bioinformatics Cou...
Introduction to RNA-seq and RNA-seq Data Analysis (UEB-UAT Bioinformatics Cou...Introduction to RNA-seq and RNA-seq Data Analysis (UEB-UAT Bioinformatics Cou...
Introduction to RNA-seq and RNA-seq Data Analysis (UEB-UAT Bioinformatics Cou...VHIR Vall d’Hebron Institut de Recerca
 
SNPs analysis methods
SNPs analysis methodsSNPs analysis methods
SNPs analysis methodshad89
 
Intro to illumina sequencing
Intro to illumina sequencingIntro to illumina sequencing
Intro to illumina sequencingUniversity of Allahabad
 
Introduction to Single-cell RNA-seq
Introduction to Single-cell RNA-seqIntroduction to Single-cell RNA-seq
Introduction to Single-cell RNA-seqTimothy Tickle
 
RNA-Seq
RNA-SeqRNA-Seq
RNA-SeqBioinformatics and Computational Biosciences Branch
 
Third Generation Sequencing
Third Generation Sequencing Third Generation Sequencing
Third Generation Sequencing priyanka raviraj
 

Recommended

RNAseq Analysis
RNAseq AnalysisRNAseq Analysis
RNAseq AnalysisAureliano Bombarely
 
So you want to do a: RNAseq experiment, Differential Gene Expression Analysis
So you want to do a: RNAseq experiment, Differential Gene Expression AnalysisSo you want to do a: RNAseq experiment, Differential Gene Expression Analysis
So you want to do a: RNAseq experiment, Differential Gene Expression AnalysisUniversity of California, Davis
 
Introduction to RNA-seq and RNA-seq Data Analysis (UEB-UAT Bioinformatics Cou...
Introduction to RNA-seq and RNA-seq Data Analysis (UEB-UAT Bioinformatics Cou...Introduction to RNA-seq and RNA-seq Data Analysis (UEB-UAT Bioinformatics Cou...
Introduction to RNA-seq and RNA-seq Data Analysis (UEB-UAT Bioinformatics Cou...VHIR Vall d’Hebron Institut de Recerca
 
SNPs analysis methods
SNPs analysis methodsSNPs analysis methods
SNPs analysis methodshad89
 
Intro to illumina sequencing
Intro to illumina sequencingIntro to illumina sequencing
Intro to illumina sequencingUniversity of Allahabad
 
Introduction to Single-cell RNA-seq
Introduction to Single-cell RNA-seqIntroduction to Single-cell RNA-seq
Introduction to Single-cell RNA-seqTimothy Tickle
 
RNA-Seq
RNA-SeqRNA-Seq
RNA-SeqBioinformatics and Computational Biosciences Branch
 
Third Generation Sequencing
Third Generation Sequencing Third Generation Sequencing
Third Generation Sequencing priyanka raviraj
 
SNP Genotyping Technologies
SNP Genotyping TechnologiesSNP Genotyping Technologies
SNP Genotyping TechnologiesSivamaniBalasubramaniam
 
RNA-seq differential expression analysis
RNA-seq differential expression analysisRNA-seq differential expression analysis
RNA-seq differential expression analysismikaelhuss
 
Next generation sequencing
Next generation sequencingNext generation sequencing
Next generation sequencingUzma Jabeen
 
RNA-seq Data Analysis Overview
RNA-seq Data Analysis OverviewRNA-seq Data Analysis Overview
RNA-seq Data Analysis OverviewSean Davis
 
An introduction to RNA-seq data analysis
An introduction to RNA-seq data analysisAn introduction to RNA-seq data analysis
An introduction to RNA-seq data analysisAGRF_Ltd
 
Ngs ppt
Ngs pptNgs ppt
Ngs pptArcha Dave
 
DNA Microarray introdution and application
DNA Microarray introdution and applicationDNA Microarray introdution and application
DNA Microarray introdution and applicationNeeraj Sharma
 
Single Nucleotide Polymorphism Analysis (SNPs)
Single Nucleotide Polymorphism Analysis (SNPs)Single Nucleotide Polymorphism Analysis (SNPs)
Single Nucleotide Polymorphism Analysis (SNPs)Data Science Thailand
 
Kogo 2013 RNA-seq analysis
Kogo 2013 RNA-seq analysisKogo 2013 RNA-seq analysis
Kogo 2013 RNA-seq analysisJunsu Ko
 
Next generation sequencing technologies for crop improvement
Next generation sequencing technologies for crop improvementNext generation sequencing technologies for crop improvement
Next generation sequencing technologies for crop improvementanjaligoud
 
Single cell RNA sequencing; Methods and applications
Single cell RNA sequencing; Methods and applicationsSingle cell RNA sequencing; Methods and applications
Single cell RNA sequencing; Methods and applicationsfaraharooj
 
Exome sequence analysis
Exome sequence analysisExome sequence analysis
Exome sequence analysisPubudu Samarakoon
 
Microarray Data Analysis
Microarray Data AnalysisMicroarray Data Analysis
Microarray Data Analysisyuvraj404
 
Next generation sequencing
Next generation sequencingNext generation sequencing
Next generation sequencingDayananda Salam
 
Rnaseq basics ngs_application1
Rnaseq basics ngs_application1Rnaseq basics ngs_application1
Rnaseq basics ngs_application1Yaoyu Wang
 
PacBio SMRT - THIRD GENERATION SEQUENCING TECHNIQUE
PacBio SMRT - THIRD GENERATION SEQUENCING TECHNIQUEPacBio SMRT - THIRD GENERATION SEQUENCING TECHNIQUE
PacBio SMRT - THIRD GENERATION SEQUENCING TECHNIQUEMuunda Mudenda
 
Expressed sequence tag (EST), molecular marker
Expressed sequence tag (EST), molecular markerExpressed sequence tag (EST), molecular marker
Expressed sequence tag (EST), molecular markerKAUSHAL SAHU
 
Comparative genomics
Comparative genomicsComparative genomics
Comparative genomicsJajati Keshari Nayak
 
Genome sequencing
Genome sequencingGenome sequencing
Genome sequencingMusaddaq Hafeez
 
Comparative genomics
Comparative genomicsComparative genomics
Comparative genomicsprateek kumar
 
Transcriptomics
TranscriptomicsTranscriptomics
TranscriptomicsMohammad Hosein Romena
 
Rna seq - PDX models
Rna seq - PDX models Rna seq - PDX models
Rna seq - PDX models Amitha Dasari
 

More Related Content

What's hot

RNA-seq differential expression analysis
RNA-seq differential expression analysisRNA-seq differential expression analysis
RNA-seq differential expression analysismikaelhuss
 
Next generation sequencing
Next generation sequencingNext generation sequencing
Next generation sequencingUzma Jabeen
 
RNA-seq Data Analysis Overview
RNA-seq Data Analysis OverviewRNA-seq Data Analysis Overview
RNA-seq Data Analysis OverviewSean Davis
 
An introduction to RNA-seq data analysis
An introduction to RNA-seq data analysisAn introduction to RNA-seq data analysis
An introduction to RNA-seq data analysisAGRF_Ltd
 
DNA Microarray introdution and application
DNA Microarray introdution and applicationDNA Microarray introdution and application
DNA Microarray introdution and applicationNeeraj Sharma
 
Single Nucleotide Polymorphism Analysis (SNPs)
Single Nucleotide Polymorphism Analysis (SNPs)Single Nucleotide Polymorphism Analysis (SNPs)
Single Nucleotide Polymorphism Analysis (SNPs)Data Science Thailand
 
Kogo 2013 RNA-seq analysis
Kogo 2013 RNA-seq analysisKogo 2013 RNA-seq analysis
Kogo 2013 RNA-seq analysisJunsu Ko
 
Next generation sequencing technologies for crop improvement
Next generation sequencing technologies for crop improvementNext generation sequencing technologies for crop improvement
Next generation sequencing technologies for crop improvementanjaligoud
 
Single cell RNA sequencing; Methods and applications
Single cell RNA sequencing; Methods and applicationsSingle cell RNA sequencing; Methods and applications
Single cell RNA sequencing; Methods and applicationsfaraharooj
 
Microarray Data Analysis
Microarray Data AnalysisMicroarray Data Analysis
Microarray Data Analysisyuvraj404
 
Next generation sequencing
Next generation sequencingNext generation sequencing
Next generation sequencingDayananda Salam
 
Rnaseq basics ngs_application1
Rnaseq basics ngs_application1Rnaseq basics ngs_application1
Rnaseq basics ngs_application1Yaoyu Wang
 
PacBio SMRT - THIRD GENERATION SEQUENCING TECHNIQUE
PacBio SMRT - THIRD GENERATION SEQUENCING TECHNIQUEPacBio SMRT - THIRD GENERATION SEQUENCING TECHNIQUE
PacBio SMRT - THIRD GENERATION SEQUENCING TECHNIQUEMuunda Mudenda
 
Expressed sequence tag (EST), molecular marker
Expressed sequence tag (EST), molecular markerExpressed sequence tag (EST), molecular marker
Expressed sequence tag (EST), molecular markerKAUSHAL SAHU
 
Comparative genomics
Comparative genomicsComparative genomics
Comparative genomicsprateek kumar
 

What's hot (20)

SNP Genotyping Technologies
SNP Genotyping TechnologiesSNP Genotyping Technologies
SNP Genotyping Technologies
 
RNA-seq differential expression analysis
RNA-seq differential expression analysisRNA-seq differential expression analysis
RNA-seq differential expression analysis
 
Next generation sequencing
Next generation sequencingNext generation sequencing
Next generation sequencing
 
RNA-seq Data Analysis Overview
RNA-seq Data Analysis OverviewRNA-seq Data Analysis Overview
RNA-seq Data Analysis Overview
 
An introduction to RNA-seq data analysis
An introduction to RNA-seq data analysisAn introduction to RNA-seq data analysis
An introduction to RNA-seq data analysis
 
Ngs ppt
Ngs pptNgs ppt
Ngs ppt
 
DNA Microarray introdution and application
DNA Microarray introdution and applicationDNA Microarray introdution and application
DNA Microarray introdution and application
 
Single Nucleotide Polymorphism Analysis (SNPs)
Single Nucleotide Polymorphism Analysis (SNPs)Single Nucleotide Polymorphism Analysis (SNPs)
Single Nucleotide Polymorphism Analysis (SNPs)
 
Kogo 2013 RNA-seq analysis
Kogo 2013 RNA-seq analysisKogo 2013 RNA-seq analysis
Kogo 2013 RNA-seq analysis
 
Next generation sequencing technologies for crop improvement
Next generation sequencing technologies for crop improvementNext generation sequencing technologies for crop improvement
Next generation sequencing technologies for crop improvement
 
Single cell RNA sequencing; Methods and applications
Single cell RNA sequencing; Methods and applicationsSingle cell RNA sequencing; Methods and applications
Single cell RNA sequencing; Methods and applications
 
Exome sequence analysis
Exome sequence analysisExome sequence analysis
Exome sequence analysis
 
Microarray Data Analysis
Microarray Data AnalysisMicroarray Data Analysis
Microarray Data Analysis
 
Next generation sequencing
Next generation sequencingNext generation sequencing
Next generation sequencing
 
Rnaseq basics ngs_application1
Rnaseq basics ngs_application1Rnaseq basics ngs_application1
Rnaseq basics ngs_application1
 
PacBio SMRT - THIRD GENERATION SEQUENCING TECHNIQUE
PacBio SMRT - THIRD GENERATION SEQUENCING TECHNIQUEPacBio SMRT - THIRD GENERATION SEQUENCING TECHNIQUE
PacBio SMRT - THIRD GENERATION SEQUENCING TECHNIQUE
 
Expressed sequence tag (EST), molecular marker
Expressed sequence tag (EST), molecular markerExpressed sequence tag (EST), molecular marker
Expressed sequence tag (EST), molecular marker
 
Comparative genomics
Comparative genomicsComparative genomics
Comparative genomics
 
Genome sequencing
Genome sequencingGenome sequencing
Genome sequencing
 
Comparative genomics
Comparative genomicsComparative genomics
Comparative genomics
 

Viewers also liked

Rna seq - PDX models
Rna seq - PDX models Rna seq - PDX models
Rna seq - PDX models Amitha Dasari
 
Aims@jcu 2015 amin
Aims@jcu 2015 aminAims@jcu 2015 amin
Aims@jcu 2015 aminAmin Mohamed
 
Amin's talk at the 13th ICRS, Hawaii
Amin's talk at the 13th ICRS, Hawaii Amin's talk at the 13th ICRS, Hawaii
Amin's talk at the 13th ICRS, Hawaii Amin Mohamed
 
Whole Transcriptome Profiling of Cancer Tumors in Mouse PDX Models
Whole Transcriptome Profiling of Cancer Tumors in Mouse PDX ModelsWhole Transcriptome Profiling of Cancer Tumors in Mouse PDX Models
Whole Transcriptome Profiling of Cancer Tumors in Mouse PDX ModelsTom Koch
 
Why Transcriptome? Why RNA-Seq? ENCODE answers….
Why Transcriptome? Why RNA-Seq? ENCODE answers….Why Transcriptome? Why RNA-Seq? ENCODE answers….
Why Transcriptome? Why RNA-Seq? ENCODE answers….Mohammad Hossein Banabazi
 

Viewers also liked (6)

Transcriptomics
TranscriptomicsTranscriptomics
Transcriptomics
 
Rna seq - PDX models
Rna seq - PDX models Rna seq - PDX models
Rna seq - PDX models
 
Aims@jcu 2015 amin
Aims@jcu 2015 aminAims@jcu 2015 amin
Aims@jcu 2015 amin
 
Amin's talk at the 13th ICRS, Hawaii
Amin's talk at the 13th ICRS, Hawaii Amin's talk at the 13th ICRS, Hawaii
Amin's talk at the 13th ICRS, Hawaii
 
Whole Transcriptome Profiling of Cancer Tumors in Mouse PDX Models
Whole Transcriptome Profiling of Cancer Tumors in Mouse PDX ModelsWhole Transcriptome Profiling of Cancer Tumors in Mouse PDX Models
Whole Transcriptome Profiling of Cancer Tumors in Mouse PDX Models
 
Why Transcriptome? Why RNA-Seq? ENCODE answers….
Why Transcriptome? Why RNA-Seq? ENCODE answers….Why Transcriptome? Why RNA-Seq? ENCODE answers….
Why Transcriptome? Why RNA-Seq? ENCODE answers….
 

Similar to RNA-seq: A High-resolution View of the Transcriptome

OKC Grand Rounds 2009
OKC Grand Rounds 2009OKC Grand Rounds 2009
OKC Grand Rounds 2009Sean Davis
 
Genomica - Microarreglos de DNA
Genomica - Microarreglos de DNAGenomica - Microarreglos de DNA
Genomica - Microarreglos de DNAUlises Urzua
 
Genomics Technologies
Genomics TechnologiesGenomics Technologies
Genomics TechnologiesSean Davis
 
115 genomic and proteomic screen
115 genomic and proteomic screen115 genomic and proteomic screen
115 genomic and proteomic screenSHAPE Society
 
Acc 2002 microarray mehran for print
Acc 2002 microarray mehran for printAcc 2002 microarray mehran for print
Acc 2002 microarray mehran for printSHAPE Society
 
Predicting phenotype from genotype with machine learning
Predicting phenotype from genotype with machine learningPredicting phenotype from genotype with machine learning
Predicting phenotype from genotype with machine learningPatricia Francis-Lyon
 
Visual Exploration of Clinical and Genomic Data for Patient Stratification
Visual Exploration of Clinical and Genomic Data for Patient StratificationVisual Exploration of Clinical and Genomic Data for Patient Stratification
Visual Exploration of Clinical and Genomic Data for Patient StratificationNils Gehlenborg
 
Acc 2002 mehran for print
Acc 2002 mehran for printAcc 2002 mehran for print
Acc 2002 mehran for printSHAPE Society
 
High Dimensional Biological Data Analysis and Visualization
High Dimensional Biological Data Analysis and VisualizationHigh Dimensional Biological Data Analysis and Visualization
High Dimensional Biological Data Analysis and VisualizationDmitry Grapov
 
20100509 bioinformatics kapushesky_lecture03-04_0
20100509 bioinformatics kapushesky_lecture03-04_020100509 bioinformatics kapushesky_lecture03-04_0
20100509 bioinformatics kapushesky_lecture03-04_0Computer Science Club
 

Similar to RNA-seq: A High-resolution View of the Transcriptome (20)

OKC Grand Rounds 2009
OKC Grand Rounds 2009OKC Grand Rounds 2009
OKC Grand Rounds 2009
 
Genomica - Microarreglos de DNA
Genomica - Microarreglos de DNAGenomica - Microarreglos de DNA
Genomica - Microarreglos de DNA
 
Genomics Technologies
Genomics TechnologiesGenomics Technologies
Genomics Technologies
 
Rna seq
Rna seqRna seq
Rna seq
 
155 dna microarray
155 dna microarray155 dna microarray
155 dna microarray
 
155 dna microarray
155 dna microarray155 dna microarray
155 dna microarray
 
Dna microarray mehran
Dna microarray mehranDna microarray mehran
Dna microarray mehran
 
Dna microarray mehran- u of toronto
Dna microarray mehran- u of torontoDna microarray mehran- u of toronto
Dna microarray mehran- u of toronto
 
115 genomic and proteomic screen
115 genomic and proteomic screen115 genomic and proteomic screen
115 genomic and proteomic screen
 
Genomic and proteomic screen
Genomic and proteomic screenGenomic and proteomic screen
Genomic and proteomic screen
 
Acc 2002 microarray mehran for print
Acc 2002 microarray mehran for printAcc 2002 microarray mehran for print
Acc 2002 microarray mehran for print
 
Acc 2002 microarray mehran for print
Acc 2002 microarray mehran for printAcc 2002 microarray mehran for print
Acc 2002 microarray mehran for print
 
115 genomic and proteomic screen
115 genomic and proteomic screen115 genomic and proteomic screen
115 genomic and proteomic screen
 
Predicting phenotype from genotype with machine learning
Predicting phenotype from genotype with machine learningPredicting phenotype from genotype with machine learning
Predicting phenotype from genotype with machine learning
 
Visual Exploration of Clinical and Genomic Data for Patient Stratification
Visual Exploration of Clinical and Genomic Data for Patient StratificationVisual Exploration of Clinical and Genomic Data for Patient Stratification
Visual Exploration of Clinical and Genomic Data for Patient Stratification
 
Dna microarray application in vp research mehran
Dna microarray application in vp research mehranDna microarray application in vp research mehran
Dna microarray application in vp research mehran
 
Acc 2002 mehran for print
Acc 2002 mehran for printAcc 2002 mehran for print
Acc 2002 mehran for print
 
Acc 2002 mehran for print
Acc 2002 mehran for printAcc 2002 mehran for print
Acc 2002 mehran for print
 
High Dimensional Biological Data Analysis and Visualization
High Dimensional Biological Data Analysis and VisualizationHigh Dimensional Biological Data Analysis and Visualization
High Dimensional Biological Data Analysis and Visualization
 
20100509 bioinformatics kapushesky_lecture03-04_0
20100509 bioinformatics kapushesky_lecture03-04_020100509 bioinformatics kapushesky_lecture03-04_0
20100509 bioinformatics kapushesky_lecture03-04_0
 

More from Sean Davis

Lightweight data engineering, tools, and software to facilitate data reuse an...
Lightweight data engineering, tools, and software to facilitate data reuse an...Lightweight data engineering, tools, and software to facilitate data reuse an...
Lightweight data engineering, tools, and software to facilitate data reuse an...Sean Davis
 
2016 07 12_purdue_bigdatainomics_seandavis
2016 07 12_purdue_bigdatainomics_seandavis2016 07 12_purdue_bigdatainomics_seandavis
2016 07 12_purdue_bigdatainomics_seandavisSean Davis
 
SRAdb Bioconductor Package Overview
SRAdb Bioconductor Package OverviewSRAdb Bioconductor Package Overview
SRAdb Bioconductor Package OverviewSean Davis
 
ShinySRAdb: an R package using shiny to wrap the SRAdb Bioconductor package
ShinySRAdb: an R package using shiny to wrap the SRAdb Bioconductor packageShinySRAdb: an R package using shiny to wrap the SRAdb Bioconductor package
ShinySRAdb: an R package using shiny to wrap the SRAdb Bioconductor packageSean Davis
 
Introduction to R
Introduction to RIntroduction to R
Introduction to RSean Davis
 
Forsharing cshl2011 sequencing
Forsharing cshl2011 sequencingForsharing cshl2011 sequencing
Forsharing cshl2011 sequencingSean Davis
 
Public datatutorialoverview
Public datatutorialoverviewPublic datatutorialoverview
Public datatutorialoverviewSean Davis
 
Sssc retreat.bioinfo resources.20110411
Sssc retreat.bioinfo resources.20110411Sssc retreat.bioinfo resources.20110411
Sssc retreat.bioinfo resources.20110411Sean Davis
 
Genetics Branch Journal club
Genetics Branch Journal clubGenetics Branch Journal club
Genetics Branch Journal clubSean Davis
 
Bioc strucvariant seattle_11_09
Bioc strucvariant seattle_11_09Bioc strucvariant seattle_11_09
Bioc strucvariant seattle_11_09Sean Davis
 

More from Sean Davis (10)

Lightweight data engineering, tools, and software to facilitate data reuse an...
Lightweight data engineering, tools, and software to facilitate data reuse an...Lightweight data engineering, tools, and software to facilitate data reuse an...
Lightweight data engineering, tools, and software to facilitate data reuse an...
 
2016 07 12_purdue_bigdatainomics_seandavis
2016 07 12_purdue_bigdatainomics_seandavis2016 07 12_purdue_bigdatainomics_seandavis
2016 07 12_purdue_bigdatainomics_seandavis
 
SRAdb Bioconductor Package Overview
SRAdb Bioconductor Package OverviewSRAdb Bioconductor Package Overview
SRAdb Bioconductor Package Overview
 
ShinySRAdb: an R package using shiny to wrap the SRAdb Bioconductor package
ShinySRAdb: an R package using shiny to wrap the SRAdb Bioconductor packageShinySRAdb: an R package using shiny to wrap the SRAdb Bioconductor package
ShinySRAdb: an R package using shiny to wrap the SRAdb Bioconductor package
 
Introduction to R
Introduction to RIntroduction to R
Introduction to R
 
Forsharing cshl2011 sequencing
Forsharing cshl2011 sequencingForsharing cshl2011 sequencing
Forsharing cshl2011 sequencing
 
Public datatutorialoverview
Public datatutorialoverviewPublic datatutorialoverview
Public datatutorialoverview
 
Sssc retreat.bioinfo resources.20110411
Sssc retreat.bioinfo resources.20110411Sssc retreat.bioinfo resources.20110411
Sssc retreat.bioinfo resources.20110411
 
Genetics Branch Journal club
Genetics Branch Journal clubGenetics Branch Journal club
Genetics Branch Journal club
 
Bioc strucvariant seattle_11_09
Bioc strucvariant seattle_11_09Bioc strucvariant seattle_11_09
Bioc strucvariant seattle_11_09
 

Recently uploaded

Spermiogenesis or Spermateleosis or metamorphosis of spermatid
Spermiogenesis or Spermateleosis or metamorphosis of spermatidSpermiogenesis or Spermateleosis or metamorphosis of spermatid
Spermiogenesis or Spermateleosis or metamorphosis of spermatidSarthak Sekhar Mondal
 
Recombination DNA Technology (Nucleic Acid Hybridization )
Recombination DNA Technology (Nucleic Acid Hybridization )Recombination DNA Technology (Nucleic Acid Hybridization )
Recombination DNA Technology (Nucleic Acid Hybridization )aarthirajkumar25
 
Pests of cotton_Sucking_Pests_Dr.UPR.pdf
Pests of cotton_Sucking_Pests_Dr.UPR.pdfPests of cotton_Sucking_Pests_Dr.UPR.pdf
Pests of cotton_Sucking_Pests_Dr.UPR.pdfPirithiRaju
 
Discovery of an Accretion Streamer and a Slow Wide-angle Outflow around FUOri...
Discovery of an Accretion Streamer and a Slow Wide-angle Outflow around FUOri...Discovery of an Accretion Streamer and a Slow Wide-angle Outflow around FUOri...
Discovery of an Accretion Streamer and a Slow Wide-angle Outflow around FUOri...Sérgio Sacani
 
Green chemistry and Sustainable development.pptx
Green chemistry and Sustainable development.pptxGreen chemistry and Sustainable development.pptx
Green chemistry and Sustainable development.pptxRajatChauhan518211
 
Presentation Vikram Lander by Vedansh Gupta.pptx
Presentation Vikram Lander by Vedansh Gupta.pptxPresentation Vikram Lander by Vedansh Gupta.pptx
Presentation Vikram Lander by Vedansh Gupta.pptxgindu3009
 
Zoology 4th semester series (krishna).pdf
Zoology 4th semester series (krishna).pdfZoology 4th semester series (krishna).pdf
Zoology 4th semester series (krishna).pdfSumit Kumar yadav
 
PossibleEoarcheanRecordsoftheGeomagneticFieldPreservedintheIsuaSupracrustalBe...
PossibleEoarcheanRecordsoftheGeomagneticFieldPreservedintheIsuaSupracrustalBe...PossibleEoarcheanRecordsoftheGeomagneticFieldPreservedintheIsuaSupracrustalBe...
PossibleEoarcheanRecordsoftheGeomagneticFieldPreservedintheIsuaSupracrustalBe...Sérgio Sacani
 
Traditional Agroforestry System in India- Shifting Cultivation, Taungya, Home...
Traditional Agroforestry System in India- Shifting Cultivation, Taungya, Home...Traditional Agroforestry System in India- Shifting Cultivation, Taungya, Home...
Traditional Agroforestry System in India- Shifting Cultivation, Taungya, Home...jana861314
 
Botany 4th semester file By Sumit Kumar yadav.pdf
Botany 4th semester file By Sumit Kumar yadav.pdfBotany 4th semester file By Sumit Kumar yadav.pdf
Botany 4th semester file By Sumit Kumar yadav.pdfSumit Kumar yadav
 
A relative description on Sonoporation.pdf
A relative description on Sonoporation.pdfA relative description on Sonoporation.pdf
A relative description on Sonoporation.pdfnehabiju2046
 
Biological Classification BioHack (3).pdf
Biological Classification BioHack (3).pdfBiological Classification BioHack (3).pdf
Biological Classification BioHack (3).pdfmuntazimhurra
 
Hubble Asteroid Hunter III. Physical properties of newly found asteroids
Hubble Asteroid Hunter III. Physical properties of newly found asteroidsHubble Asteroid Hunter III. Physical properties of newly found asteroids
Hubble Asteroid Hunter III. Physical properties of newly found asteroidsSérgio Sacani
 
Broad bean, Lima Bean, Jack bean, Ullucus.pptx
Broad bean, Lima Bean, Jack bean, Ullucus.pptxBroad bean, Lima Bean, Jack bean, Ullucus.pptx
Broad bean, Lima Bean, Jack bean, Ullucus.pptxjana861314
 
Recombinant DNA technology (Immunological screening)
Recombinant DNA technology (Immunological screening)Recombinant DNA technology (Immunological screening)
Recombinant DNA technology (Immunological screening)PraveenaKalaiselvan1
 
STERILITY TESTING OF PHARMACEUTICALS ppt by DR.C.P.PRINCE
STERILITY TESTING OF PHARMACEUTICALS ppt by DR.C.P.PRINCESTERILITY TESTING OF PHARMACEUTICALS ppt by DR.C.P.PRINCE
STERILITY TESTING OF PHARMACEUTICALS ppt by DR.C.P.PRINCEPRINCE C P
 
Unlocking the Potential: Deep dive into ocean of Ceramic Magnets.pptx
Unlocking the Potential: Deep dive into ocean of Ceramic Magnets.pptxUnlocking the Potential: Deep dive into ocean of Ceramic Magnets.pptx
Unlocking the Potential: Deep dive into ocean of Ceramic Magnets.pptxanandsmhk
 
Stunning ➥8448380779▻ Call Girls In Panchshil Enclave Delhi NCR
Stunning ➥8448380779▻ Call Girls In Panchshil Enclave Delhi NCRStunning ➥8448380779▻ Call Girls In Panchshil Enclave Delhi NCR
Stunning ➥8448380779▻ Call Girls In Panchshil Enclave Delhi NCRDelhi Call girls
 

Recently uploaded (20)

Spermiogenesis or Spermateleosis or metamorphosis of spermatid
Spermiogenesis or Spermateleosis or metamorphosis of spermatidSpermiogenesis or Spermateleosis or metamorphosis of spermatid
Spermiogenesis or Spermateleosis or metamorphosis of spermatid
 
Recombination DNA Technology (Nucleic Acid Hybridization )
Recombination DNA Technology (Nucleic Acid Hybridization )Recombination DNA Technology (Nucleic Acid Hybridization )
Recombination DNA Technology (Nucleic Acid Hybridization )
 
Pests of cotton_Sucking_Pests_Dr.UPR.pdf
Pests of cotton_Sucking_Pests_Dr.UPR.pdfPests of cotton_Sucking_Pests_Dr.UPR.pdf
Pests of cotton_Sucking_Pests_Dr.UPR.pdf
 
9953056974 Young Call Girls In Mahavir enclave Indian Quality Escort service
9953056974 Young Call Girls In Mahavir enclave Indian Quality Escort service9953056974 Young Call Girls In Mahavir enclave Indian Quality Escort service
9953056974 Young Call Girls In Mahavir enclave Indian Quality Escort service
 
Discovery of an Accretion Streamer and a Slow Wide-angle Outflow around FUOri...
Discovery of an Accretion Streamer and a Slow Wide-angle Outflow around FUOri...Discovery of an Accretion Streamer and a Slow Wide-angle Outflow around FUOri...
Discovery of an Accretion Streamer and a Slow Wide-angle Outflow around FUOri...
 
Green chemistry and Sustainable development.pptx
Green chemistry and Sustainable development.pptxGreen chemistry and Sustainable development.pptx
Green chemistry and Sustainable development.pptx
 
Presentation Vikram Lander by Vedansh Gupta.pptx
Presentation Vikram Lander by Vedansh Gupta.pptxPresentation Vikram Lander by Vedansh Gupta.pptx
Presentation Vikram Lander by Vedansh Gupta.pptx
 
Zoology 4th semester series (krishna).pdf
Zoology 4th semester series (krishna).pdfZoology 4th semester series (krishna).pdf
Zoology 4th semester series (krishna).pdf
 
PossibleEoarcheanRecordsoftheGeomagneticFieldPreservedintheIsuaSupracrustalBe...
PossibleEoarcheanRecordsoftheGeomagneticFieldPreservedintheIsuaSupracrustalBe...PossibleEoarcheanRecordsoftheGeomagneticFieldPreservedintheIsuaSupracrustalBe...
PossibleEoarcheanRecordsoftheGeomagneticFieldPreservedintheIsuaSupracrustalBe...
 
Traditional Agroforestry System in India- Shifting Cultivation, Taungya, Home...
Traditional Agroforestry System in India- Shifting Cultivation, Taungya, Home...Traditional Agroforestry System in India- Shifting Cultivation, Taungya, Home...
Traditional Agroforestry System in India- Shifting Cultivation, Taungya, Home...
 
Botany 4th semester file By Sumit Kumar yadav.pdf
Botany 4th semester file By Sumit Kumar yadav.pdfBotany 4th semester file By Sumit Kumar yadav.pdf
Botany 4th semester file By Sumit Kumar yadav.pdf
 
A relative description on Sonoporation.pdf
A relative description on Sonoporation.pdfA relative description on Sonoporation.pdf
A relative description on Sonoporation.pdf
 
Biological Classification BioHack (3).pdf
Biological Classification BioHack (3).pdfBiological Classification BioHack (3).pdf
Biological Classification BioHack (3).pdf
 
Hubble Asteroid Hunter III. Physical properties of newly found asteroids
Hubble Asteroid Hunter III. Physical properties of newly found asteroidsHubble Asteroid Hunter III. Physical properties of newly found asteroids
Hubble Asteroid Hunter III. Physical properties of newly found asteroids
 
Broad bean, Lima Bean, Jack bean, Ullucus.pptx
Broad bean, Lima Bean, Jack bean, Ullucus.pptxBroad bean, Lima Bean, Jack bean, Ullucus.pptx
Broad bean, Lima Bean, Jack bean, Ullucus.pptx
 
The Philosophy of Science
The Philosophy of ScienceThe Philosophy of Science
The Philosophy of Science
 
Recombinant DNA technology (Immunological screening)
Recombinant DNA technology (Immunological screening)Recombinant DNA technology (Immunological screening)
Recombinant DNA technology (Immunological screening)
 
STERILITY TESTING OF PHARMACEUTICALS ppt by DR.C.P.PRINCE
STERILITY TESTING OF PHARMACEUTICALS ppt by DR.C.P.PRINCESTERILITY TESTING OF PHARMACEUTICALS ppt by DR.C.P.PRINCE
STERILITY TESTING OF PHARMACEUTICALS ppt by DR.C.P.PRINCE
 
Unlocking the Potential: Deep dive into ocean of Ceramic Magnets.pptx
Unlocking the Potential: Deep dive into ocean of Ceramic Magnets.pptxUnlocking the Potential: Deep dive into ocean of Ceramic Magnets.pptx
Unlocking the Potential: Deep dive into ocean of Ceramic Magnets.pptx
 
Stunning ➥8448380779▻ Call Girls In Panchshil Enclave Delhi NCR
Stunning ➥8448380779▻ Call Girls In Panchshil Enclave Delhi NCRStunning ➥8448380779▻ Call Girls In Panchshil Enclave Delhi NCR
Stunning ➥8448380779▻ Call Girls In Panchshil Enclave Delhi NCR
 

RNA-seq: A High-resolution View of the Transcriptome

Editor's Notes

  1. I am going to spend a few minutes illustrating how existing and emerging high-throughput genomic technologies are being used to understand cancer, a mindnumbingly complex and disregulated biologic process.
  2. The first karyotypes were produced in 1956. Shown here is a comparison of a normal karyotype of a normal female and one from a tumor. By 1960, a karyotype of a cancer genome revealed the presence of the Philadelphia chromosome. Now known to represent the BCR-ABL fusion protein, it was not until 33 years later in 1993 that a drug, gleevec, become available that targeted the fusion product. By applying high-throughput microarray technologies, the Cancer Genetics Branch is striving to make observations of the cancer genome that will provide deeper understandings of the biology of cancer, to develop prognostic and diagnostic markers to improve patient-specific treatments, and to find promising targets for directed drug therapy.
  3. Since Knudson’s famous hypothesis proposing the two-hit model, our understanding of cancer as a genetic disease has progressed to the realization that cancer is not often a function of a single gene gone awry, but probably represents a complex interaction of multiple processes in the genome including altered copy number, gene expression, transcriptional regulation, chromatin modification, sequence variation, and DNA methylation. It is vital to the goal of producing better patient outcomes to understand not only what genes are involved in a certain type of cancer, but also how these other processes affect gene regulation. In short, an integrated view of the cancer genome is necessary and is now becoming possible.