RNAseq Pevsner

8/10/2019 RNAseq Pevsner

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RNAseq: design principles

How RNAseq works

Data analysis

Outline


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Experimental design principles: randomization, replication

RNAseq specific effects

Sequencing depth

Paired-end sequencing

Biases of NGS

Sample size calculation

Validation

RNAseq: experimental principles

Fang Z, Cui X. Brief. Bioinf. (2011) 12:280


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Disc1

k/o

wt

barcode 1

barcode 2

barcode 3

barcode 4

barcode 5

barcode 6

barcode 7

barcode 8

barcode 9

pool, sequence

demultiplex

Experimental design for RNAseq


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Disc1

k/o

wt

Experimental design for RNAseq

plus

virus

wt Pcm1

k/o

wt

date of RNA

isolation: best

to coordinate

sample size

can vary, but try

for n>3

barcoding

strategy

depth of

coverage


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How RNAseq works

Data analysis

Outline


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mRNA or RNA

removecontaminant DNA

fragment RNA

reverse transcribe

to cDNA

Data generation Data analysis

Ligate sequence

adaptors

Select size range

Sequence cDNA

ends

raw reads

remove artifacts

correct errors

assemble

transcripts

Post-process

transcripts

Align reads to

transcripts to

quantifyexpressionMartin JA Wang Z NRG (2011) 12:671


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RNAseq single reads: map to genomic DNA,

detect alternative splicing events

Ozsolak F, Milos PM NRG (2011) 12:87


9/21Ozsolak F, Milos PM NRG (2011) 12:87

RNAseq paired-end reads: map to genomic DNA,

get better map of transcript structure

and of chimeric sequences


10/21Martin JA Wang Z NRG (2011) 12:671

Reference-based transcriptome assembly

(a) Splice-align reads to the genome


11/21Martin JA Wang Z NRG (2011) 12:671


(b) Build graph of alternative splicing events


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Martin JA Wang Z NRG (2011) 12:671


(c) Traverse graph to assemble variants


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(d) Assemble isoforms


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Accuracy: % of correctly assembled bases using references

Completeness: % expressed reference transcripts covered by

all the assembled transcripts

Contiguity: % of expressed reference transcripts covered by a

single, longest-assembled transcript

Chimerism: % of chimeras due to misassemblies (spans two

or more different reference genes)

Variant resolution: % of transcript variants resolved

Quality metrics for assessing transcriptome assemblies



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Ozsolak F, Milos PM NRG (2011) 12:87

Emerging technologies for single-cell gene

expression profiling


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How RNAseq works

Data analysis

Outline


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Bowtie: short read aligner

TopHat: align RNAseq reads togenome, find splice sites

Cufflinks: assembles

transcripts, finds differentially

expressed transcripts

CummRbund: explore data

Trapnell C, Nature Prot. (2012) 7:563


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Galaxy for RNAseq analysis:

web-based collection of tools for bioinformatics analysis


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Galaxy for RNAseq analysis

Tools panel includes Tophat,

Cufflinks for RNAseq analysis


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History panel shows data files for

analysis (can be included in

transparent, reproducible

workflows)


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Display panel shows data

files; here fastq files from

RNAseq with raw sequence

data and base quality scores

Documents

RNAseq Pevsner