NGS Data Generation Dr Laura Emery. Overview The NGS data explosion Sequencing technologies An example of a sequencing workflow Bioinformatics challenges.

NGS Data Generation

Dr Laura Emery

Overview

• The NGS data explosion

• Sequencing technologies

• An example of a sequencing workflow

• Bioinformatics challenges

The NGS data explosion

EBI biological data

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Bottlenecks to biological research

Source: Qiagen

NGS Technologies

• A variety of platforms available

• Differ in:

• Library preparation

• Sequencing chemistry

Comparison of NGS Technologies

Library preparation

Sequencing chemistry

Features

Roche 454 Emulsion PCR

Pyrosequencing

Longer read length, only available until 2016

Illumina HiSeq

Solid phase amplification

Reversible terminator

Best output to cost ratio, low error rates

Applied Biosciences SOLiD

Emulsion PCR

Sequencing by ligation

Highest accuracy

Pacific Biosciences RS II

Single molecule

Real time Very long read lengths, highest error rates

Example: Illumina NGS workflow

4. Data Analyses

3. Sequencing

2. Hybridisation and Amplification

1. Library Preparation

1. Library preparation

• RNA extraction

• Fragmentation and size selection

• cDNA synthesis

• Adapter ligation

RNA only

RNA only

1. Library preparation

• Alternative library preparation methods:

• Mate pair • Targeted • Strand specific

1. Library preparation

• Multiplexing (optional)

Example: Illumina NGS workflow

4. Data Analyses

3. Sequencing

2. Hybridisation and Amplification

1. Library Preparation

2. Hybridisation and Amplification

Example: Illumina NGS workflow

4. Data Analyses

3. Sequencing

2. Hybridisation and Amplification

1. Library Preparation

3. Sequencing

Errors!

3. Sequencing (Paired-end)

Example: Illumina NGS workflow

4. Data Analyses

3. Sequencing

2. Hybridisation and Amplification

1. Library Preparation

4. Data analyses: generalised pipeline

Data submission to public repository

Downstream analyses

Alignment and/or assembly

Filtering

QC

FASTQ

Otherdata

Bioinformatics challenges

• Library preparation biases

• Random hexamer priming

• GC content

• Data storage

• Data analysis

• Errors

• Mapping/assembly uncertainty

Bioinformatics challenges

• Library preparation biases

• Random hexamer priming

• GC content

• Data storage

• Data analysis

• Errors

• Mapping/assembly uncertainty

Sequence bias in the first 13 nucleotidesMethods for correction: Cufflinks, mmseq

Bioinformatics challenges

• Library preparation biases

• Random hexamer priming

• GC content

• Data storage

• Data analysis

• Errors

• Mapping/assembly uncertainty

GC-rich or AT-rich fragments have been found to be over/underrepresentedMethods for correction: EDASeq, CG correct

Bioinformatics challenges

• Library preparation biases

• Random hexamer priming

• GC content

• Data storage

• Data analysis

• Errors

• Mapping/assembly uncertainty

Conclusions

• NGS technologies provide us with new opportunities but new challenges

• You will learn more about overcoming these challenges during this course

• Furthermore, other omics technologies will be introduced

So over to Bernardo…