ngs data generation dr laura emery. overview the ngs data explosion sequencing technologies an...
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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…