Course: Bioinformatics for Biomedical Research (2014). Session: 3.1- Brief Overview to Amplicon Variant Analysis. Statistics and Bioinformatisc Unit (UEB) & High Technology Unit (UAT) from Vall d'Hebron Research Institute (www.vhir.org), Barcelona.

1. Hospital Universitari Vall d’Hebron
Institut de Recerca - VHIR
Institut d’Investigació Sanitària de l’Instituto de Salud Carlos III (ISCIII)
Bioinformàtica per la
Recerca Biomèdica
http://ueb.vhir.org/2014BRB
Ferran Briansó
ferran.brianso@vhir.org
20/05/2014
BRIEF OVERVIEW TO
AMPLICON VARIANT ANALYSIS

2. 1. DISCLAIMER
2. BASIC CONCEPTS
3. NGS APPROACH
4. SOURCES OF ERROR
5. CLINICAL RELEVANCE
6. BAD NEWS / GOOD NEWS
5
1
2
3
5
6
PRESENTATION OUTLINE
4

3. DISCLAIMER1
3Extracted from Dr Kassahn's publicly shared slides (2013)

4. BASIC CONCEPTS2
4
2
* Being able to characterize viral populations rapidly and
accurately is important for understanding pathogenesis,
interplay between viruses and humoral responses, and the
evolution of drug resistance
* Both HIV-1 and HCV exist as viral quasispecies in a host, i.e.
many distinct viral strains are circulating at any given moment in
time
* NGS has the potential to directly sequence many such strains
* Using multiplexing (multiple samples/run), high throughput
can be achieved

5. 5
2 BASIC CONCEPTS
* Which mutations are real?
- Sequencing error
- Assay error / reproducibility
* What frequency of mutations matter clinically?
* DRAMs = Drug resistance associated mutations
* Cloning/Single genome sequencing generates ~10-100
sequences; how representative is this of the entire population?
* NGS approach obtain 1000s of reads/sample from a single run

6. 6
3 NGS APPROACH

7. SOURCES OF ERROR
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4

8. 454 SEQUENCING ERROR RATES
8
4

9. 454 SEQUENCING ERROR RATES
8
4

10. CLINICAL RELEVANCE
9
5

11. BAD NEWS / GOOD NEWS1
10
6

12. BAD NEWS / GOOD NEWS1
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6