Exploring next-generation sequence data requires an iterative process whereby a researcher can find a "needle in the haystack" that contributes to a particular disease or other phenotype. Once that needle has been found, a workflow can be established for analyzing other samples or to create a repeatable, time-effective process for clinical usage.
Yet, repeating a workflow that involves several different quality control, filtering, and analysis steps is burdensome and error-prone.
To solve this problem, we introduce custom workflow automation in SVS, which allows you to collapse dozens of steps into a few run-specific options. This click-and-go process saves an exponential amount of time while eliminating the inevitable user error that happens with tedious repetition and ensures that the exact same protocol is followed with each run, a critical requirement for use in the clinic.
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Making NGS Data Analysis Clinically Practical: Repeatable and Time-Effective Workflows
1. Autumn Laughbaum, Biostatistician
with introduction by Dr. Andreas Scherer,
President & CEO
Making NGS Data Analysis Clinically Practical:
Repeatable and Time-Effective Workflows
2. Use the Questions pane in your
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Questions during
the presentation
4. Hands-on Time Savings
2 weeks
2 minutes
2 hours
1 trio using Excel 100 trios
using SVS
Unlimited trios
using automated
workflow
5. Today’s Agenda
Status Quo
Example Workflow: Ogden Syndrome
Example Workflow: Trio Analysis
Discussion
1
2
3
4
Moving from Excel > SVS > Automated Workflows
General sequencing workflow
9. Analyzing Sequencing Data
Filter to coding regions
Non-
synonmyous
variants
2 variants
Filter based on
population frequencies
Functional
prediction
10,000
30,000
35,000
40,000
Data from
secondary analysis
pipeline (VCF) –
2 million variants
Inheritance
pattern
Filter on read depth & quality
score
3,000
13. Ogden Syndrome
Filter based
on VCF
quality
metrics
Filter based
on
population
frequencies
Annotate
based on
functional
predictions
Filter based
on variant
classification
Filter based
on
inheritance
pattern
5 Samples
107,000 variants
1 damaging
variant
Ref_Alt
Alt
28. Clinicians vs. Researchers
Clinicians
Running well-defined
workflow on additional
samples
Minimum user-interface
knowledge
Small learning curve
Limited hands-on time
Researchers
Building and testing workflows
More complex but intuitive
interface
Larger learning curve
Power to investigate and
manipulate data
29. Conclusion – The GHI Approach
Work closely
with clients to
learn about
needs and
develop
workflow
specification
Create document
and workflow
diagram outlining
specifications
and
requirements
Build automated-
workflow
prototype
Thorough
internal testing
and complete
documentation
Finished product
works seamlessly
within SVS
30. Use the Questions pane in your
GoToWebinar window
Questions during
the presentation