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on
1
Introduction
2
Disclosures
3
Sample Workflow
4
methylation data
5
normalization
6
beta value
7
classification
8
training data
9
feature selection
10
training classifier
11
dimensionality reduction
12
results
13
concordant data
14
validation
15
correlation
16
interference
17
Typical case
18
Disney Plot
19
Copy Number Plot
20
Discussion
21
Conclusions
22
Acknowledgements
23
Questions
24
Clinical Laboratory
25
Sharing the Classifier
26
Clinical Application
27
Constitutional Disorders
28
Additional Questions
29
Probability Score Recalibration
30
Can Pathologists Determine Classification of a Sample
Description:
Explore a comprehensive 35-minute conference talk from the Cancer Genomics Consortium's 2022 Annual Meeting, focusing on the clinical validation of whole genome methylation profiling classifiers for central nervous system tumors. Delve into the intricacies of sample workflow, methylation data analysis, and classification techniques. Learn about the normalization process, beta value interpretation, and the importance of training data in feature selection. Discover how dimensionality reduction impacts results and examine concordant data validation methods. Investigate typical cases through Disney Plots and Copy Number Plots, and engage in a thought-provoking discussion on the clinical applications of this technology. Gain insights into potential uses for constitutional disorders and explore the recalibration of probability scores. Conclude with a Q&A session addressing the role of pathologists in sample classification and the sharing of classifiers within the clinical laboratory setting.

Clinical Validation of Whole Genome Methylation Profiling Classifier for Central Nervous System Tumors

Cancer Genomics Consortium
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