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Half-time (Improved methods for identifying biomarkers (NormalyzerDE (High…
Half-time
Improved methods for identifying biomarkers
Visualization
Tools
JupyterRUtils
:question: Visualization strategies (how much emphasis?)
PCA
P-value histograms
Vulcano plots
MA plots
Machine learning
Selecting for important features
Correlation
Other reduction strategies
Countering technical bias in proteomics experiments
Batch effects
How do know what bias to counter?
NormalyzerDE
Normalization and statistical comparisons
RT-based differential expression
High availability
Server
Bioconductor
Singularity container
P-value histogram
Study insights
Limma outperforming ANOVA
RT-segmented performing well in these studies
Optimal normalization methods vary
Covariate compensation
Linking genomics to proteomics
Outlook
Future developments
Further studies
Potato follow up study
Bull follow up study
Further methodolical advances
Verify the marker studies
Think more about optimal ways of studying them
Investigate how to use visualizations to see what needs to be seen
Developing biomarkers for agriculture
Climate and potato
Impact
Better adaption of potato to conditions in northen Sweden
Environmental impact?
Aim
Develop marker to identify variety differences in ability to adapt to growing in northen Sweden
Current outcome
:sunrise_over_mountains: Significant markers in different varieties
Challenges & Solutions
MS column swap + partially randomized data
Explicitly asking for rerun of a number of samples
Inclusion of batch correcting variable in statistical tests
Bull and fertility
Impact
Reducing breeding cycles from 6 years
What we study
Proteome in seminal plasma
Aim
Identify protein biomarkers predictive of fertility
Develop powerful predictor using statistics or machine learning methods
Challenges
Different biological batches
Clear outlier bull
:bow_and_arrow: Oat and
Fusarium
Impact
Resistance
Healthy and Swedish
Results
Proteogenomic study
:sunrise_over_mountains: Linking proteins to genomics
Potential markers
Challenges & Solutions
(1) Major unknown batch effect
Splitting of data
Introduction
:question: General talk about biomarkers?
Where can they be useful?
Diseases
Long breeding cycles
Environmental
Marker assisted breeding
What has been done
Proteomics for breeding
Challenges in omics-data
Technical bias
Normalization
Batch effects
Visualization
What you look for can be hidden in plain sight
Reference categories
Biomarkers
Proteomics for biomarkers
Marker assisted breeding
Impact points
Methods
Normalization
Batch effects
Visualizations
Breeding
Oat
Potato
Bull