In this episode, I dusted off my genomic gloves with the HCLC-FC and CLIMB methods, waxed poetic with Python’s latest alpha release, and solved plotting mysteries with R-package ‘sherlock’.

References:

Regression discontinuity threshold optimization
Explaining predictive factors in patient pathways using autoencoders
HCLC-FC: A novel statistical method for phenome-wide association studies
Uncertainty-aware mixed-variable machine learning for materials design
Closed-form continuous-time neural networks
New statistical method improves genomic analyzes
synr: Analyze stimulus-color consistency test data
Profile plots in SAS
Optimal linear profile plots in SAS
Python 3.12.0 alpha 2 released
What is Interactive Analytics?
Top 9 Highest Paying Programming Languages (2023)
How to Analyze Likert Scale Data?
Top 10 Data Visualisation Tools Every Data Science Enthusiast Must Know
Open source is a hard requirement for reproducibility


R-packages:

exactLTRE: An Exact Method for Life Table Response Experiment (LTRE) Analysis
sherlock: Graphical Displays to Aid Structured Problem Solving and Diagnosis
cipheR: Encryption and Decryption with Text Ciphers
rjtools: Preparing, Checking, and Submitting Articles to the 'R Journal'
commafree: Call Functions Without Commas Between Arguments

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