Episode 34: Genomics, My Dear Watson

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