Covers the principles and tools for reproducible research in biostatistics, emphasizing the importance of complete documentation and the use of text editors for compiling source documents.
Explores robust regression in genomic data analysis, focusing on downweighting large residuals for improved estimation accuracy and quality assessment metrics like NUSE and RLE.
Explores the challenges of multiple testing in genomic data analysis, covering error rate control, adjusted p-values, permutation tests, and pitfalls in hypothesis testing.
Explores tools and models for Next-Generation Sequencing data analysis, covering DNA sequencing technologies, data analysis pipelines, and statistical models.
