Eikosstatistics & data science

Time Series, Health & Evidence Synthesis · Biostatistics & Clinical Trials

Computational Biostatistics: Bioinformatics, High Dimensionality and Omic Data

Public introduction · full guide in Eikos

Introduction

What this guide covers

Introduction Treatise on Computational Biostatistics

Overview

Topics covered

  • Introduction
  • The Precision Medicine Revolution and the Omic Era
  • Data Structures, Representation and Normalization Methods
  • 2.1 Abundance Metrics in RNA-Seq: RPKM, FPKM and TPM
  • 2.2 Robust Modeling: TMM (edgeR) and Median-of-Ratios (DESeq2) Methods
  • 2.3 Batch Effect and its Mathematical Correction

Related concepts

Main connections

  • Variance & standard deviation
  • Regularization (Lasso / Ridge / Elastic Net)
  • Linear algebra & matrices
  • p-value & significance
  • Hypothesis testing
  • Multiple testing & FWER/FDR

Compatible notation

Mathematical sample in LaTeX

The expression is rendered accessibly, with its LaTeX source preserved below.

p≫nwithp∈[103,107],n∈[101,103]
View LaTeX sourcep \gg n \quad \text{with} \quad p \in [10^3, 10^7], \quad n \in [10^1, 10^3]