Omics Data Analysis

What are Omics

Omics refers to large-scale, high-throughput fields of biology that systematically measure and characterize entire classes of molecules within a biological system.

Omics field What is measured Typical technologies Stability Distance from current phenotype Main question
Genomics DNA sequence & variation Whole-genome sequencing, WES High Farther What genetic variants does a person carry?
Transcriptomics RNA abundance & splicing RNA-seq, microarrays Medium Intermediate Which genes are being transcribed?
Proteomics Proteins & modifications Mass spectrometry (LC-MS/MS), TMT/iTRAQ Medium-low Closer Which proteins are expressed or circulating?
Metabolomics Small molecules & metabolites MS, NMR Low Very close What is the current metabolic state?
Epigenomics Chromatin state & methylation ATAC-seq, ChIP-seq, bisulfite sequencing

Common Omics Data Analysis Workflow

  1. Define biological / clinical question
  2. Data preprocessing and QC
  3. Normalization and transformation
  4. Differential analysis
  5. Dimensionality reduction and clustering
  6. Functional interpretation
  7. Validation and biological interpretation

Common Analysis Methods

Differential analysis

= comparisons between groups (e.g., disease vs control)

metrics

visualization

Enrichment analysis

See LearningNotes/Enrichment Analysis

Network analysis

PPI (Protein-Protein Interaction) network analysis

= constructs an interaction map using databases like STRING or BioGRID to reveal hubs and regulatory modules

Multi-omics integration

Specific Omics Analysis