[Diversity] 다양성 지표 (Alpha diversity, Beta diversity)

Alpha diversity는 샘플 '내' 다양성을 나타내고, Beta diversity는 샘플 '간' 다양성을 나타낸다.

 

Alpha 및 beta diversity를 나타내는 데 사용되는 수식은 하나가 아니라 다양하게 존재하는데, 그 종류는 다음과 같다.

 

• Alpha diversity metrics
  • Shannon’s diversity index (a quantitative measure of community richness)
  • Observed Features (a qualitative measure of community richness)
  • Faith’s Phylogenetic Diversity (a qualitiative measure of community richness that incorporates phylogenetic relationships between the features)
  • Evenness (or Pielou’s Evenness; a measure of community evenness)

 

• Beta diversity metrics
  • Jaccard distance (a qualitative measure of community dissimilarity)
  • Bray-Curtis distance (a quantitative measure of community dissimilarity)
  • unweighted UniFrac distance (a qualitative measure of community dissimilarity that incorporates phylogenetic relationships between the features)
  • weighted UniFrac distance (a quantitative measure of community dissimilarity that incorporates phylogenetic relationships between the features)
  • 즉, binary metrics는 rare taxa에서의 variations에 민감하고 (Jaccard, unweighted UniFrac), quantitative metrics는 abundant taxa에서의 variation에 민감하다 (Bray-Curtis, weighted UniFrac). 그래서 샘플에 rare taxa가 많다면 전자, 아니라면 후자를 사용한다.

 

연구 목적 및 상황에 맞게 적절한 metric을 사용하여 분석하면 된다.

 

 

Reference

• docs.qiime2.org/2021.2/tutorials/moving-pictures/