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Analysis Guide

Draft: This section is the guide to downstream analyses that start from assembled outputs or SNP-capable HDF5 inputs.

Summary

Analysis Guide will document the methods that run on filtered SNP or sequence data inside ipyrad2 or through wrapped external tools.

Who This Section Is For

  • Users moving from assembled outputs into downstream analysis
  • Users choosing between built-in analyses and exported external workflows

Page Map

  • pca: PCA, t-SNE, and UMAP on SNP-capable HDF5 data
  • dapc: sklearn-backed DAPC-style clustering on SNP-capable HDF5 data
  • popgen: built-in population-genetic summary statistics from sequence or SNP-capable HDF5 inputs
  1. Start here for method selection.
  2. Read pca if you want PCA-family ordinations from SNP HDF5 data.
  3. Read dapc if you want DAPC-style clustering and discriminant coordinates from SNP HDF5 data.
  4. Read popgen if you want diversity, differentiation, heterozygosity, or SFS summaries inside ipyrad2.
  5. Return to Writing Outputs if you need an exported format instead.
  • Writing Outputs
  • Files and Data Types

Open TODOs

  • Add an overview table covering PCA-family, DAPC, admixture, sNMF, popgen, and converters.