Introduction

This walkthrough will take you through the steps of generating each piece of data needed to run InPhyNet to infer a 50 taxa network rapidly and accurately. Data used at each step of this walkthrough is available via functions that are built-in to InPhyNet.jl, so feel free to follow along or use your own data instead!

Requirements:

• Julia installed
• InPhyNet and SNaQ Julia packages installed

Steps:

|| Step | Input | Output | |-|–––|–––-|––––| | 1 | Estimate a pairwise distance matrix | Input data $I^*$ | Matrix $D$ | | 2 | Separate your taxa into subsets | $D$ | Subsets $\mathbf{S}=\{S_i\}_{i=1}^k$ | | 3 | Infer "constraint" networks on your subsets of taxa | $I,\mathbf{S}$ | Networks $\mathbf{N}=\{N_i\}_{i=1}^k$ | | 4 | Put it together with InPhyNet | $D,\mathbf{N}$ | Species network $\mathcal{N}$ |

\[^*I\]

can be any form of input data with which a distance matrix and semi-directed networks can be computed and inferred. Here, we utilize estimated gene trees.