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paramo's Introduction

PARAMO

Phylogenetic Ancestral Reconstruction of Anatomy by Mapping Ontologies

PARAMO pipline is a set of R scripts for reconstructing organismal ancestral anatomies. It appropriately models anatomical dependencies and uses ontology-informed amalgamation of stochastic maps to reconstruct phenotypic evolution at different levels of anatomical hierarchy including entire phenotypes. This approach provides new opportunities for tracking phenotypic radiations and evolution of organismal anatomies.

The PARAMO tutorial is given in PARAMO_pipeline.pdf, it can be viewed by clicking on the pdf file directly from within GitHub. To run the pipline, you need to copy it to your computer and follow the instructions given in the tutorail. To copy, use either "Cloned or download" icon in the right upper coner or the following command:

$ git clone git://github.com/sergeitarasov/PARAMO

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paramo's Issues

STEP 4 = four-state character Rev file creation

Hi Sergei,

Really looking forward to trying PARAMO but I am working through the pipeline and am stuck in a few places. I have made it to STEP 4.

  1. In STEP 4 at
    # write Rev file for dependent four-state character C3-2 setwd("~/Documents/Recon-Anc_Anat/Supplementary_materials")

Is this simply the same for loop used to create the two-state character Rev file? These is no code showing how to do this in the pipeline.

  1. It is unclear where the output from the SMMs go into the Rev file (Character Evolution Model, I assume). Also, should these SMMs be created prior to and inserted into the PARAMO_template that is then used for making each Rev file for each character?

  2. Lastly, I am not familiar with RevBayes and I am unsure how one manipulates the NUM_STATES and the SMMs to match their own data. For example, I have 5 traits, two of which are dependent on one another. Would I then adjust NUM_STATES to 5? If so, how would someone input that into the SMM creation? Sorry if that is a completely newb question.

Thanks for this program.

Cheers,
Cody Coyotee

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