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pirouette_examples

pirouette examples.

Overview

Experiments for the pirouette article supplementary material

In the pirouette article, one DD tree is used, from example 30.

For the supplementary materials, certain parameters have been investigated:

  • Build Status Build Status Build status Build status 30: Use one DD tree
  • Build Status Build Status Build status Build status 28: use a distribution of DD trees (instead of just one)
  • Build Status Build Status Build status Build status 31 use multiple artifical trees (instead of just one)
  • Build Status Build Status Build status Build status 20: the effect of the number of taxa
  • Build Status Build Status Build status Build status 21: the effect of DNA sequence length
  • Build Status Build Status Build status Build status 19: the effect of halving a DNA sequence length (that is, from 1k to 500 nucleotides)
  • Build Status Build Status Build status Build status 34: the effect of double the DNA sequence length (that is, from 1k to 2k nucleotides)
  • Build Status Build Status Build status Build status 27: the effect of non-clock like models
  • Build Status Build Status Build status Build status 22: The effect of assuming a Yule tree prior on a Yule tree
  • Build Status Build Status Build status Build status 26: The effect of assuming a Yule tree prior on a BD tree
  • Build Status Build Status Build status Build status 23: The effect of differently common diversity-dependent trees
  • Build Status Build Status Build status Build status 18: The effect of equal or equalized mutation rate in the twin alignment
  • Build Status Build Status Build status Build status 24: The effect of mutation rate
  • Build Status Build Status Build status Build status 25: the effect of RNG in the alignment for the error distribution
  • Build Status Build Status Build status Build status 29: the effect of MCMC chain length on ESS
  • Build Status Build Status Build status Build status 32 use DD tree with 12 taxa (instead of 6)
  • Build Status Build Status Build status Build status 33 use 24 taxa (instead of 6)
  • Build Status Build Status 35 use a mutation rate of 0.25 / crown_age (instead of 1.0 / crown_age)
  • Build Status Build Status 36 use a mutation rate of 0.50 / crown_age (instead of 1.0 / crown_age)
  • Build Status Build Status 37 use a mutation rate of 0.75 / crown_age (instead of 1.0 / crown_age)
  • Build Status Build Status 38 use a mutation rate of 1.25 / crown_age (instead of 1.0 / crown_age)
  • Build Status Build Status 39 use a mutation rate of 1.50 / crown_age (instead of 1.0 / crown_age)
  • Build Status Build Status 40 use a mutation rate of 2.00 / crown_age (instead of 1.0 / crown_age)
  • Build Status Build Status 41 use 32 taxa (instead of 6)
  • Build Status Build Status 42 use 40 taxa (instead of 6)
  • Build Status Build Status 43: Use 10x shorter MCMC chain length (from 10M to 1M), sample 1k times
  • Build Status Build Status 44: Use 100x shorter MCMC chain length (from 10M to 100k), sample 1k times
  • Build Status Build Status 45: Use 10x longer MCMC chain length (from 10M to 100M), sample 1k times

Other published experiments

Combinations of pirouette functionality

These are all runs based on one phylogeny. Each of these examples serves as a high-level test.

Example Phylogeny Gen Cand Twin TTM DSL STRAF STWAF Err Travis CI logo AppVeyor logo
1 Yule Y N N - 1k STD - nLTT Build Status Build status
2 Yule Y Y N - 1k STD - nLTT Build Status Build status
3 Fict Y Y Y BD 1k STD STDEQ nLTT Build Status Build status
4 Fict Y N N - 1k STD - nLTT Build Status Build status
5 Fict Y Y N - 1k STD - nLTT Build Status Build status
6 Yule Y Y Y BD 1k STD STDEQ nLTT Build Status Build status
7 Yule Y N Y BD 1k STD STDEQ nLTT Build Status Build status
8 Yule N Y Y BD 1k STD STDEQ nLTT Build Status Build status
9 Fict Y N Y BD 1k STD STDEQ nLTT Build Status Build status
10 Fict N Y Y BD 1k STD STDEQ nLTT Build Status Build status
11 Yule N Y N - 1k STD - nLTT Build Status Build status
12 Fict N Y N - 1k STD - nLTT Build Status Build status
13 Fict Y Y Y BD 1k STD STDEQ ADG Build Status Build status
14 Fict Y Y Y BD 1k STD STDEQ LTN Build Status Build status
15 Fict Y N Y CT 1k STD STDEQ nLTT Build Status Build status
16 Fict Y N Y CT 1k NSL STDEQ nLTT Build Status Build status
17 Fict Y N Y CT 1k NSU STDEQ nLTT Build Status Build status
18 Fict Y Y Y BD 1k STD STD nLTT Build Status Build status
34 Fict Y Y Y BD 10k STD STDEQ nLTT Build Status Build status
30 DD Y Y Y BD 10k STD STDEQ nLTT Build Status Build status

Legend

Column Value Description
Phylogeny Yule The true phylogeny is created from a Yule (pure-birth) model
Phylogeny Fict The true phylogeny is completely fictious and artificial. If any, it follows both a multiple-birth and a protracted speciation model
Gen Y/N A generative model is yes/no hand-picked for this experiment
Cand Y/N A set of candidate models is yes/no used in this experiment
Twin Y/N The background noise is measured yes/no by using twinning
TTM BD,CT Twin tree method, BD=birth_death, Y=yule, CT=copy_true
DSL [1,->> DNA Sequence Length in number of nucleotides
STRAF STD,NSL,NSU Simulate TRue Alignment function: STD: standard, NSL: node_sub_linked and NSU: node_sub_unlinked
STWAF STD,STDEQ Simulate TWin Alignment function, STD: standard, STEQ: standard with equal number of mutations
Err nLTT,ADG,LTN The error statistic used is nLTT, ADG: absolute delta gamma, LTN: Log-transformed nLTT statistic

FAQ

Why are some TTM and STWAF values empty?

If there is no twinning (Twin = N), one cannot specify a TTM ('Twin Tree Model'), nor a STWAF ('Simulate TWin Alignment Function').

Why are some AppVeyor values empty?

These are empty when there are candidate models (Cand = T), because model comparison is unsupported on Windows.

How are the examples related?

See the table, or use this figure:

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