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mkdocs.yml
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site_name: Phylogenetic Data Science (IN DEVELOPMENT)
repo_url: https://github.com/eaton-lab/phylogenetic-data-science
edit_uri: edit/master/docs/
theme:
name: material
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# accent: orange
toggle:
icon: material/lightbulb
name: Switch to light mode
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# primary: teal
# accent: orange
toggle:
icon: material/lightbulb-outline
name: Switch to dark mode
favicon: /images/favicon.ico
icon:
logo: material/library
# admonition:
# <type>
features:
- navigation.instant
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# - toc.integrate # right-hav is always in toc
- search.highlight
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- content.code.annotate #
# - navigation.indexes
# - navigation.sections
# - navigation.expand
# - navigation.tabs.sticky
extra_css:
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extra_javascript:
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- javascripts/mathjax.js
- https://polyfill.io/v3/polyfill.min.js?features=es6
- https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-mml-chtml.js
extra:
analytics:
provider: google
property: G-HV34HZZD5N
# version:
# provider: mike
markdown_extensions:
# Python Markdown
- abbr
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- attr_list
- def_list
- footnotes
- meta
- tables
- md_in_html
- toc:
permalink: true
# Python Markdown Extensions
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generic: true
- pymdownx.betterem:
smart_enable: all
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nav:
- About/Ethos: index.md
- Installation/Software: installation.md
- Columbia course: course.md
- 0 - Coding Bootcamp:
- Getting started: bootcamp/getting-started.md
- 0.0 - Installation (conda): bootcamp/0.0-installation-conda.md
- 0.1 - Python Jupyter/Binder: bootcamp/0.1-jupyter-and-binder.md
- 0.2 - Python types: bootcamp/0.2-python-types.md # add link to vanderplas.
- 0.3 - Python functions: bootcamp/0.3-python-funcs.md # type hints at own link.
- 0.4 - Python classes: bootcamp/0.4-python-classes.md #
- 0.5 - Python style: bootcamp/0.5-python-style.md
# - 0.6 - Python iterators: bootcamp/0.6-python-iterators.md
# - 0.x - Python Data Science: bootcamp/python-datascience.md
# - 0.x - Python Jit compilation: bootcamp/jit-compile.md
# - 0.x - Python Algorithms: bootcamp/python-algorithms.md # dynamic, iteration,
- 1 - Trees as data:
- x.1 - Introduction: chapter-1/1.1-introduction.md
- x.2 - Tree Thinking: chapter-1/1.2-tree-thinking.md
- x.3 - Visualization: chapter-1/1.3-visualization.md
- 1.4 - Tree data structure: chapter-1/1.4-features-of-trees.md
- 1.5 - Code - Node class: chapter-1/1.5-code-node-class.md
- 1.6 - Code - Tree traversal: chapter-1/1.6-code-tree-traversal.md
- 1.7 - Code - Tree class: chapter-1/1.7-code-tree-class.md
- x.7 - Exercises: chapter-1/1.6-exercises.md
- 2 - Evolutionary models:
- 2.0 - Modeling evolution: chapter-2/2.0-modeling-evolution.md
# - x.1 - everything is descended from an ancestor
# - x.1 - whether or not we can infer that past is a separate question.
- 2.1 - Idealized population: chapter-2/2.1-idealized-population.md
- 2.2 - Wright-Fisher Process: chapter-2/2.2-wright-fisher.md
# - x.1 - assumptions on evolutionary process
# - x.1 - start by setting only population size and mutation
# - x.1 - we can make predictions about genetic diversity
# - x.1 - modeling and simulations
- 2.3 - The Coalescent: chapter-2/2.3-coalescent.md
# - x.1 - why coalescent thinking is powerful
# - x.2 - what is the coalescent model
# - 3.1 - Kingman Coalescent:
# - x.3 - why is this useful?
# - x.4 - some math examples
# - x.5 - probability statement, one rep is weak, many reps is strong.
# - x.6 - retiterate assumptions and constraints.
# - 2.2 - Coalescent Simulation: chapter-2/2.2-simulation.md
# - x.1 - coalescent simulation software exists
# - x.x - Code - estimate Ne using equations
# - x.2 - demographic models
# - x.3 - ...
# - 2.2 - Species Trees: chapter-2/2.3-species-trees.md
# - x.1 -
# - x.4 - Species Tree simulations (ipcoal): 3.4-ipcoal.md
# - x.x - Code - MSC probability...
# - 2.3 - Tree Sequences: chapter-2/2.4-tree-sequences.md
# - x.1 - Recombinaiton
# - x.2 - Genetic linkage
# - x.3 - ARGs
- 2.4 - Coalescent simulation: chapter-2/2.4-coalescent-simulation.md
- 2.x - Exercises: chapter-2/2.x-exercises.md
# - Reading and Exercises: 1-reading-list.md
# 1. how can we model a mutation: per generation a site one state to another: A->C
# 2. if this process occurs at many sites independently, then a starting sequence of DNA changes over time.
# 3. on a tree, different samples share different starting states (MRCA).
# 4. So, if this process occurs on a tree, then it leads to some sequences more similar than others.
# 5. Demonstrate this.
# 6. That process we just showed, represents a very simple MARKOV process.
# 7. assumptions of this included equal rates.
# 8. Could be different, e.g., we can describe diff rates w/ a matrix.
# 9. Example...
# 10. Using a Markov model is valuable b/c it can estimate historical process
# 11. Examples: its used in ... DNA
# 12. Compared to e.g., parsimony assumptions, where we count OBSERVABLE changes..
# this model can estimate the unobserved changes. Important b/c....
# 13. Functions to show the loss of information over time.
- 3 - Mutation Models:
- 3.0 - Modeling Evolution: chapter-3/3.x-DNA-Markov.md
# Evolution and Information:
# Molecular Evolution:
- 3.x - Probabilistic and Generative Models: .
# - assumptions of this model.
# - when is it used, and why.
# - demonstrate its shortcomings compared to infinite (speed?)
- 3.2 - Markov models: chapter-3/3.2-markov-models.md
# - statistical properties of Markov models
# -
# - 3.x - Bioinformatics: .
# - x.x - mutation, substitution, allele, haplotype (terminology)
# - x.x - orthology, homology, alignment
- 3.x - Other models: 3.x-other-models.md
# - x.x - phenotypic, stepwise, etc.
# - x.x - infinite-sites model: .
# - x.x - assumptions of this model.
# - x.x - when is it used, and why.
# - x.x - demonstrate its shortcomings using simulation
# - how to write this data using ipcoal? compute distances?
- Reading and Exercises: 1-reading-list.md
- 4 - Data:
- x.1 - data formats: 4.1-data-formats.md
- x.2 - strings, tables, and matrices: 4.2-strings-and-matrices.md
# - x.3 - SNP data (variant call format): 543-variant
- x.x - Code - simulating data/traits: x.x-simulating-traits.md
- x.x - Code - sequence alignment: x.x-sequence-alignment.md
- x.x - Code - converting file formats: x.x-converting-file-formats.md
- Exercises: read, write, parse, find, and clean phylip, fasta, fastq, and vcf data.
- 5 - Phylogenetic Inference:
- x.0 - introduction: .
- x.1 - history: .
- x.2 - choosing a method: .
- x.3 - ...
- x.4 - ...
- 6 - Inference (Parsimony):
- 6.0 - Fitch Parsimony: chapter-6/6.0-fitch-parsimony.md
- 6.1 - Character matrices: chapter-6/6.1-fitch-multiple-traits.md
- 6.2 - Sankoff Parsimony: .
# chapter-6/6.1-sankoff-parsimony.md
# - 6.2 - Code - heuristic search: .
# - 6.3 - Inferring: .
# - application: infinite sites NJ tree versus homoplasy... cite papers using NJ.
# - Reading and Exercises: .
- 7 - Inference (Distance-based):
- 7.0 - Distance based trees: chapter-7/7.0-introduction.md
- 7.1 - Code - Least-squares: chapter-7/7.1-least-squares.md
- 7.2 - Code - UPGMA: chapter-7/7.2-upgma.md
- 7.3 - Code - Neighbor Joining: chapter-7/7.3-neighbor-joining.md
- 7.4 - Applied examples: chapter-7/7.4-applied.md
- 7.5 - New Applications: chapter-7/7.5-new-applications.md
# - Exercises: TODO
# - Reading: TODO
- 8 - Inference (Likelihood):
- x.0 - Maximum Likelihood: .
- x.1 - Genealogies: .
- x.2 - Sequences: .
- x.3 - Inferring: .
- Reading and Exercises: .
- 9 - Multispecies Coalescent:
- 9.0 - Species trees: chapter-9/9.0-intro.md
- 9.1 - Coalescent likelihood: chapter-9/9.1-likelihood.md
- 9.2 - Genealogical thinking: chapter-9/9.2-genealogical.md
- 9.3 - Genetic thinking: chapter-9/9.2-genetics.md
- 9.4 - MSC likelihood: chapter-9/9.3-MSC.md
- Reading and Exercises: .