Cogent3 Cookbook

Contents:

• Introduction
• Manipulating biological data
  • Sequences and Alignments
    • Molecular types
    • Loading nucleotide, protein sequences
    • Alphabets
    • Sequence
    • Protein sequences
    • Collections and Alignments
    • Annotations
    • Annotations with coordinates
  • Genetic code
    • Available genetic codes
    • Getting a genetic code with get_code()
    • Translate DNA sequences
    • Translate all six frames
    • Find out how many stops in a frame
    • Translate a codon
    • Look up the amino acid corresponding to a single codon
    • Or get all the codons for one amino acid
    • For a group of amino acids
    • Converting the CodonAlphabet to codon series
    • Obtaining the codons from a DnaSequence object
  • Trees
    • Trees
    • Phylonodes Methods
  • Tables
    • Tabular data
• Building alignments
  • Using the cogent3 aligners
    • Running a pairwise Needleman-Wunsch-Alignment
    • Running a progressive aligner
  • Converting gaps from aa-seq alignment to nuc seq alignment
• Genetic distance calculation
  • Fast pairwise distance estimation
  • Computing genetic distances using the Alignment object
  • Using the distance calculator directly
  • Likelihood based pairwise distance estimation
• Building phylogenies
  • Building A Phylogenetic Tree From Pairwise Distances
  • Directly via alignment.quick_tree()
    • Using the DistanceMatrix object
    • Explicitly via DistanceMatrix and cogent3.phylo.nj.nj()`
    • Directly from a pairwise distance dict
  • By Least-squares
  • By ML
• Evolutionary Analysis Using Likelihood
  • Specifying substitution models
    • The available pre-defined substitution models
    • Getting a substitution model with get_model()
    • Rate heterogeneity models
  • Making a likelihood function
    • Providing an alignment to a likelihood function
    • Scoping parameters on trees – time heterogeneous models
    • Specifying a parameter as constant
    • Providing a starting value for a parameter
    • Setting parameter bounds for optimisation
    • Setting an upper bound for branch length
    • Specifying rate heterogeneity functions
    • Specifying Phylo-HMMs
    • Fitting likelihood functions - Choice of optimisers
    • How to check your optimisation was successful
    • Overview of the fitted likelihood function
    • Testing Hypotheses - Using Likelihood Ratio Tests
    • Determining confidence intervals on MLEs
    • Saving results
    • Reconstructing ancestral sequences
    • Tips for improved performance – sequentially build the fitting
• Useful Utilities
  • UnionDict – a dict with set like operations and keys as attributes
    • Accessing elements of a UnionDict
    • Updating a UnionDict
    • Accessing a non-existent UnionDict key
  • Using Cogent3’s optimisers for your own functions
  • Miscellaneous functions
    • Identity testing
    • Force a variable to be iterable
    • Curry a function
    • Test to see if an object is iterable
    • Test to see if an object is a single char
    • Flatten a deeply nested iterable
    • Test to determine if list of tuple
    • Create a case-insensitive iterable
    • Construct a distance matrix lookup function
    • Check class types
    • Delegate to a separate object
    • Wrap a function to hide from a class
    • Construct a constrained container