Search results
This section focuses first on how we estimate distances, depending upon the level of interest, and then highlights some approaches for visualizing and gaining inferences from the distance matrix itself.
Computing genetic distances using the Alignment object# Abbreviations listed from available_distances() can be used as values for the distance_matrix(calc=<abbreviation>) . from cogent3 import load_aligned_seqs aln = load_aligned_seqs ( "data/primate_brca1.fasta" , moltype = "dna" ) dists = aln . distance_matrix ( calc = "tn93" , show_progress ...
Computing genetic distances using the Alignment object¶ Abbreviations listed from available_distances() can be used as values for the distance_matrix(calc=<abbreviation>).
Genetic distance, in simple terms, is the number of alleles at which two individuals differ. For example, matches at 111/111 markers have a genetic distance of 0, while matches at 21/25 have a genetic distance of 4. These calculations can be performed at various levels of confidence.
The distance matrix is widely used in the bioinformatics field, and it is present in several methods, algorithms and programs. Distance matrices are used to represent protein structures in a coordinate-independent manner, as well as the pairwise distances between two sequences in sequence space.
Genetic distance is a measure of the genetic divergence between species or between populations within a species, whether the distance measures time from common ancestor or degree of differentiation. Populations with many similar alleles have small genetic distances.
The Geographic Distance Matrix Generator is a platform-independent Java application that implements the same powerful suite of spherical functions as the Perpendicular Distance Calculator to compute all pair wise distances from a simple list of geographic coordinates.
