phylogram - Dendrograms for Evolutionary Analysis
Contains functions for developing phylogenetic trees as deeply-nested lists ("dendrogram" objects). Enables bi-directional conversion between dendrogram and "phylo" objects (see Paradis et al (2004) <doi:10.1093/bioinformatics/btg412>), and features several tools for command-line tree manipulation and import/export via Newick parenthetic text.
Last updated 5 years ago
peer-reviewed
8.49 score 11 stars 9 packages 209 scripts 911 downloadskmer - Fast K-Mer Counting and Clustering for Biological Sequence Analysis
Contains tools for rapidly computing distance matrices and clustering large sequence datasets using fast alignment-free k-mer counting and recursive k-means partitioning. See Vinga and Almeida (2003) <doi:10.1093/bioinformatics/btg005> for a review of k-mer counting methods and applications for biological sequence analysis.
Last updated 6 years ago
8.17 score 26 stars 6 packages 63 scripts 447 downloadsaphid - Analysis with Profile Hidden Markov Models
Designed for the development and application of hidden Markov models and profile HMMs for biological sequence analysis. Contains functions for multiple and pairwise sequence alignment, model construction and parameter optimization, file import/export, implementation of the forward, backward and Viterbi algorithms for conditional sequence probabilities, tree-based sequence weighting, and sequence simulation. Features a wide variety of potential applications including database searching, gene-finding and annotation, phylogenetic analysis and sequence classification. Based on the models and algorithms described in Durbin et al (1998, ISBN: 9780521629713).
Last updated 4 months ago
6.56 score 22 stars 3 packages 37 scripts 456 downloadsinsect - Informatic Sequence Classification Trees
Provides tools for probabilistic taxon assignment with informatic sequence classification trees. See Wilkinson et al (2018) <doi:10.7287/peerj.preprints.26812v1>.
Last updated 3 years ago
5.76 score 14 stars 82 scripts 731 downloadsdclust - Divisive Hierarchical Clustering
Contains a single function 'dclust' for divisive hierarchical clustering based on recursive k-means partitioning (k = 2). Useful for clustering large datasets where computation of a n x n distance matrix is not feasible (e.g. n > 10,000 records). For further information see Steinbach M, Karypis G, Kumar V (2000) A Comparison of Document Clustering Techniques. Proceedings of World Text Mining Conference, KDD2000, Boston.
Last updated 5 years ago
2.00 score 1 stars 1 scripts 150 downloads