R Packages worth a look

Design of Observational Studies, Companion to the Second Edition ( DOS2 )

Contains data sets, examples and software from the Second Edition of ‘Design of Observational Studies’; see Rosenbaum, P.R. (2010) <doi:10.1007/978-1-4419-1213-8>.

Extend ‘tinytest’ with ‘diffobj’ ( ttdo )

The ‘tinytest’ package offers a light-weight zero-dependency unit-testing framework to which this package adds support of the ‘diffobj’ package for ‘diff’-style comparison of R objects.

Diversity Estimator ( DivE )

Contains functions for the ‘DivE’ estimator <doi:10.1371/journal.pcbi.1003646>. The ‘DivE’ estimator is a heuristic approach to estimate the number of classes or the number of species (species richness) in a population.

Clusters of Colocalized Sequences ( colocalized )

Finds clusters of colocalized sequences in .bed annotation files up to a specified cut-off distance. Two sequences are colocalized if they are within the cut-off distance of each other, and clusters are sets of sequences where each sequence is colocalized to at least one other sequence in the cluster. For a set of .bed annotation tables provided in a list along with a cut-off distance, the program will output a file containing the locations of each cluster. Annotated .bed files are from the ‘pwmscan’ application at < https://…/pwmscan.php>. Personal machines might crash or take excessively long depending on the number of annotated sequences in each file and whether chromsearch() or gensearch() is used.

Extracts the Backbone from Weighted Graphs ( backbone )

Provides methods for extracting from a weighted graph a binary or signed backbone that retains only the significant edges. The user may input a weighted graph, or a bipartite graph from which a weighted graph is first constructed via projection. Backbone extraction methods include the stochastic degree sequence model (Neal, Z. P. (2014). <doi:10.1016/j.socnet.2014.06.001>), hypergeometric model (Neal, Z. (2013). <doi:10.1007/s13278-013-0107-y>), the fixed degree sequence model (Zweig, K. A., and Kaufmann, M. (2011). <doi:10.1007/s13278-011-0021-0>), as well as a universal threshold method.

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