The Wagner parsimony model implemented in Count with the gain penalty of 1 was used to reconstruct gene content evolution in the history of the PAH-degrading gene groups as well as four types of the RHO group.
The model was fit using the maximum-likelihood procedure implemented in Count, with the default null model as a starting point, and with gain, loss, and duplicate rates estimated for all branches of the tree.
A limitation of the evolutionary reconstructions reported here is that the ML approach implemented in Count [ 22, 75] takes as input the gene family membership matrix, without explicitly exploiting information on the level of sequence similarity and phylogenetic relationships within individual families.
An in-house Python script was used to count the reads mapped within each annotation feature in a similar way as implemented in htseq-count utility software (HTSeq: analysing high-throughput sequencing data with Python. [ http://www-huber.embl.de/users/anders/HTSeq/]).de/users/anders/HTSeq/]
We compared models of increasing complexity, implemented in the Count program, with respect to model fit, robustness, and stability.
To model losses and gains of CTD repeats and lysine content within each ancestral clade, we used Wagner parsimony (with an equal weight for gains and losses) as implemented in the Count program for analysis of numerical observations on a phylogeny [ 40].
These correlations and statistics are implemented in the site-counting model, and results from the site-counting model and the KMC-ARS model are in good agreement.
To investigate the evolution of microsporidian genomic diversity, we applied a phylogenetic gain loss-duplication model implemented in the progain loss-duplication10) on the inferred phylogeny to estimodelthe number of gaimplementedses as well as the expansinn and conthection of program families during the evolution of MiCountoridia (fig. 1).
The generalized linear model Quasi-likelihood spline method assuming negative binomial distribution of read counts implemented in the QuasiSeq package was used to compute a P value for each gene.
} Then, a custom algorithm implemented in JAVA is used to count the number of common AGROVOC URIs between the AGRIS entity and web URLs returned by the previous query, storing the top 20 most relevant web resources in the Recommender Database.
