calculate_AA_variation: Calculate AA variations on each position of the multiple...
In michalstolarczyk/BALCONY: Better ALignment CONsensus analYsis

Description Usage Arguments Details Value Examples

This function calculates AA variations on each position of the alignment which may be further used for the conservativity study of the set of sequences in quiestio

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calculate_AA_variation(alignment, threshold = NULL, grouped = F,
  grouping_method = "substitution_matrix", weights = NULL,
  pseudo_counts = F)

`alignment`	The data loaded with `read.alignment` function
`threshold`	(optional) A number in range 0-1. A of minimal frequency of occurences of amino acids at each position. Default: all the residues are visualized.
`grouped`	(optional) A logical indicating if the grouping of amino acids should be applied. Default: FALSE
`grouping_method`	(optional) A string which specifies the grouping method to be used. One of following: 'substitution_matrix', 'polarity', 'size', 'aromaticity'. Default: 'substitution_matrix'. Default: 'substitution_matrix' if grouped is TRUE.
`weights`	(optional) A vector of length equal number of sequences in the alignment object with weights to overcome the taxonomic bias in the conservation analysis.
`pseudo_counts`	(optional) A logical indicating if pseudo-counts should be added to the MSA. Pseudo-counts can be used only in non-group mode and without weights. Using these options with pseudo-counts will be suppressed. Default: FALSE

The output consists of amino acids and their fractions on each position of alignment. Amino acids with occurence frequencies lower than the threshold of user's choice are excluded.

Returns list of three matrices with tabelarized symbols of the most common AA in alignment column, percentage values for contributed AA and combined one.

`AA`	A matrix of AA on all alignment positions with decreasing frequencies in columns
`per`	The percentage of AA frequencies corresponding to the $AA
`matrix`	A combination of this two. The best suited element for visual inspection of the variability at each position

data("small_alignment")
alignment = delete_isoforms(small_alignment)
threshold=10
grouped = FALSE
var_aa=calculate_AA_variation(small_alignment, threshold, grouped)