The efficient treatment and convenient analysis of experimental highthroughput (omics) data gets facilitated through this collection of diverse functions. Several functions address advanced objectconversions, like manipulating lists of lists or lists of arrays, reorganizing lists to arrays or into separate vectors, merging of multiple entries, etc. Another set of functions provides speedoptimized calculation of standard deviation (sd), coefficient of variance (CV) or standard error of the mean (SEM) for data in matrixes or means per line with respect to additional grouping (eg n groups of replicates). A group of functions facilitate dealing with nonredundant information, by indexing unique, adding counters to redundant or eliminating lines with respect redundancy in a given referencecolumn, etc. Help is provided to identify very closely matching numeric values to generate (partial) distance matrixes for very big data in a memory efficient manner or to reduce the complexity of large datasets by combining very close values. Other functions help aligning a matrix or data.frame to a reference using partial matching or to mine an experimental setup to extract patterns of replicate samples. Many times large experimental datasets need some additional filtering, adequate functions are provided. Convenient data normalization is supported in various different modes, parameter estimation via permutations or bootstrap as well as flexible testing of multiple pairwise combinations using the framework of 'limma' is provided, too. Batch reading (or writing) of sets of files and combining data to arrays is supported, too.
Package details 


Author  Wolfgang Raffelsberger [aut, cre] 
Maintainer  Wolfgang Raffelsberger <w.raffelsberger@gmail.com> 
License  GPL3 
Version  1.15.0.3 
Package repository  View on CRAN 
Installation 
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