vac18

The data come from a trial evaluating a vaccine based on HIV-1 lipopeptides in HIV-negative volunteers. The vaccine (HIV-1 LIPO-5 ANRS vaccine) contains five HIV-1 amino acid sequences coding for Gag, Pol and Nef proteins.
This data set contains the expression measure of a subset of 2500 genes from purified in vitro stimulated Peripheral Blood Mononuclear Cells from 42 repeated samples (12 unique vacicnated participants) 14 weeks after vaccination, , 6 hours after in vitro stimulation by either (1) all the peptides included in the vaccine (LIPO-5), or (2) the Gag peptides included in the vaccine (GAG+) or (3) the Gag peptides not included in the vaccine (GAG-) or (4) without any stimulation (NS).

datasets

The package provide statistical integrative techniques and
        variants to analyse highly dimensional data sets: regularized
        CCA and sparse PLS to unravel relationships between two
        heterogeneous data sets of size (nxp) and (nxq) where the p and
        q variables are measured on the same samples or individuals n.
        These data may come from high throughput technologies, such as
        omics data (e.g. transcriptomics, metabolomics or proteomics
        data) that require an integrative or joint analysis. However,
        mixOmics can also be applied to any other large data sets where
        p + q >> n. rCCA is a regularized version of CCA to deal with
        the large number of variables. sPLS allows variable selection
        in a one step procedure and two frameworks are proposed:
        regression and canonical analysis. Numerous graphical outputs
        are provided to help interpreting the results. Recent
        methodological developments include: sparse PLS-Discriminant
        Analysis, Independent Principal Component Analysis and
        multilevel analysis using variance decomposition of the data.

vac18: Vaccine study Data

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