Description Usage Format Details Value Source References
The 16S data from the Human Microbiome Project includes only the most diverse bodysites: Antecubital fossa (skin), Stool and Subgingival plaque (oral) and can be analysed using a multilevel approach to account for repeated measurements using our module mixMC. The data include 162 samples (54 unique healthy individuals) measured on 1,674 OTUs.
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A list containing two data sets, data.TSS
and data.raw
and some meta data information:
data frame with 162 rows (samples) and 1674 columns (OTUs). The prefiltered normalised data using Total Sum Scaling normalisation.
data frame with 162 rows (samples) and 1674 columns (OTUs). The prefiltered raw count OTU data which include a 1 offset (i.e. no 0 values).
data frame with 1674 rows (OTUs) and 6 columns indicating the taxonomy of each OTU.
data frame with 162 rows indicating sample meta data.
factor of length 162 indicating the bodysite with levels "Antecubital_fossa", "Stool" and "Subgingival_plaque".
vector of length 162 indicating the unique individual ID, useful for a multilevel approach to taken into account the repeated measured on each individual.
The data were downloaded from the Human Microbiome Project (HMP,
http://hmpdacc.org/HMQCP/all/ for the V1-3 variable region). The original
data contained 43,146 OTU counts for 2,911 samples measured from 18
different body sites. We focused on the first visit of each healthy
individual and focused on the three most diverse habitats. The prefiltered
dataset included 1,674 OTU counts. We strongly recommend to use log ratio
transformations on the data.TSS
normalised data, as implemented in
the PLS and PCA methods, see details on www.mixOmics.org/mixMC.
The data.raw
include a 1 offset in order to be log ratios transformed
after TSS normalisation. Consequently, the data.TSS
are TSS
normalisation of data.raw
. The CSS normalisation was performed on the
orignal data (including zero values)
none
The raw data were downloaded from http://hmpdacc.org/HMQCP/all/. Filtering and normalisation described in our website www.mixOmics.org/mixMC
LĂȘ Cao K.-A., Costello ME, Lakis VA, Bartolo, F,Chua XY, Brazeilles R, Rondeau P. MixMC: Multivariate insights into Microbial Communities. PLoS ONE, 11(8): e0160169 (2016).
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