#' @import captioner
#'
figs <- captioner::captioner(prefix="Figure S", auto_space=FALSE)
tbls <- captioner::captioner(prefix="Table S", auto_space=FALSE)
figs(name="S1", "The relationship between sample injection order and total ion
intensity per sample of raw spectral data.")
figs(name="S2", "The relationship between sample injection order and total
ion intensity per sample after deconvolution with XCMS software.")
figs(name="S3", "The relationship between raw intensity signal and intensity
signal extracted by XCMS. High correlation between data points in this
figure indicates acceptable performance of peak picking step.")
figs(name="S4", "The relationship of the number of extracted features by XCMS
versus the total extracted signal intensity.")
figs(name="S5", "Scores plot of the first two principal components of PCA
model for all QC and biological samples. Signal intensities scaled to unit
variance (UV) and k-nearest (knn) method used (k=5) to fill in missing
values.")
figs(name="S6", "Scores plot of the first two principal components of PCA
model for QC samples only. Signal intensities scaled to unit variance (UV)
and k-nearest (knn) method used (k=5) to fill in missing values.")
figs(name="S7", " Scores plot of the first two principal components of PCA
model for QC samples only and the first 5 QCs removed. Signal intensities
scaled to unit variance (UV) and k-nearest (knn) method used (k=5) to fill
in missing values.")
figs(name="S8", "Scores plot of the first two principal components of PCA
model for all biological samples and QC samples and the first 5 QCs
removed. Signal intensities scaled to unit variance (UV) and k-nearest (knn)
method used (k=5) to fill in missing values.")
figs(name="S9", "Examples of extracted ion chromatogram (EICs). The figure is
divided in three panels. Top pane includes chromatograms of the peak group
with highest intensity for peak sets detected in at least 80% of samples.
Bottom panes are showing peak sets from the closest m/z values of the main
one to visualise potential drift in m/z.")
figs(name="S10", "Number of detection rate (percentage) across samples and
extracted features.")
figs(name="S11", "Violin plot of Relative Standard Deviation (RSD%) per sample
group. Equilibration QC samples 1-5 were excluded from RSD% calculations.
Horisontal lines indicate 25%, 50% and 75% quantiles.")
figs(name="S12", "RSD% values of metabolic feature across QC samples in
comparison to RSD% values of metabolic feature across biological samples.
The plot visualises the difference between technical and biological
variability of the spectral data.")
figs(name="S13", "Box plot of the features of all QC samples (per analytical
batch if more than one is present) scaled to unit variance. Thick line in
each bar represents median value of the scaled features and is expected to
be close to 0 and for QC samples should stay within a range of +-2
(2 standard deviations).")
figs(name="S14", "Box plot of the features of all QC and biological samples
scaled to unit variance. This figure is indicative for a stability of the
whole analytical batch.")
figs(name="S15", "Scores plot of the first two principal components of PCA
model for biological and QC (first 5 QCs removed) samples after peak matrix
filtering. Data are normalised using PQN normalisation and k-nearest (knn)
method used (k=5) to fill in missing values. Glog transformation used to
scale signal intensities.")
figs(name="S16", "Scores plot of the first two principal components of PCA
model for QC (first 5 QCs removed) samples after peak matrix filtering.
K-nearest (knn) method used (k=5) to fill in missing values and signal
intensities are scaled to unit variance.")
figs(name="S17", "Scores plot of the first two principal components of PCA
model for biological and QC (first 5 QCs removed) samples after peak matrix
filtering, and signal/batch correction. Data are normalised using PQN
normalisation and k-nearest (knn) method used (k=5) to fill in missing
values. Glog transformation used to scale signal intensities.")
figs(name="S18", "Scores plot of the first two principal components of PCA
model for QC (first 5 QCs removed) samples after peak matrix filtering,
and signal/batch correction. K-nearest (knn) method used (k=5) to fill in
missing values and signal intensities are scaled to unit variance.")
figs(name="S19", "Violin plot of Relative Standard Deviation (RSD%) per sample
group after peak matrix filtering. Equilibration QC samples were excluded
from RSD% calculations. Horizontal lines indicate 25%, 50% and 75%
quantiles.")
figs(name="S19a", "Violin plot of Relative Standard Deviation (RSD%) of QC
samples per batch after peak matrix filtering. Equilibration QC samples were
excluded from RSD% calculations. Horizontal lines indicate 25%, 50% and 75%
quantiles.")
figs(name="S20", "Violin plot of Relative Standard Deviation (RSD%) per sample
group after peak matrix filtering and signal/batch correction. Equilibration
QC samples 1-5 were excluded from RSD% calculations. Horizontal lines
indicate 25%, 50% and 75% quantiles.")
figs(name="RT_MAD", "Violin plots of MAD (meadian absolute deviation) of
median RT per chromatographic feature.")
figs(name="peak_width", "Violin plot of meadian peak width per chromatographic
feature in s.")
figs(name="mz_precision", "Violin plot of meadian of mass precision per
chromatographic feature in ppm. Values below -5 and above 5 ppm are excluded
from a plot.")
figs(name="size_vs_peaknr", "The relationship of the number of extracted
features by XCMS versus the mzML file size. This figure should be useful to
identify possible technical issues during sample collection.")
tbls(name="S1", "A summary of the Pearson's product-moment correlation
coefficients for the data shown in Figures S2-S4 (blank samples are excluded
from calculations). High correlation should not beens observed between
measurement order and total signal intensity.")
tbls(name="S2", "A summary of RSD% for data shown in Figure S11.")
tbls(name="S3", "A summary of RSD% values for data shown in Figure S17.")
tbls(name="S4", "A summary of RSD% values for data shown in Figure S18.")
tbls(name="S5", "Summary of the sample metadata of the analytical batch;
Sample names, group labels, sample measurement time and number of features
detected by XCMS for each sample.")
tbls(name="RT_RSD", "A summary of RSD% of median RT per chromatographic
feature.")
tbls(name="RT_MAD", "A summary of MAD (meadian absolute deviation) of median
RT per chromatographic feature.")
tbls(name="peak_width", "A summary of meadian peak width per chromatographic
feature in s.")
tbls(name="mz_precision", "A summary of meadian of mass precision per
chromatographic feature in ppm.")
tbls(name="filtering", "Several filters on extracted peak matrix are applied
to asses data quality. 1) Blank filter; 2) Missing value (MV) filter across
samples; 3) MV filter across features for QC samples; 4) MV filter across
feature and across all samples. Parameters and thresholds used are listed in
table below. Column 'Number of features' shows how many features are
retained after each filtering step, column 'Number of samples' how many
samples are retained and column 'Applied' if the filter was applied.")
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