# Plot individual patient
data("PatProAlphaDiv",package="patPRO")
data("PatProMap",package="patPRO")
data("PatProOTU",package="patPRO")
data("PatProBacLoad",package="patPRO")
# Alpha Diversity
mergedMapAlpha <- mergeMapMetaData(map.file=PatProMap,
merging.file=PatProAlphaDiv,
map.sub.id="SubjectID",
map.tmpt="Time_point",
map.smpl.id="SampleID",
sample.id.col="SampleID")
testNormAlphaDiv <- normalizeAlphaDiv(mergedMapAlpha, c("chao1","shannon"), 1)
alphaDivPlot <- plotNormalizedAlphaDiv(testNormAlphaDiv,
c("chao1","shannon"),
plot.title="Subject One Diversity",
color.brewer.set="Set2",
legend.text.size = 12)
# Absolute Abundance Estimation
transTestRelAbund <- transposeRelAbund(PatProOTU)
mergedMapTransRA <- mergeMapMetaData(map.file=PatProMap,
merging.file=transTestRelAbund,
map.sub.id="SubjectID",
map.tmpt="Time_point",
map.smpl.id="SampleID",
sample.id.col="SampleID")
top5RelAbund <- topRelAbundDataFrame(x=mergedMapTransRA, top.taxa.num=5)
mergedMapBacLoad <- mergeMapMetaData(map.file=PatProMap,
merging.file=PatProBacLoad,
map.sub.id="SubjectID",
map.tmpt="Time_point",
map.smpl.id="SampleID",
sample.id.col="SampleID")
absAbundOutDf <- topAbsAbundDataFrame(top5RelAbund, mergedMapBacLoad, bac.load.id="Num_Bacteria")
normTopTaxa <- topAbsAbundPlot(absAbundOutDf,
1,
bac.load.col="Num_Bacteria",
plot.title="Subject One Normalized Taxonomy",
color.brewer.set="Set2",
mark.events=TRUE,
mark.times=c(2,6),
mark.text="Surgery",
legend.text.size = 8)
patproPlotTwo(alphaDivPlot, normTopTaxa, "Subject One Profile")
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