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< h1 > How to conduct principal component analysis (PCA) for AMR< / h1 >
< h4 class = "author" > Matthijs S. Berends< / h4 >
2020-03-14 14:05:43 +01:00
< h4 class = "date" > 14 March 2020< / h4 >
2020-03-07 21:48:21 +01:00
< div class = "hidden name" > < code > PCA.Rmd< / code > < / div >
< / div >
< p > < strong > NOTE: This page will be updated soon, as the pca() function is currently being developed.< / strong > < / p >
< div id = "introduction" class = "section level1" >
< h1 class = "hasAnchor" >
< a href = "#introduction" class = "anchor" > < / a > Introduction< / h1 >
< / div >
< div id = "transforming" class = "section level1" >
< h1 class = "hasAnchor" >
< a href = "#transforming" class = "anchor" > < / a > Transforming< / h1 >
< p > For PCA, we need to transform our AMR data first. This is what the < code > example_isolates< / code > data set in this package looks like:< / p >
< div class = "sourceCode" id = "cb1" > < pre class = "sourceCode r" > < code class = "sourceCode r" > < span id = "cb1-1" > < a href = "#cb1-1" > < / a > < span class = "kw" > < a href = "https://rdrr.io/r/base/library.html" > library< / a > < / span > (AMR)< / span >
< span id = "cb1-2" > < a href = "#cb1-2" > < / a > < span class = "kw" > < a href = "https://rdrr.io/r/base/library.html" > library< / a > < / span > (dplyr)< / span >
< span id = "cb1-3" > < a href = "#cb1-3" > < / a > < span class = "kw" > < a href = "https://dplyr.tidyverse.org/reference/reexports.html" > glimpse< / a > < / span > (example_isolates)< / span >
< span id = "cb1-4" > < a href = "#cb1-4" > < / a > < span class = "co" > # Observations: 2,000< / span > < / span >
< span id = "cb1-5" > < a href = "#cb1-5" > < / a > < span class = "co" > # Variables: 49< / span > < / span >
< span id = "cb1-6" > < a href = "#cb1-6" > < / a > < span class = "co" > # $ date < date> 2002-01-02, 2002-01-03, 2002-01-07, 2002-01-07, 2002…< / span > < / span >
< span id = "cb1-7" > < a href = "#cb1-7" > < / a > < span class = "co" > # $ hospital_id < fct> D, D, B, B, B, B, D, D, B, B, D, D, D, D, D, B, B, B,…< / span > < / span >
< span id = "cb1-8" > < a href = "#cb1-8" > < / a > < span class = "co" > # $ ward_icu < lgl> FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, T…< / span > < / span >
< span id = "cb1-9" > < a href = "#cb1-9" > < / a > < span class = "co" > # $ ward_clinical < lgl> TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, F…< / span > < / span >
< span id = "cb1-10" > < a href = "#cb1-10" > < / a > < span class = "co" > # $ ward_outpatient < lgl> FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALS…< / span > < / span >
< span id = "cb1-11" > < a href = "#cb1-11" > < / a > < span class = "co" > # $ age < dbl> 65, 65, 45, 45, 45, 45, 78, 78, 45, 79, 67, 67, 71, 7…< / span > < / span >
< span id = "cb1-12" > < a href = "#cb1-12" > < / a > < span class = "co" > # $ gender < chr> "F", "F", "F", "F", "F", "F", "M", "M", "F", "F", "M"…< / span > < / span >
< span id = "cb1-13" > < a href = "#cb1-13" > < / a > < span class = "co" > # $ patient_id < chr> "A77334", "A77334", "067927", "067927", "067927", "06…< / span > < / span >
< span id = "cb1-14" > < a href = "#cb1-14" > < / a > < span class = "co" > # $ mo < mo> B_ESCHR_COLI, B_ESCHR_COLI, B_STPHY_EPDR, B_STPHY_EPDR…< / span > < / span >
< span id = "cb1-15" > < a href = "#cb1-15" > < / a > < span class = "co" > # $ PEN < rsi> R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R, R,…< / span > < / span >
< span id = "cb1-16" > < a href = "#cb1-16" > < / a > < span class = "co" > # $ OXA < rsi> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…< / span > < / span >
< span id = "cb1-17" > < a href = "#cb1-17" > < / a > < span class = "co" > # $ FLC < rsi> NA, NA, R, R, R, R, S, S, R, S, S, S, NA, NA, NA, NA,…< / span > < / span >
< span id = "cb1-18" > < a href = "#cb1-18" > < / a > < span class = "co" > # $ AMX < rsi> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…< / span > < / span >
< span id = "cb1-19" > < a href = "#cb1-19" > < / a > < span class = "co" > # $ AMC < rsi> I, I, NA, NA, NA, NA, S, S, NA, NA, S, S, I, I, R, I,…< / span > < / span >
< span id = "cb1-20" > < a href = "#cb1-20" > < / a > < span class = "co" > # $ AMP < rsi> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…< / span > < / span >
< span id = "cb1-21" > < a href = "#cb1-21" > < / a > < span class = "co" > # $ TZP < rsi> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…< / span > < / span >
< span id = "cb1-22" > < a href = "#cb1-22" > < / a > < span class = "co" > # $ CZO < rsi> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…< / span > < / span >
< span id = "cb1-23" > < a href = "#cb1-23" > < / a > < span class = "co" > # $ FEP < rsi> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…< / span > < / span >
< span id = "cb1-24" > < a href = "#cb1-24" > < / a > < span class = "co" > # $ CXM < rsi> I, I, R, R, R, R, S, S, R, S, S, S, S, S, NA, S, S, R…< / span > < / span >
< span id = "cb1-25" > < a href = "#cb1-25" > < / a > < span class = "co" > # $ FOX < rsi> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…< / span > < / span >
< span id = "cb1-26" > < a href = "#cb1-26" > < / a > < span class = "co" > # $ CTX < rsi> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, S, S,…< / span > < / span >
< span id = "cb1-27" > < a href = "#cb1-27" > < / a > < span class = "co" > # $ CAZ < rsi> NA, NA, R, R, R, R, R, R, R, R, R, R, NA, NA, NA, S, …< / span > < / span >
< span id = "cb1-28" > < a href = "#cb1-28" > < / a > < span class = "co" > # $ CRO < rsi> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, S, S,…< / span > < / span >
< span id = "cb1-29" > < a href = "#cb1-29" > < / a > < span class = "co" > # $ GEN < rsi> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…< / span > < / span >
< span id = "cb1-30" > < a href = "#cb1-30" > < / a > < span class = "co" > # $ TOB < rsi> NA, NA, NA, NA, NA, NA, S, S, NA, NA, NA, NA, S, S, N…< / span > < / span >
< span id = "cb1-31" > < a href = "#cb1-31" > < / a > < span class = "co" > # $ AMK < rsi> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…< / span > < / span >
< span id = "cb1-32" > < a href = "#cb1-32" > < / a > < span class = "co" > # $ KAN < rsi> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…< / span > < / span >
< span id = "cb1-33" > < a href = "#cb1-33" > < / a > < span class = "co" > # $ TMP < rsi> R, R, S, S, R, R, R, R, S, S, NA, NA, S, S, S, S, S, …< / span > < / span >
< span id = "cb1-34" > < a href = "#cb1-34" > < / a > < span class = "co" > # $ SXT < rsi> R, R, S, S, NA, NA, NA, NA, S, S, NA, NA, S, S, S, S,…< / span > < / span >
< span id = "cb1-35" > < a href = "#cb1-35" > < / a > < span class = "co" > # $ NIT < rsi> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…< / span > < / span >
< span id = "cb1-36" > < a href = "#cb1-36" > < / a > < span class = "co" > # $ FOS < rsi> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…< / span > < / span >
< span id = "cb1-37" > < a href = "#cb1-37" > < / a > < span class = "co" > # $ LNZ < rsi> R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R…< / span > < / span >
< span id = "cb1-38" > < a href = "#cb1-38" > < / a > < span class = "co" > # $ CIP < rsi> NA, NA, NA, NA, NA, NA, NA, NA, S, S, NA, NA, NA, NA,…< / span > < / span >
< span id = "cb1-39" > < a href = "#cb1-39" > < / a > < span class = "co" > # $ MFX < rsi> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…< / span > < / span >
< span id = "cb1-40" > < a href = "#cb1-40" > < / a > < span class = "co" > # $ VAN < rsi> R, R, S, S, S, S, S, S, S, S, NA, NA, R, R, R, R, R, …< / span > < / span >
< span id = "cb1-41" > < a href = "#cb1-41" > < / a > < span class = "co" > # $ TEC < rsi> R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R…< / span > < / span >
< span id = "cb1-42" > < a href = "#cb1-42" > < / a > < span class = "co" > # $ TCY < rsi> R, R, S, S, S, S, S, S, S, I, S, S, NA, NA, I, R, R, …< / span > < / span >
< span id = "cb1-43" > < a href = "#cb1-43" > < / a > < span class = "co" > # $ TGC < rsi> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…< / span > < / span >
< span id = "cb1-44" > < a href = "#cb1-44" > < / a > < span class = "co" > # $ DOX < rsi> NA, NA, S, S, S, S, S, S, S, NA, S, S, NA, NA, NA, R,…< / span > < / span >
< span id = "cb1-45" > < a href = "#cb1-45" > < / a > < span class = "co" > # $ ERY < rsi> R, R, R, R, R, R, S, S, R, S, S, S, R, R, R, R, R, R,…< / span > < / span >
< span id = "cb1-46" > < a href = "#cb1-46" > < / a > < span class = "co" > # $ CLI < rsi> NA, NA, NA, NA, NA, R, NA, NA, NA, NA, NA, NA, NA, NA…< / span > < / span >
< span id = "cb1-47" > < a href = "#cb1-47" > < / a > < span class = "co" > # $ AZM < rsi> R, R, R, R, R, R, S, S, R, S, S, S, R, R, R, R, R, R,…< / span > < / span >
< span id = "cb1-48" > < a href = "#cb1-48" > < / a > < span class = "co" > # $ IPM < rsi> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, S, S,…< / span > < / span >
< span id = "cb1-49" > < a href = "#cb1-49" > < / a > < span class = "co" > # $ MEM < rsi> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…< / span > < / span >
< span id = "cb1-50" > < a href = "#cb1-50" > < / a > < span class = "co" > # $ MTR < rsi> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…< / span > < / span >
< span id = "cb1-51" > < a href = "#cb1-51" > < / a > < span class = "co" > # $ CHL < rsi> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…< / span > < / span >
< span id = "cb1-52" > < a href = "#cb1-52" > < / a > < span class = "co" > # $ COL < rsi> NA, NA, R, R, R, R, R, R, R, R, R, R, NA, NA, NA, R, …< / span > < / span >
< span id = "cb1-53" > < a href = "#cb1-53" > < / a > < span class = "co" > # $ MUP < rsi> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…< / span > < / span >
< span id = "cb1-54" > < a href = "#cb1-54" > < / a > < span class = "co" > # $ RIF < rsi> R, R, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, R, R, R…< / span > < / span > < / code > < / pre > < / div >
< p > Now to transform this to a data set with only resistance percentages per taxonomic order and genus:< / p >
< div class = "sourceCode" id = "cb2" > < pre class = "sourceCode r" > < code class = "sourceCode r" > < span id = "cb2-1" > < a href = "#cb2-1" > < / a > resistance_data < -< span class = "st" > < / span > example_isolates < span class = "op" > %> %< / span > < span class = "st" > < / span > < / span >
< span id = "cb2-2" > < a href = "#cb2-2" > < / a > < span class = "st" > < / span > < span class = "kw" > < a href = "https://dplyr.tidyverse.org/reference/group_by.html" > group_by< / a > < / span > (< span class = "dt" > order =< / span > < span class = "kw" > < a href = "../reference/mo_property.html" > mo_order< / a > < / span > (mo), < span class = "co" > # group on anything, like order< / span > < / span >
< span id = "cb2-3" > < a href = "#cb2-3" > < / a > < span class = "dt" > genus =< / span > < span class = "kw" > < a href = "../reference/mo_property.html" > mo_genus< / a > < / span > (mo)) < span class = "op" > %> %< / span > < span class = "st" > < / span > < span class = "co" > # and genus as we do here< / span > < / span >
< span id = "cb2-4" > < a href = "#cb2-4" > < / a > < span class = "st" > < / span > < span class = "kw" > < a href = "https://dplyr.tidyverse.org/reference/summarise_all.html" > summarise_if< / a > < / span > (is.rsi, resistance) < span class = "op" > %> %< / span > < span class = "st" > < / span > < span class = "co" > # then get resistance of all drugs< / span > < / span >
< span id = "cb2-5" > < a href = "#cb2-5" > < / a > < span class = "st" > < / span > < span class = "kw" > < a href = "https://dplyr.tidyverse.org/reference/select.html" > select< / a > < / span > (order, genus, AMC, CXM, CTX, < / span >
< span id = "cb2-6" > < a href = "#cb2-6" > < / a > CAZ, GEN, TOB, TMP, SXT) < span class = "co" > # and select only relevant columns< / span > < / span >
< span id = "cb2-7" > < a href = "#cb2-7" > < / a > < / span >
< span id = "cb2-8" > < a href = "#cb2-8" > < / a > < span class = "kw" > < a href = "https://rdrr.io/r/utils/head.html" > head< / a > < / span > (resistance_data)< / span >
< span id = "cb2-9" > < a href = "#cb2-9" > < / a > < span class = "co" > # # A tibble: 6 x 10< / span > < / span >
< span id = "cb2-10" > < a href = "#cb2-10" > < / a > < span class = "co" > # # Groups: order [2]< / span > < / span >
< span id = "cb2-11" > < a href = "#cb2-11" > < / a > < span class = "co" > # order genus AMC CXM CTX CAZ GEN TOB TMP SXT< / span > < / span >
< span id = "cb2-12" > < a href = "#cb2-12" > < / a > < span class = "co" > # < chr> < chr> < dbl> < dbl> < dbl> < dbl> < dbl> < dbl> < dbl> < dbl> < / span > < / span >
< span id = "cb2-13" > < a href = "#cb2-13" > < / a > < span class = "co" > # 1 (unknown orde… Micrococcoides NA NA NA NA NA NA NA NA< / span > < / span >
< span id = "cb2-14" > < a href = "#cb2-14" > < / a > < span class = "co" > # 2 Actinomycetal… Actinomyces NA NA NA NA NA NA NA NA< / span > < / span >
< span id = "cb2-15" > < a href = "#cb2-15" > < / a > < span class = "co" > # 3 Actinomycetal… Corynebacterium NA NA NA NA NA NA NA NA< / span > < / span >
< span id = "cb2-16" > < a href = "#cb2-16" > < / a > < span class = "co" > # 4 Actinomycetal… Dermabacter NA NA NA NA NA NA NA NA< / span > < / span >
< span id = "cb2-17" > < a href = "#cb2-17" > < / a > < span class = "co" > # 5 Actinomycetal… Micrococcus NA NA NA NA NA NA NA NA< / span > < / span >
< span id = "cb2-18" > < a href = "#cb2-18" > < / a > < span class = "co" > # 6 Actinomycetal… Propionibacter… NA NA NA NA NA NA NA NA< / span > < / span > < / code > < / pre > < / div >
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< div id = "perform-principal-component-analysis" class = "section level1" >
< h1 class = "hasAnchor" >
< a href = "#perform-principal-component-analysis" class = "anchor" > < / a > Perform principal component analysis< / h1 >
< p > The new < code > < a href = "../reference/pca.html" > pca()< / a > < / code > function will automatically filter on rows that contain numeric values in all selected variables, so we now only need to do:< / p >
< div class = "sourceCode" id = "cb3" > < pre class = "sourceCode r" > < code class = "sourceCode r" > < span id = "cb3-1" > < a href = "#cb3-1" > < / a > pca_result < -< span class = "st" > < / span > < span class = "kw" > < a href = "../reference/pca.html" > pca< / a > < / span > (resistance_data)< / span >
< span id = "cb3-2" > < a href = "#cb3-2" > < / a > < span class = "co" > # < / span > < span class = "al" > NOTE< / span > < span class = "co" > : Columns selected for PCA: AMC/CXM/CTX/CAZ/GEN/TOB/TMP/SXT.< / span > < / span >
< span id = "cb3-3" > < a href = "#cb3-3" > < / a > < span class = "co" > # Total observations available: 7.< / span > < / span > < / code > < / pre > < / div >
< p > The result can be reviewed with the good old < code > < a href = "https://rdrr.io/r/base/summary.html" > summary()< / a > < / code > function:< / p >
< div class = "sourceCode" id = "cb4" > < pre class = "sourceCode r" > < code class = "sourceCode r" > < span id = "cb4-1" > < a href = "#cb4-1" > < / a > < span class = "kw" > < a href = "https://rdrr.io/r/base/summary.html" > summary< / a > < / span > (pca_result)< / span >
< span id = "cb4-2" > < a href = "#cb4-2" > < / a > < span class = "co" > # Importance of components:< / span > < / span >
< span id = "cb4-3" > < a href = "#cb4-3" > < / a > < span class = "co" > # PC1 PC2 PC3 PC4 PC5 PC6 PC7< / span > < / span >
< span id = "cb4-4" > < a href = "#cb4-4" > < / a > < span class = "co" > # Standard deviation 2.1580 1.6783 0.61282 0.33017 0.20150 0.03190 2.123e-16< / span > < / span >
< span id = "cb4-5" > < a href = "#cb4-5" > < / a > < span class = "co" > # Proportion of Variance 0.5821 0.3521 0.04694 0.01363 0.00508 0.00013 0.000e+00< / span > < / span >
< span id = "cb4-6" > < a href = "#cb4-6" > < / a > < span class = "co" > # Cumulative Proportion 0.5821 0.9342 0.98117 0.99480 0.99987 1.00000 1.000e+00< / span > < / span > < / code > < / pre > < / div >
< p > Good news. The first two components explain a total of 93.4% of the variance (see the PC1 and PC2 values of the < em > Proportion of Variance< / em > . We can create a so-called biplot with the base R < code > < a href = "https://rdrr.io/r/stats/biplot.html" > biplot()< / a > < / code > function, to see which antimicrobial resistance per drug explain the difference per microorganism.< / p >
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< div id = "plotting-the-results" class = "section level1" >
< h1 class = "hasAnchor" >
< a href = "#plotting-the-results" class = "anchor" > < / a > Plotting the results< / h1 >
< div class = "sourceCode" id = "cb5" > < pre class = "sourceCode r" > < code class = "sourceCode r" > < span id = "cb5-1" > < a href = "#cb5-1" > < / a > < span class = "kw" > < a href = "https://rdrr.io/r/stats/biplot.html" > biplot< / a > < / span > (pca_result)< / span > < / code > < / pre > < / div >
< p > < img src = "PCA_files/figure-html/unnamed-chunk-5-1.png" width = "750" > < / p >
< p > But we can’ < code > < a href = "../reference/ggplot_pca.html" > ggplot_pca()< / a > < / code > function, that automatically adds the right labels and even groups:< / p >
< div class = "sourceCode" id = "cb6" > < pre class = "sourceCode r" > < code class = "sourceCode r" > < span id = "cb6-1" > < a href = "#cb6-1" > < / a > < span class = "kw" > < a href = "../reference/ggplot_pca.html" > ggplot_pca< / a > < / span > (pca_result)< / span > < / code > < / pre > < / div >
< p > < img src = "PCA_files/figure-html/unnamed-chunk-6-1.png" width = "750" > < / p >
< p > You can also print an ellipse per group, and edit the appearance:< / p >
< div class = "sourceCode" id = "cb7" > < pre class = "sourceCode r" > < code class = "sourceCode r" > < span id = "cb7-1" > < a href = "#cb7-1" > < / a > < span class = "kw" > < a href = "../reference/ggplot_pca.html" > ggplot_pca< / a > < / span > (pca_result, < span class = "dt" > ellipse =< / span > < span class = "ot" > TRUE< / span > ) < span class = "op" > +< / span > < / span >
< span id = "cb7-2" > < a href = "#cb7-2" > < / a > < span class = "st" > < / span > ggplot2< span class = "op" > ::< / span > < span class = "kw" > < a href = "https://ggplot2.tidyverse.org/reference/labs.html" > labs< / a > < / span > (< span class = "dt" > title =< / span > < span class = "st" > "An AMR/PCA biplot!"< / span > )< / span > < / code > < / pre > < / div >
< p > < img src = "PCA_files/figure-html/unnamed-chunk-7-1.png" width = "750" > < / p >
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< a href = "#tocnav" class = "anchor" > < / a > Contents< / h2 >
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< li > < a href = "#introduction" > Introduction< / a > < / li >
< li > < a href = "#transforming" > Transforming< / a > < / li >
< li > < a href = "#perform-principal-component-analysis" > Perform principal component analysis< / a > < / li >
< li > < a href = "#plotting-the-results" > Plotting the results< / a > < / li >
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< p > Developed by < a href = "https://www.rug.nl/staff/m.s.berends/" > Matthijs S. Berends< / a > , < a href = "https://www.rug.nl/staff/c.f.luz/" > Christian F. Luz< / a > , < a href = "https://www.rug.nl/staff/a.w.friedrich/" > Alexander W. Friedrich< / a > , < a href = "https://www.rug.nl/staff/b.sinha/" > Bhanu N. M. Sinha< / a > , < a href = "https://www.rug.nl/staff/c.j.albers/" > Casper J. Albers< / a > , < a href = "https://www.rug.nl/staff/c.glasner/" > Corinna Glasner< / a > .< / p >
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