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factoextra 变量绘图和标记子集

[英]factoextra variable plotting and labeling subset

I've run a PCA using prcomp in R and I am trying to produce a variable plot that has 1) a subset of the variables (arrows) in a different color (black) than the rest of the variables, 2) sort those variables prior to plotting so the black arrows aren't covered up by any of the other arrows, and 3) label the black arrows with their TUXXXX number.我在 R 中使用 prcomp 运行了 PCA,我正在尝试生成一个变量 plot,它具有 1) 变量(箭头)的子集,颜色(黑色)与变量的 rest 不同,2)对这些变量进行排序在绘图之前,黑色箭头不会被任何其他箭头覆盖,以及 3) label 黑色箭头及其 TUXXXX 编号。

Here is a truncated version of my data:这是我的数据的截断版本:

structure(list(sdev = c(21.7106794138444, 15.6885074594869, 11.9124316528111, 
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-0.210616362796393, -0.0812013243962482, -0.185771800435443, 
-0.0438135376399639, 0.218374086144347, 0.121623152294345, -0.170058260806661
), .Dim = c(35L, 21L), .Dimnames = list(c("TU35976", "TU38792", 
"TU35975", "TU4897", "TU9262", "TU18312", "TU38793", "TU30299", 
"TU38794", "TU16422", "TU32068", "TU12311", "TU18325", "TU22117", 
"TU20746", "TU19660", "TU41790", "TU43092", "TU18309", "TU19659", 
"TU16277", "TU34798", "TU10953", "TU18317", "TU18307", "TU9186", 
"TU17864", "TU15658", "TU14030", "TU15669", "TU9890", "TU33617", 
"TU16279", "TU27042", "TU17167"), c("PC1", "PC2", "PC3", "PC4", 
"PC5", "PC6", "PC7", "PC8", "PC9", "PC10", "PC11", "PC12", "PC13", 
"PC14", "PC15", "PC16", "PC17", "PC18", "PC19", "PC20", "PC21"
))), center = c(TU35976 = 6.61238491831215, TU38792 = 10.2487864648085, 
TU35975 = 7.41959195648095, TU4897 = 10.9311685931669, TU9262 = 11.0918083964267, 
TU18312 = 11.7076238975148, TU38793 = 9.74398564779285, TU30299 = 12.892315214803, 
TU38794 = 9.54139631961704, TU16422 = 12.3329627148834, TU32068 = 7.97610519995008, 
TU12311 = 10.3617106799956, TU18325 = 7.59060411317826, TU22117 = 9.03799676912002, 
TU20746 = 9.178102720165, TU19660 = 9.87502757868133, TU41790 = 8.9943466756264, 
TU43092 = 10.9585816938684, TU18309 = 10.6298994150062, TU19659 = 10.3934726050624, 
TU16277 = 8.32556725898017, TU34798 = 7.02103110645297, TU10953 = 7.01860382462013, 
TU18317 = 7.36244270525821, TU18307 = 11.3778296252987, TU9186 = 10.7024172065364, 
TU17864 = 8.2903853475227, TU15658 = 6.58819311715545, TU14030 = 8.134641008701, 
TU15669 = 7.01449935590416, TU9890 = 8.13988320730633, TU33617 = 10.6809972208427, 
TU16279 = 7.9614057227348, TU27042 = 7.34221912393268, TU17167 = 11.2592403834747
), scale = FALSE, x = structure(c(24.4897868475554, 12.4416010164283, 
12.3200413661576, 6.91612686789472, 30.5655787046573, 33.5373707608136, 
6.7521417841798, 31.2938791704631, 29.0635289584208, -23.3354523484558, 
-15.6229701200559, 6.43010789907339, -24.9147092475567, -31.0094950116289, 
-28.4137928961069, -21.5926413362042, -3.97585196983663, -20.8563124842282, 
-0.593920033332157, -3.64572299218967, -19.8492949360489, -9.96693484414473, 
-23.5449684594658, -18.996265716943, -23.7811581634436, 3.93738430048, 
9.37353195322868, -19.423648038774, 7.87596964384287, -3.13661328005585, 
-7.09016527838172, 3.71259770410569, 23.247076153704, -2.03249135782906, 
-3.64325919770972, -6.94450353973124, 7.55306940052889, 31.346240781817, 
-3.48931847017886, 29.4056029647248, 12.4861765573918, -6.8883231131661, 
-6.8786118382072, 15.8325477899497, 15.3870141654559, -11.3237572934353, 
-4.49560209730399, 1.115062768913, -20.2141393532659, 9.76193925462921, 
-1.15731242202584, 6.22677163564855, 14.431909276018, -13.4812455995592, 
-9.58096578254001, -10.0824168036361, -10.1417065317313, 6.11246229818054, 
-4.84525793168699, 14.9352609583166, 16.1272133946181, -17.0836840355263, 
9.35451814718846, -6.63382933222961, 5.79244304277846, 7.73028939318989, 
-6.00113726185851, -8.57575275731579, -6.70414747438031, 11.0021295692077, 
7.62205208005063, -6.03281844054887, -1.59444275830952, -7.70227835025931, 
-6.4184560830441, -12.3696585650364, 1.42826497938592, 8.28315195406988, 
-13.8464231033084, -6.95076374785849, 5.03179685038719, 16.6482451825695, 
25.4557137741208, -6.16437895161065, -0.188023057317339, 3.51919999146276, 
-3.06021456766217, 12.7300628490286, 0.340348842202129, -4.18342952961951, 
9.91999265542052, -6.2673275997563, -6.19445525060979, -4.89432563084305, 
13.3155996092707, -17.5672684031691, -11.0570104414685, -10.1512940397755, 
-2.83422832939901, 11.2933772476208, 18.438427176494, -10.6101681685668, 
2.08048057352476, 5.50745324586983, -0.13719717270706, -8.9884667602456, 
-2.05928444313446, -0.305773393272364, 4.86554463593651, 3.76285186780856, 
6.3828926870771, -9.3655246100571, 7.43651870615979, -1.67082019758757, 
10.9895599029683, -13.9919213196391, -7.47010213808747, -5.18316808251628, 
3.09935494483666, 0.0636557688816208, -1.54858827353552, 5.76445544260896, 
-7.0244817763404, -6.91485718432494, 6.12343812013661, 16.0347161023267, 
-6.04452306419056, 0.503323158087318, 1.11905480618314, -3.32310396567328, 
3.1274151532053, -1.0139189902977, -2.77210893619864, 5.73300675328722, 
-2.20016077060467, 6.88733384115661, 9.29615931028018, 7.89283806484175, 
-0.0231784873612931, -13.6472361241707, 8.57047305874539, 9.82836851225084, 
-12.0042402273719, -9.50514572716062, -7.91330903314343, 8.52172081325052, 
-3.03276814511544, -8.49580406093405, -2.33842120098311, -0.32804627167184, 
-3.21259723306479, 11.1229701308803, 0.598883041283415, 5.30460923308376, 
1.00174438392002, -1.97289932239362, -10.2991918599681, -3.87835358264123, 
-2.25659286308468, -0.166946108131337, -4.78949081440092, 3.19183354598423, 
4.8383258847991, 0.890821633270318, 14.2375666218091, -6.1498396420083, 
0.00274092818159516, 2.69868755607018, -6.72994548395586, -2.87563409646143, 
6.39162216555694, -1.86430696261611, 1.49349337044142, -0.729377873822674, 
3.91976580406387, -4.55169784656593, 4.01470477896383, 9.45815735561592, 
3.87143750044459, 2.8485319829077, -3.54554995799273, 2.1592779575771, 
-10.2265407210419, -2.57734842434015, 3.85728531842232, 3.91861430861892, 
-6.08938026261039, 2.90775931244037, -5.65086822564584, -7.43442226552497, 
-0.28834246695089, 4.46777893840091, 1.61867182502613, -1.24379496084697, 
3.09330484415506, 4.6129428255061, 4.21327794340158, -2.73480960596815, 
-1.34501116390485, -4.95417459779772, -1.50853746838879, 4.27315750243976, 
5.82184171959861, -3.417633941994, 9.09574374372561, -2.51371486672449, 
-5.3839624715871, 4.02549123440248, -4.25205519103745, -6.14575157593085, 
3.39653326861517, 2.02195972923006, 0.737129651195039, -3.82060608464456, 
-5.8916049884138, -1.48103866101421, -4.15462594283813, 2.85762680978641, 
8.01848063520863, -0.33318325779775, -4.11692676832453, -3.14609004733945, 
-3.87716607273847, 2.15863837910027, 5.89633795035078, 6.78408908767204, 
5.31335299395838, 2.26271596099398, -6.04004269690954, 0.66943773718038, 
-7.25501768327073, -1.85352333808763, 0.881321761644734, -3.37300816578494, 
1.72336449307423, -1.12738959732561, -1.00315691989581, 1.22856047955961, 
-5.49078567616185, 7.36566150881169, 1.5098504796481, -4.40047569826546, 
1.27392003732061, -1.32431052177641, -3.49056795319117, -1.81317399652518, 
4.21470358856118, -3.35477920804357, 0.76847614798403, 4.53289945581295, 
1.08860795433414, 2.64380516830634, -3.5282442958868, 0.44695028657078, 
6.40236529107031, 1.40990912221294, -0.646731159533322, -0.886819655598922, 
-0.75355529529178, -3.22681748481868, 1.14443040171423, -1.01721629940821, 
-1.91406441412825, 2.79795257160194, 1.42125707801834, -3.78513731974819, 
5.22015934186783, -3.11038146921718, 4.2502371748613, -2.23573426796635, 
1.2890326250481, -3.2044887828359, -0.0731034485321765, 1.00689042463065, 
3.10770789167095, 0.653717111815948, 2.0046773828616, -5.05502285926648, 
0.670269628945531, -0.0735066911646989, 0.567378074513561, -4.12216401435608, 
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2.19861127383831, -2.2813563892377, 1.48246659900362, 1.20813467297598, 
4.19016124903691, -3.8965814643401, 3.56184752348759, -1.3878373295987, 
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-2.44238882925152, 1.13264815277383, -1.78862294430386, 0.991256365490394, 
-3.88951966260596, 0.202107196565979, 0.551090451321218, 2.66348016156913, 
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1.61258498499148, -2.05589657580369, 0.0265571467877399, 1.25029287962319, 
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2.08546244595102, -0.0517755897340584, -2.39907743930418, -0.211807017194547, 
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-1.46819802906202, 0.849407708022543, 0.917523253251796, -1.60319562494994, 
1.89391093257302, 0.378604048008997, 0.14292959825461, -0.126413703865446, 
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0.302322289091245, 0.458890126236888, -0.788003883776506, -1.8522098865949, 
-0.303600234099745, -0.869244048674518, 2.09285131170145, 1.13594169034256, 
0.00257581110260907, 1.28821287823238, -0.603719944771219, -0.0929817189825319, 
0.646083878133434, -0.997976432253114, -0.0887921104756663, -0.252335674196718, 
0.885171983511843, -0.455664633944459, -0.080944547822266, -1.11153038212543, 
0.684953529364659, 0.00107091275654292, -0.0523472212020604, 
-0.722665903230519, 0.112695429436832, -0.431332703576418, 2.28632079906497, 
0.389976510624337, -0.672770348738164, -0.710872748519771, 1.11097033239239, 
-0.117525841496901, -0.38659967304807, -0.311519238694312, -0.58769206070627, 
0.880912821150173, -0.223180949008615, -0.0563287542495416, 0.677577799103385, 
0.174786309548343, -0.486054451272286, -0.875421020334039, -1.99840144432528e-15, 
-2.19269047363468e-15, -2.80331313717852e-15, 3.39658856596259e-15, 
4.44089209850063e-16, 4.44089209850063e-16, -2.44249065417534e-15, 
1.11022302462516e-15, -6.66133814775094e-16, -4.44089209850063e-15, 
-3.5527136788005e-15, -2.33146835171283e-15, -6.43929354282591e-15, 
2.44249065417534e-15, -1.4432899320127e-15, -2.19269047363468e-15, 
1.0547118733939e-15, -1.11022302462516e-15, -9.99200722162641e-16, 
1.33226762955019e-15, -1.55431223447522e-15), .Dim = c(21L, 21L
), .Dimnames = list(c("EDA_01", "EDA_02", "EDA_03", "EDA_04", 
"EDA_05", "EDA_06", "EDA_07", "EDA_08", "EDA_09", "NDA_01", "NDA_02", 
"NDA_03", "NDA_04", "NDA_05", "NDA_06", "NDA_08", "NDA_09", "NDA_10", 
"NDA_11", "NDA_12", "NDA_13"), c("PC1", "PC2", "PC3", "PC4", 
"PC5", "PC6", "PC7", "PC8", "PC9", "PC10", "PC11", "PC12", "PC13", 
"PC14", "PC15", "PC16", "PC17", "PC18", "PC19", "PC20", "PC21"
)))), class = "prcomp")

Here is the minimal code to reproduce this problem:这是重现此问题的最少代码:

library(factoextra)
library(tidyverse)

# create a named factor for coding the coloration of the variables in the plot
markers <- facto_summarize(pca,
                           element = "var",
                           result = "contrib",
                           axes = c(1, 2)) %>%
  mutate(candidate = ifelse(name == "TU35976" | name == "TU18317" | name == "TU12311" | name == "TU3565" | name == "TU9890" | name == "TU18316", "1", "0")) %>%
  select(name, candidate)

markers_vec <- as.factor(markers$candidate) 
names(markers_vec) <- markers$name

(var_cluster_PC12 <- fviz_pca_var(pca,
                                  col.var = markers_vec,
                                  axes = c(1,2),
                                  select.var = list(contrib = 200),
                                  palette = c(
                                    "grey90",
                                    "black"),
                                  label = "none",
                                  ) +
    theme_bw() 
)

Which produces this plot:产生这个 plot: 在此处输入图像描述

This image doesn't quite do it justice, so here is a plot of the full data set that shows how bad the overlap is:这张图片并不完全公正,所以这是完整数据集的 plot,显示了重叠的严重程度:

萨

Probably the simplest method, given your particular colour scheme, is to make the arrows all black but use the alpha channel to make the gray ones gray.考虑到您的特定配色方案,最简单的方法可能是使箭头全黑,但使用 alpha 通道使灰色箭头变为灰色。 This means the black arrows will still be completely black even if other arrows are drawn over the top:这意味着即使在顶部绘制了其他箭头,黑色箭头仍然是完全黑色的:

fviz_pca_var(pca,
             axes = c(1,2),
             select.var = list(contrib = 200),
             alpha.var = ifelse(markers_vec == 0, 0.2, 1),
             label = "none") + 
  theme_bw()

在此处输入图像描述

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