在heatplot ggplot瓷砖之间的空白区域 [英] White space between tiles in heatplot ggplot
本文介绍了在heatplot ggplot瓷砖之间的空白区域的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
我有使用ggplot2生成的这个热图。
我想要做的是在用大写字母列出的变量和以小写字母列出的变量以便分开这两个类别。我仍然希望瓷砖的宽度相等。
我用来生成图的代码是：
ggplot（mockdata，aes（variable，Measurement））+
geom_tile（aes（fill = mockdata $ plotval），color =dark red）+ scale_fill_gradient2（limits = c（-20,20），high = firebrick3，low =dodgerblue4）+
theme_minimal（）+ theme（axis.text.x = element_text（size = 28，angle = 90），axis.text.y = element_text（size = 28） ）+
labs（title =，x =，y =，fill =）
我的数据如下所示：
>头（mockdata）测量变量Pval effect
>方向plotval类别21 20 A 4.511987e + 04
> -0.004892941 -1 -4.6543678实测22 19 A 3.436853e-08 0.054344854 1 7.4638390实测23 18 A 1.465755e + 00 0.355139910 1 -0.1660613实测24
> 17 A 7.006222e-04 -0.079390247 -1 3.1545161测得25
> 16 A 4.705051e-04 -0.017708611 -1 3.3274357测得26
> 15 A 2.301113e + 03 -0.022934623 -1 -3.3619379测量的
PS。虽然这完全是另一个问题，但我也想编辑图例，使其范围从0到20不等，并且分成两个垂直方向，一边显示红色渐变和蓝色渐变。
非常感谢您的帮助。
$ b 编辑：根据请求输出输出
dput（mockdata）$ （测量=结构（c（20L，19L，18L，17L，
16L，15L，14L，13L，12L，11L，10L，9L，8L，7L，6L，5L，4L） ，3L，
2L，1L，20L，19L，18L，17L，16L，15L，14L，13L，12L，11L，10L，
9L，8L，7L，6L，5L，4L，3L ，2L，1L，20L，19L，18L，17L，16L，
15L，14L，13L，12L，11L，10L，9L，8L，7L，6L，5L，4L，3L，2L， b 1L，20L，19L，18L，17L，16L，15L，14L，13L，12L，11L，10L，9L，
8L，7L，6L，5L，4L，3L，2L，1L，20L，19L 18L，17L，16L，15L，
14L，13L，12L，11L，10L，9L，8L，7L，6L，5L，4L，3L，2L，1L，
20L，19L，18L ，17L，16L，15L，14L，13L，12L，11L，10L，9L，8L，
7L，6L，5L，4L，3L，2L，1L，20L，19L，18L，17L，16L，15L ，14L，
13L，12L，11L，10L，9L，8L，7L，6L，5L，4L，3L，2L，1L，20L，
19L，18L，17L，16L，15L，14L ，13L，12L，11L，10L，9L，8L，7L，
6L，5L，4L，3L，2L，1L，20L，19L，18L，17L，16L，15L，14L，13L， b 12L，11L，10 L，9L，8L，7L，6L，5L，4L，3L，2L，1L），标签= c（1，
2，3，4，5 6，7，8，9，10，11，12，13，
，14，15，16，17 ，18，19，20，21，22，23，24，
25，26，27，28 29，30，31，32，33，34，35，
，36，37，38，39，40 （1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L，1L， 1L，1L，
1L，1L，1L，2L，2L，2L，2L，2L，2L，2L，2L，2L，2L，2L，2L，2L，
2L，2L， 2L，2L，2L，2L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L，3L， 3L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L，4L， $ 5L，5L，5L，5L，5L，5L，5L，5L，5L，5L，5L，5L，5L，5L，5L，5L，
5L，5L，5L，6L，6L， 6L，6L，6L，6L，6L，6L，6L，6L，6L，6L，
6L，6L，6L，6L，6L，6L，6L，7L，7L，7L，7L，7L，7L， 7L，7L，7L，
7L，7L，7L，7L，7L，7L，7L，7L，7L，7L，7L，7L，8L，8L，8L，8L，8L， 8L， 8L，8L，8L，8L，8L，8L，8L，8L，8L，8L，8L，8L，9L，9B， 9L，9L，9L，9L，9L，9L，
9L，9L，9L）。标签= c（A，B，C，a，b，c ，d，e，
f），class =factor），Pval = c（45119.8699435164,3.43685309800565e-08，
1.46575455003134,0.000700622204341352,0.000470505115493356，
2301.1126328306，4.54797845872279e-09，2.82713540460051，7.27455376527109，
0.000708124149686762，2.42898037459018，129.848099736546，0.199979430821282，
3.14108095159057，1.27073870790998，107.060952494286，5853.27997745224，
0.0742582348172777，0.179994821770633，896.77644657471，23.2401456908433，
1.04257158400361e-05，0.818717078694074，0.000516863241751892，
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6.44618209352764，1047821.38958175，704454.528072486，1184.40676026588，
9.27799786552194,244051 0.746539605，375048.779613815，9134.54101073437，
3.11905288061898e-08，2.00150860109179e-05，7.0931638758186e-05，
2.43242155771004，1602.73424833609，6.02923321145412，3.21794638623681，
39545.9388361236，475.781444413131，455.686197237482，4.67829129583755，
909.58298359142，2.02989433872695e-12，0.000760836775114312，
0.000112864936813818，0.00189775331609849，0.0815921243521161，
31.0427655620544，64.1785732227039，0.00217933417639979，0.32663419999951，
2.54891270451988e-07，8.48612397192046e-08，0.370184441863085 ，
0.0773444299723239，1580.93083600716，25.4862794021994，30.2642707469218，
224.214639928028，14.7414363362227，18.0511919451453，21037.258121794，
21659.968905852，17721957.0100965，41240.6588986806，111.028537460958，
21.7975275086975，276.44178388089，171.535750708364，6.54776065462672，
151.823636593007，77.7232628471612，378439.528032194,8.9932059191815e-10，
7.49689679316569e-08，0.0155924907385915， 1032.31959077079，69.010587250471，
3136.70323628637，249713.871697334，19360.5708508639，40.7258690163879，
0.0162957051889601，1.02869393872855e-06，0.025268197376688，
0.528481476061038，0.982629085096339，9.45655313066933e-07，4.57557582847333e-05，
7.45403294058092e-05,4.53918933391971 3.30530837062386e-13
0.630234341296706 9.82668496529192e-08 8.53389810467837e-08
9.02891336492619 5451.02888390797 3.90681590706977 329.545150676593
103.491400305633 697.038514954349 222.73520900148 ，10798.3042798457，
21.0644243649671，43176.6607108169，4235.53654423626，3100.32036580987，
0.474678829666085，6.40621457829452，122.637549472055，43.0666245228938，
12.0250322640284，61440.278302552，6788575.58160297，51.9360282881212，
769.96899739087，7.59005145509618e-09， 2.43526615569376e-14，
7.39725489778816e-07，0.000232784090617743，2.71678851958226e-05，
7.42801688358956e-06，0.000419885957835749，13.5780839769886 ，
3.32442709394189，0.335486082296544，3.94230896978352，1.46425278783307，
8.69549979650646，596385.229504125，0.000115943040096764，3628.23773839244，
49454.7726336256，0.000504974333790079，0.00995546823577904，
0.233933121119438，0.363364289185792，9193.93256769758，354.456908896329，
5661.68504768727，0.121589829029783,940.93343158607,2.03003608173289e-18，
0.0149649659043151,4.52682955802236e-10，7.15334079727642e-09，
0.000310851843411754,1.93389728243117e-06,2.03883508956486e-07，
0.00284517176384008， 540.061334125012，21318282.1015595，14894.4660549342，
0.000266471541489485，0.246672590081899，0.102617416010794，30584.5294303485，
1.6644151457974，0.274144521451231，5.61250055231602，801087.819256331，
649321.765215902，1.09526223361541，3.19905699111348e-05，0.383890848761449，
895.643897487244 ，2.68459116542856,26.4804232740359,5.94041739131986，
1.53119475830081e-07），效应= c（-0.0048929408170183,0 0.0543448544236634，
0.355139910284011，-0.0793902472151885，-0.0177086113171934，
-0.0229346227548993，0.0859476877708055，0.0616530901499479，
0.0255808327961239，0.0587050814255305，0.0141476490245787，0.016845032477233，
0.0534824934671667，0.109055235276048，0.111112652283139，0.0234941463950778，
0.0509358202565552，0.0252735688725701，0.0359067099796669，0.00562271637183446，
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0.0109268890743347，-0.100768815837666，-0.00606344260837149，
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- 0.116360501719279，-0.0685817739681672，0.0190371136722137，
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0.0581172695200586， 0.0352865160196343，-0.0390338901505756，
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-0.09902230127504 21，-0.022532243059551，-0.109508938534005，
-0.0828800247402709，-0.0224991372217077，-0.0864470271893071，
-0.0120276456354962，-0.171616504240665，-0.0405716645109222，
-0.150207882114913,0.019187309212901,0.083618216547288,0.312977089073896，
-0.116708039798045，-0.0727212548658722，-0.0334904589242441，
0.0250211767009604，-0.0262773156800457，-0.00638328497889965，
0.0207436409328599，0.00526977878443117，0.0121248749949723，
0.0372084648778052，0.0119773388777849，0.0299841410899367，0.0179852238184209，
0.00615922907815808， 0.0923011852715508，0.0286655081413075，
0.0615892570124506，-0.040101427234219，0.00471273799312188，
-0.0695325837078327，-0.0194435878635383，-0.0113447270023325，
-0.052896201189637，0.15391622949438，0.0625317280746324，0.305195811975115，
0.0175140430499281，0.0944330305254164，0.125486034995771 ，0.204097960624017，
0.0139041133925463，0.115503245160239，0.0744749299835659，0.03094011 53645095，
0.0774734185854047，0.128577840642144，-0.00523940764293137，
-0.0826725654792668，0.00061718469555555，-0.139447399226457，
-0.015892803158233，-0.0776351210087576，-0.114375795737603，
0.506655172546014，0.0139569906287469，0.032593809131997，0.0838209562382717，
0.026889024005808，0.114847700394033，0.0344957168306127，0.309849172983949，
0.224583305802426，0.0920680732068372，0.20205450223499，0.129261938040113，
0.118741527574873，0.0666598681717314，-0.0259685736746482，-0.00493768230442141，
-0.0513043909367941，-0.0228292902998043，-0.125120892334107 ，
-0.0354061460089046，-0.145910823420589，-0.0505094213129978，
-0.357522550450534，-0.0492725484140125，-0.00672879449498781，
-0.00498836470563034，0.0857101915123005，0.245202106389044，
0.0652610111098569，0.00803793757485241，0.0456354806905821，
0.0567597911088563,0.155069881077418,0.0398552868265476），方向= c（-1，
1,1,1，-1，-1,1,1 ，1,1,1,1,1,1,1,1,1,1,1,1,1，
1,1，-1，-1，-1，-1，-1，-1， -1，-1，-1，-1，-1,1，-1，-1，-1，
1,1,1,1,1,1,1,1,1，-1 ，-1,1,1，-1，-1，-1，-1，-1，
-1，-1，-1，-1，-1,1,1,1，-1 ，-1，-1,1，-1,1,1，-1,1，
-1，-1，-1，-1，-1,1,1，-1,1， - 1，-1,1,1,1,1,1,1，-1，
-1，-1，-1，-1，-1，-1，-1，-1， - 1，-1,1,1,1，-1，-1，-1，
1，-1，-1,1,1,1,1,1,1,1,1,1， 1,1,1,1,1，-1，-1，
-1,1,1,1,1,1,1,1,1,1,1,1,1,1 ，-1，-1,1，-1，-1，
-1，-1,1,1,1,1,1,1,1,1,1,1,1,1 ，1，-1，-1，-1，
-1，-1，-1，-1，-1，-1，-1，-1，-1,1,1,1,1 ，1,1,1,1），
plotval = c（-4.65436783913808,7.4638390305887，-0.166061251006543，
3.15451610300161,3.3743565041216,3.36193787665198,8.34218160099397，
-0.45134660936061，-0.861806358039495,3.14989059429165 ，
-0.385424005854277，-2.11343559832442,0.699014672037075，
-0.497079129132047，-0.104056259146589，-2。 02963110287305，
-3.7673992980343，1.12925537854411，0.744739988834407，-2.95268419318977，
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2.66167617047025,0.485938344726535,6.59364 503804761，7.0712906280104，
0.431581837757606,1.1157095694052，-3.19891287043981，-1.40630643990113，
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2.0019383089733，0.630908284813054， 0.439657756641714，-3.96350131412125，
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2.54589150999432，-2.732443084933，-7.32875220486331，-4.17302493900107，
3.57434916575198，0.607879106033299，0.98877892542788，-4.48550180288597，
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4.49497802290257,0.415792240525927，-2.95213537116121，-0.428878156658466，
-1.42292492276573，-0.773816960869839,6.81496956627369），
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测量，测量，测量，测量，测量测量，测量，测量，测量，
测量，测量，测量，测量，测量，
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测量测量测量测量测量
测量测量，测量，测量，测量，
测量，测量，测量，测量，测量，
测量 ，派生的，派生的，派生的，派生的，
派生的，派生的，派生的，派生的派生，派生，派生，派生，派生，
派生，派生，派生，衍生 ，
派生，派生，派生，派生，派生，派生，
派生，派生，衍生派生，派生，派生，派生，派生，派生，派生，衍生 ，派生，派生 ，衍生，衍生，派生，派生，派生，派生，派生，派生，衍生派生，派生，派生，
派生，派生，派生，派生，派生 ，派生的，派生的，派生的，派生的，
派生的，派生的，派生的，派生的派生，派生，派生，派生，派生，
派生，派生，派生，衍生 ，
派生，派生，派生，派生，派生，派生，
派生，派生，衍生派生，派生，派生，派生，派生，派生，派生，衍生 ，派生的，派生的，派生的，
派生的，派生的，派生的，衍生的，派生的 ，.Names = c（Measurement，variable，Pval，
（21L，
22L，23L，24L，25L，26L，27L，28L，29L，30L，31L，32L ，33L，34L，
35L，36L，37L，38L，39L，40L，61L，62L，63L，64L，65L，66L，67L，
68L，69L，70L，71L，72L，73L ，74L，75L，76L，77L，78L，79L，80L，
101L，102L，103L，104L，105L，106L，107L，108L，109L，110L，111L，$ b $ 112L，113L，114L ，115L，116L，117L，118L，119L，120L，141L，142L，
143L，144L，145L，146L，147L，148L，149L，150L，151L，152L，153L，$ b $ 154L，155L ，156L，157L，158L，159L，160L，181L，182L，183L，184L，
185L，186L，187L，188L，189L，190L，191L，192L，193L，194L，195L，
196L ，197L，198L，199L，200L，221L，222L，223L，224L，225L，226L，
227L，228L，229L，230L，231L，232L，233L，234L，235L，236L，237L， b 238L，239L，240L，261L，262L，263L，264L，265L，266L，267L，268L，
269L，270L，271L，272L，273L，274L，275L，276L，277L，278L，279L， b $ b 280L，301L，302L，303L，304L，305L，306L，307L，308L，309L，310L，
311L，312L，313L，314L，315L，316L，317L，318L，319L，320L，341L，
342L，343L，344L，345L，346L，347L，348L，349L，350L，351L， 352L，
353L，354L，355L，356L，357L，358L，359L，360L），class =data.frame）
解决方案
选项1
使用构面
mockdata $ type = ifelse（mockdata $ variable％in％LETTERS [1：3]，1，2）
ggplot mockdata）+
facet_wrap（〜type，scales ='free_x'）+
geom_tile（aes（variable，Measurement，fill = mockdata $ plotval），color =dark red）+
scale_fill_gradient2（limits = c（-20,20），high =firebrick3，low =dodgerblue4）+
theme_minimal（）+
theme（axis.text.x = element_text（size = 28） ，angle = 90），axis.text.y = element_text（size = 28））+
labs（title =，x =，y =，fill =）
选项3
另一种解决方案是为每个类别创建单独的图并将它们排列在一起。在这里，我使用 cowplot :: plot_grid 将它们放在一起，它允许我们设置相对宽度（我们希望它们的方式）（尽管您可能需要稍微调整rel_widths值以获得它只是正确的）：
library（cowplot）
p1 < - ggplot（mockdata [which（mockdata $ type （aes（variable，Measurement，fill = plotval），color =dark red）+
scale_fill_gradient2（limits = c（-20，20）=1），]）+
geom_tile ，high =firebrick3，low =dodgerblue4）+
theme_minimal（）+
主题（axis.text.x = element_text（size = 28，angle = 90），axis.text.y = element_text（size = 28），
legend.position =none）+
labs（title =，x =，y =，fill =）
p2 < - ggplot（mockdata [which（mockdata $ type ==2），]）+
geom_tile（aes（variable，Measurement，fill = plotval），color =dark red ）+
scale_fill_gradient2（limits = c（-20,20），high =firebrick3，low =dodgerblue4）+
theme_minimal（）+
theme（axis.text。 X = element_te xt（size = 28，angle = 90），axis.text.y = element_blank（））+
labs（title =，x =，y =，fill =）
plot_grid（p1，p2，nrow = 1，rel_widths = c（1,2））
选项4
数据中的一个额外因素级别，位于要分隔的列之间，然后以白色为该列绘制图块。
mockdata = rbind（mockdata，
data.frame（Measurement = 1：20，
variable =，
Pval = NA，
effect = NA，
方向= NA，
plotval = 0，
category =Measured））
mockdata $ variable = factor（mockdata $ variable，levels = c（A， B，C，，a，b，c，d，e，f））
ggplot（mockdata，aes变量，度量））+
geom_tile（fill = NA，color = NA）+
geom_tile（data = mockdata [which（mockdata $ variable ==），]，fill =white， color =white）+
geom_tile（data = mockdata [which（mockdata $ variable！=），]，aes（fill = plotval），color =dark red）+
scale_fill_gradient2 （limits = c（-20,20），high =firebrick3，low =dodgerblue4）+
theme_minimal（）+
theme（axis.text.x = element_text（size = 28，角度= 90），axis.text.y = element_text（size = 28））+
labs（title =，x =，y =，fill =）
I have this heatplot that I've generated using ggplot2.
What I would like to do is to add white space between the variables listed in capital letters and the variables listed in lower case letters so as to separate these two categories. I still want the tiles to be of equal width.
The code I've used to generate the plot is:
ggplot(mockdata, aes(variable, Measurement)) +
geom_tile(aes(fill = mockdata$plotval), colour = "dark red") + scale_fill_gradient2(limits=c(-20, 20),high = "firebrick3", low = "dodgerblue4") +
theme_minimal() + theme(axis.text.x=element_text(size=28, angle=90), axis.text.y=element_text(size=28)) +
labs(title="", x="", y="", fill="")
And my data looks as follows:
> head(mockdata) Measurement variable Pval effect
> direction plotval category 21 20 A 4.511987e+04
> -0.004892941 -1 -4.6543678 Measured 22 19 A 3.436853e-08 0.054344854 1 7.4638390 Measured 23 18 A 1.465755e+00 0.355139910 1 -0.1660613 Measured 24
> 17 A 7.006222e-04 -0.079390247 -1 3.1545161 Measured 25
> 16 A 4.705051e-04 -0.017708611 -1 3.3274357 Measured 26
> 15 A 2.301113e+03 -0.022934623 -1 -3.3619379 Measured
PS. While it is strictly another question, I would also like to edit the legend so that it ranges simply from 0-20 and is split in two vertically, showing on one side the red gradient and the blue gradient on the other.
Thank you very much for your help.
Edit: dput output as requested
dput(mockdata)
structure(list(Measurement = structure(c(20L, 19L, 18L, 17L,
16L, 15L, 14L, 13L, 12L, 11L, 10L, 9L, 8L, 7L, 6L, 5L, 4L, 3L,
2L, 1L, 20L, 19L, 18L, 17L, 16L, 15L, 14L, 13L, 12L, 11L, 10L,
9L, 8L, 7L, 6L, 5L, 4L, 3L, 2L, 1L, 20L, 19L, 18L, 17L, 16L,
15L, 14L, 13L, 12L, 11L, 10L, 9L, 8L, 7L, 6L, 5L, 4L, 3L, 2L,
1L, 20L, 19L, 18L, 17L, 16L, 15L, 14L, 13L, 12L, 11L, 10L, 9L,
8L, 7L, 6L, 5L, 4L, 3L, 2L, 1L, 20L, 19L, 18L, 17L, 16L, 15L,
14L, 13L, 12L, 11L, 10L, 9L, 8L, 7L, 6L, 5L, 4L, 3L, 2L, 1L,
20L, 19L, 18L, 17L, 16L, 15L, 14L, 13L, 12L, 11L, 10L, 9L, 8L,
7L, 6L, 5L, 4L, 3L, 2L, 1L, 20L, 19L, 18L, 17L, 16L, 15L, 14L,
13L, 12L, 11L, 10L, 9L, 8L, 7L, 6L, 5L, 4L, 3L, 2L, 1L, 20L,
19L, 18L, 17L, 16L, 15L, 14L, 13L, 12L, 11L, 10L, 9L, 8L, 7L,
6L, 5L, 4L, 3L, 2L, 1L, 20L, 19L, 18L, 17L, 16L, 15L, 14L, 13L,
12L, 11L, 10L, 9L, 8L, 7L, 6L, 5L, 4L, 3L, 2L, 1L), .Label = c("1",
"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13",
"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24",
"25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35",
"36", "37", "38", "39", "40"), class = "factor"), variable = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L, 8L, 8L, 8L, 8L,
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L), .Label = c("A", "B", "C", "a", "b", "c", "d", "e",
"f"), class = "factor"), Pval = c(45119.8699435164, 3.43685309800565e-08,
1.46575455003134, 0.000700622204341352, 0.000470505115493356,
2301.1126328306, 4.54797845872279e-09, 2.82713540460051, 7.27455376527109,
0.000708124149686762, 2.42898037459018, 129.848099736546, 0.199979430821282,
3.14108095159057, 1.27073870790998, 107.060952494286, 5853.27997745224,
0.0742582348172777, 0.179994821770633, 896.77644657471, 23.2401456908433,
1.04257158400361e-05, 0.818717078694074, 0.000516863241751892,
0.445544049614064, 37.9699212955842, 4.87750761132064, 0.138732186303325,
0.0185924820003653, 30.8203248121754, 2.40190754411345, 61.2579350060232,
6.44618209352764, 1047821.38958175, 704454.528072486, 1184.40676026588,
9.27799786552194, 244051.746539605, 375048.779613815, 9134.54101073437,
3.11905288061898e-08, 2.00150860109179e-05, 7.0931638758186e-05,
2.43242155771004, 1602.73424833609, 6.02923321145412, 3.21794638623681,
39545.9388361236, 475.781444413131, 455.686197237482, 4.67829129583755,
909.58298359142, 2.02989433872695e-12, 0.000760836775114312,
0.000112864936813818, 0.00189775331609849, 0.0815921243521161,
31.0427655620544, 64.1785732227039, 0.00217933417639979, 0.32663419999951,
2.54891270451988e-07, 8.48612397192046e-08, 0.370184441863085,
0.0773444299723239, 1580.93083600716, 25.4862794021994, 30.2642707469218,
224.214639928028, 14.7414363362227, 18.0511919451453, 21037.258121794,
21659.968905852, 17721957.0100965, 41240.6588986806, 111.028537460958,
21.7975275086975, 276.44178388089, 171.535750708364, 6.54776065462672,
151.823636593007, 77.7232628471612, 378439.528032194, 8.9932059191815e-10,
7.49689679316569e-08, 0.0155924907385915, 1032.31959077079, 69.010587250471,
3136.70323628637, 249713.871697334, 19360.5708508639, 40.7258690163879,
0.0162957051889601, 1.02869393872855e-06, 0.025268197376688,
0.528481476061038, 0.982629085096339, 9.45655313066933e-07, 4.57557582847333e-05,
7.45403294058092e-05, 4.53918933391971, 3.30530837062386e-13,
0.630234341296706, 9.82668496529192e-08, 8.53389810467837e-08,
9.02891336492619, 5451.02888390797, 3.90681590706977, 329.545150676593,
103.491400305633, 697.038514954349, 222.73520900148, 10798.3042798457,
21.0644243649671, 43176.6607108169, 4235.53654423626, 3100.32036580987,
0.474678829666085, 6.40621457829452, 122.637549472055, 43.0666245228938,
12.0250322640284, 61440.278302552, 6788575.58160297, 51.9360282881212,
769.96899739087, 7.59005145509618e-09, 2.43526615569376e-14,
7.39725489778816e-07, 0.000232784090617743, 2.71678851958226e-05,
7.42801688358956e-06, 0.000419885957835749, 13.5780839769886,
3.32442709394189, 0.335486082296544, 3.94230896978352, 1.46425278783307,
8.69549979650646, 596385.229504125, 0.000115943040096764, 3628.23773839244,
49454.7726336256, 0.000504974333790079, 0.00995546823577904,
0.233933121119438, 0.363364289185792, 9193.93256769758, 354.456908896329,
5661.68504768727, 0.121589829029783, 940.93343158607, 2.03003608173289e-18,
0.0149649659043151, 4.52682955802236e-10, 7.15334079727642e-09,
0.000310851843411754, 1.93389728243117e-06, 2.03883508956486e-07,
0.00284517176384008, 540.061334125012, 21318282.1015595, 14894.4660549342,
0.000266471541489485, 0.246672590081899, 0.102617416010794, 30584.5294303485,
1.6644151457974, 0.274144521451231, 5.61250055231602, 801087.819256331,
649321.765215902, 1.09526223361541, 3.19905699111348e-05, 0.383890848761449,
895.643897487244, 2.68459116542856, 26.4804232740359, 5.94041739131986,
1.53119475830081e-07), effect = c(-0.0048929408170183, 0.0543448544236634,
0.355139910284011, -0.0793902472151885, -0.0177086113171934,
-0.0229346227548993, 0.0859476877708055, 0.0616530901499479,
0.0255808327961239, 0.0587050814255305, 0.0141476490245787, 0.016845032477233,
0.0534824934671667, 0.109055235276048, 0.111112652283139, 0.0234941463950778,
0.0509358202565552, 0.0252735688725701, 0.0359067099796669, 0.00562271637183446,
0.0507704293161921, 0.17283228087345, 0.16140675832248, -0.0818286747635847,
-0.00755469414427661, -0.0104447567093411, -0.128088271682644,
-0.0534210973538898, -0.373370146687058, -0.0158548424704536,
-0.0748163315974356, -0.0904460324042191, -0.0028512716452736,
0.014271561838011, -0.00190156753813359, -0.0239279177026479,
-0.0094336807819733, 0.0222425549129021, 0.0292506342181443,
0.0325754202368439, 0.0148015986703938, 0.0421882264651577, 0.423260142208342,
0.0203382101649578, 0.00402969463133637, 0.0866038959569813,
-0.0126180724522637, -0.00101624925914612, 0.0424729539424711,
0.0109268890743347, -0.100768815837666, -0.00606344260837149,
-0.0909174554780339, -0.0959700647301915, -0.0768705808220001,
-0.0662807953036616, -0.00706464147110935, -0.0260825101925435,
-0.116360501719279, -0.0685817739681672, 0.0190371136722137,
0.314176452865903, 0.0852019981707266, -0.109955683402951, -0.0429494359040651,
-0.018893257986317, 0.0359280715736875, -0.00777719486360404,
0.0268854711195253, 0.035717165605315, -0.0185632636448169, 0.00219893106540051,
-0.0575168050187894, -0.0268860255228866, -0.0120997481434518,
-0.0174770295188239, -0.0365387268315564, 0.00427667014560775,
0.0290413811465955, -0.0303874959875708, 0.0494496371834744,
-0.0172878730121681, -0.0596619493875312, 0.0674472930186462,
0.0581172695200586, 0.0352865160196343, -0.0390338901505756,
0.0201101954340249, 0.0968644367520139, -0.00587675128187206,
-0.0990223012750421, -0.022532243059551, -0.109508938534005,
-0.0828800247402709, -0.0224991372217077, -0.0864470271893071,
-0.0120276456354962, -0.171616504240665, -0.0405716645109222,
-0.150207882114913, 0.019187309212901, 0.0583618216547288, 0.312977089073896,
-0.116708039798045, -0.0727212548658722, -0.0334904589242441,
0.0250211767009604, -0.0262773156800457, -0.00638328497889965,
0.0207436409328599, 0.00526977878443117, 0.0121248749949723,
0.0372084648778052, 0.0119773388777849, 0.0299841410899367, 0.0179852238184209,
0.00615922907815808, 0.0923011852715508, 0.0286655081413075,
0.0615892570124506, -0.040101427234219, 0.00471273799312188,
-0.0695325837078327, -0.0194435878635383, -0.0113447270023325,
-0.052896201189637, 0.15391622949438, 0.0625317280746324, 0.305195811975115,
0.0175140430499281, 0.0944330305254164, 0.125486034995771, 0.204097960624017,
0.0139041133925463, 0.115503245160239, 0.0744749299835659, 0.0309401153645095,
0.0774734185854047, 0.128577840642144, -0.00523940764293137,
-0.0826725654792668, 0.00061718469555555, -0.139447399226457,
-0.015892803158233, -0.0776351210087576, -0.114375795737603,
0.506655172546014, 0.0139569906287469, 0.032593809131997, 0.0838209562382717,
0.026889024005808, 0.114847700394033, 0.0344957168306127, 0.309849172983949,
0.224583305802426, 0.0920680732068372, 0.20205450223499, 0.129261938040113,
0.118741527574873, 0.0666598681717314, -0.0259685736746482, -0.00493768230442141,
-0.0513043909367941, -0.0228292902998043, -0.125120892334107,
-0.0354061460089046, -0.145910823420589, -0.0505094213129978,
-0.357522550450534, -0.0492725484140125, -0.00672879449498781,
-0.00498836470563034, 0.0857101915123005, 0.245202106389044,
0.0652610111098569, 0.00803793757485241, 0.0456354806905821,
0.0567597911088563, 0.155069881077418, 0.0398552868265476), direction = c(-1,
1, 1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, -1, -1, -1,
1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, 1, 1, -1, -1, -1, -1, -1,
-1, -1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, -1, 1, 1, -1, 1,
-1, -1, -1, -1, -1, 1, 1, -1, 1, -1, -1, 1, 1, 1, -1, 1, 1, -1,
-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, -1, -1, -1,
1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, -1, 1, -1, -1, -1,
-1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, 1, -1, -1,
-1, -1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1,
-1, -1, -1, -1, -1, -1, -1, -1, -1, 1, 1, 1, 1, 1, 1, 1, 1),
plotval = c(-4.65436783913808, 7.4638390305887, -0.166061251006543,
3.15451610300161, 3.32743565041216, -3.36193787665198, 8.34218160099397,
-0.45134660936061, -0.861806358039495, 3.14989059429165,
-0.385424005854277, -2.11343559832442, 0.699014672037075,
-0.497079129132047, -0.104056259146589, -2.02963110287305,
-3.7673992980343, 1.12925537854411, 0.744739988834407, -2.95268419318977,
-1.36623884628847, 4.98189411623867, 0.0868661499973576,
3.28662435286223, 0.351109352101632, -1.57943969693098, -0.688197955780953,
0.857822769551858, 1.73066263028667, -1.48883721139058, -0.380556286225031,
-1.78716235272839, -0.809302569419764, -6.02028725962301,
-5.84785296501876, -3.073500877557, -0.967454268269813, -5.38748192000237,
-5.57408775663275, -3.96068672995749, 7.50597726212444, 4.69864253925926,
4.14916000637992, -0.386038843759309, -3.20486151733282,
-0.780262082752201, -0.507578804102515, -4.59710189032113,
-2.67740750044583, -2.65866587397551, -0.670087259849411,
-2.95884232700787, 11.6925265676543, 3.11870850390026, 3.94744095721937,
2.72176024102353, 1.08835175932808, -1.49196040507446, -1.8073900579076,
2.66167617047025, 0.485938344726535, 6.59364503804761, 7.0712906280104,
0.431581837757606, 1.11157095694052, -3.19891287043981, -1.40630643990113,
-1.48093021354005, -2.35066396611971, -1.16853980119637,
-1.25650588425321, -4.32298913566366, -4.3356578288347, -7.24851167871111,
-4.61532559535481, -2.04543461904724, -1.33840723441989,
-2.4416036868115, -2.23435464751167, -0.816092795927033,
-2.18133938975974, -1.89055102413018, -5.57799649218455,
9.04608546234764, 7.12511846787433, 1.80708450523289, -3.01381416921109,
-1.83891572308132, -3.49647343200987, -5.39744266823951,
-4.28691815843339, -1.6098703601382, 1.7879268409032, 5.98771381910823,
1.59742573937338, 0.276970230656392, 0.00761038521452666,
6.02426713306055, 4.33955424293266, 4.12760869236016, -0.656978297958022,
12.4807880165375, 0.200497935929844, 7.00759296681644, 7.06885254695129,
-0.955635485860221, -3.73647848327309, -0.591822947332438,
-2.51791492529225, -2.01490426327141, -2.84325677575944,
-2.34778887382083, -4.03335556106781, -1.32354959550492,
-4.63524905089898, -3.62690843318892, -3.49140657316158,
0.323600137070818, -0.806601481409993, -2.08862346391581,
-1.63414083395139, -1.08008625029083, -4.78845317422705,
-6.83177865764632, -1.71546873469442, -2.88647323876581,
8.11975527988995, 13.6134535668385, 6.13092941593436, 3.63304670440456,
4.56594416664396, 5.1291271177969, 3.37686864914492, -1.13283849034736,
-0.521716813134629, 0.474325491909851, -0.595750658150867,
-0.165616059566562, -0.939294549263021, -5.77552687887169,
3.93575531635149, -3.55969573624066, -4.6942082095516, 3.29673069510235,
2.0019383089733, 0.630908284813054, 0.439657756641714, -3.96350131412125,
-2.54956344582082, -3.75294570645333, 0.915102752209537,
-2.97355889939168, 17.6924962428955, 1.82492426830489, 9.34420585704084,
8.14549108393769, 3.50744655283763, 5.71356659688074, 6.6906179005526,
2.54589150999432, -2.732443084933, -7.32875220486331, -4.17302493900107,
3.57434916575198, 0.607879106033299, 0.98877892542788, -4.48550180288597,
-0.221261659119412, 0.562020428705443, -0.749156396749516,
-5.90368012822885, -5.81245996063456, -0.039518112762786,
4.49497802290257, 0.415792240525927, -2.95213537116121, -0.428878156658466,
-1.42292492276573, -0.773816960869839, 6.81496956627369),
category = c("Measured", "Measured", "Measured", "Measured",
"Measured", "Measured", "Measured", "Measured", "Measured",
"Measured", "Measured", "Measured", "Measured", "Measured",
"Measured", "Measured", "Measured", "Measured", "Measured",
"Measured", "Measured", "Measured", "Measured", "Measured",
"Measured", "Measured", "Measured", "Measured", "Measured",
"Measured", "Measured", "Measured", "Measured", "Measured",
"Measured", "Measured", "Measured", "Measured", "Measured",
"Measured", "Measured", "Measured", "Measured", "Measured",
"Measured", "Measured", "Measured", "Measured", "Measured",
"Measured", "Measured", "Measured", "Measured", "Measured",
"Measured", "Measured", "Measured", "Measured", "Measured",
"Measured", "Derived", "Derived", "Derived", "Derived", "Derived",
"Derived", "Derived", "Derived", "Derived", "Derived", "Derived",
"Derived", "Derived", "Derived", "Derived", "Derived", "Derived",
"Derived", "Derived", "Derived", "Derived", "Derived", "Derived",
"Derived", "Derived", "Derived", "Derived", "Derived", "Derived",
"Derived", "Derived", "Derived", "Derived", "Derived", "Derived",
"Derived", "Derived", "Derived", "Derived", "Derived", "Derived",
"Derived", "Derived", "Derived", "Derived", "Derived", "Derived",
"Derived", "Derived", "Derived", "Derived", "Derived", "Derived",
"Derived", "Derived", "Derived", "Derived", "Derived", "Derived",
"Derived", "Derived", "Derived", "Derived", "Derived", "Derived",
"Derived", "Derived", "Derived", "Derived", "Derived", "Derived",
"Derived", "Derived", "Derived", "Derived", "Derived", "Derived",
"Derived", "Derived", "Derived", "Derived", "Derived", "Derived",
"Derived", "Derived", "Derived", "Derived", "Derived", "Derived",
"Derived", "Derived", "Derived", "Derived", "Derived", "Derived",
"Derived", "Derived", "Derived", "Derived", "Derived", "Derived",
"Derived", "Derived", "Derived", "Derived", "Derived", "Derived",
"Derived", "Derived", "Derived", "Derived", "Derived", "Derived",
"Derived", "Derived", "Derived", "Derived", "Derived", "Derived",
"Derived")), .Names = c("Measurement", "variable", "Pval",
"effect", "direction", "plotval", "category"), row.names = c(21L,
22L, 23L, 24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L,
35L, 36L, 37L, 38L, 39L, 40L, 61L, 62L, 63L, 64L, 65L, 66L, 67L,
68L, 69L, 70L, 71L, 72L, 73L, 74L, 75L, 76L, 77L, 78L, 79L, 80L,
101L, 102L, 103L, 104L, 105L, 106L, 107L, 108L, 109L, 110L, 111L,
112L, 113L, 114L, 115L, 116L, 117L, 118L, 119L, 120L, 141L, 142L,
143L, 144L, 145L, 146L, 147L, 148L, 149L, 150L, 151L, 152L, 153L,
154L, 155L, 156L, 157L, 158L, 159L, 160L, 181L, 182L, 183L, 184L,
185L, 186L, 187L, 188L, 189L, 190L, 191L, 192L, 193L, 194L, 195L,
196L, 197L, 198L, 199L, 200L, 221L, 222L, 223L, 224L, 225L, 226L,
227L, 228L, 229L, 230L, 231L, 232L, 233L, 234L, 235L, 236L, 237L,
238L, 239L, 240L, 261L, 262L, 263L, 264L, 265L, 266L, 267L, 268L,
269L, 270L, 271L, 272L, 273L, 274L, 275L, 276L, 277L, 278L, 279L,
280L, 301L, 302L, 303L, 304L, 305L, 306L, 307L, 308L, 309L, 310L,
311L, 312L, 313L, 314L, 315L, 316L, 317L, 318L, 319L, 320L, 341L,
342L, 343L, 344L, 345L, 346L, 347L, 348L, 349L, 350L, 351L, 352L,
353L, 354L, 355L, 356L, 357L, 358L, 359L, 360L), class = "data.frame")
解决方案
Option 1
Use facets
mockdata$type = ifelse(mockdata$variable %in% LETTERS[1:3], "1", "2")
ggplot(mockdata) +
facet_wrap(~ type, scales='free_x') +
geom_tile(aes(variable, Measurement, fill = mockdata$plotval), colour = "dark red") +
scale_fill_gradient2(limits=c(-20, 20),high = "firebrick3", low = "dodgerblue4") +
theme_minimal() +
theme(axis.text.x=element_text(size=28, angle=90), axis.text.y=element_text(size=28)) +
labs(title="", x="", y="", fill="")
Although this is not quite perfect, because dropping the unused x-axis categories from each facet requires specifying scales='free_x' - which unfortunately does not keep the boxes the same width in each facet.
Option2
To remedy this we can also set space="free_x" in facet_grid. Which I think gives what you are looking for:
ggplot(mockdata) +
facet_grid(~ type, scales='free_x', space="free_x") +
geom_tile(aes(variable, Measurement, fill = mockdata$plotval), colour = "dark red") +
scale_fill_gradient2(limits=c(-20, 20),high = "firebrick3", low = "dodgerblue4") +
theme_minimal() +
theme(axis.text.x=element_text(size=28, angle=90), axis.text.y=element_text(size=28)) +
labs(title="", x="", y="", fill="")
Option 3
An alternative solution is to create separate plots for each category, and arrange them together. Here I put them together using cowplot::plot_grid, which allows us to set the relative widths how we want them (although you may need to tweak the rel_widths values a bit to get it just right):
library(cowplot)
p1 <- ggplot(mockdata[which(mockdata$type=="1"),]) +
geom_tile(aes(variable, Measurement, fill = plotval), colour = "dark red") +
scale_fill_gradient2(limits=c(-20, 20), high = "firebrick3", low = "dodgerblue4") +
theme_minimal() +
theme(axis.text.x=element_text(size=28, angle=90), axis.text.y=element_text(size=28),
legend.position="none") +
labs(title="", x="", y="", fill="")
p2 <- ggplot(mockdata[which(mockdata$type=="2"),]) +
geom_tile(aes(variable, Measurement, fill = plotval), colour = "dark red") +
scale_fill_gradient2(limits=c(-20, 20),high = "firebrick3", low = "dodgerblue4") +
theme_minimal() +
theme(axis.text.x=element_text(size=28, angle=90), axis.text.y=element_blank()) +
labs(title="", x="", y="", fill="")
plot_grid(p1,p2, nrow = 1, rel_widths = c(1,2))
Option 4
You can create an extra factor level in the data, which lies between the columns you want to separate, and then plot tiles for that column in white.
mockdata = rbind(mockdata,
data.frame(Measurement=1:20,
variable="",
Pval = NA,
effect = NA,
direction = NA,
plotval = 0,
category = "Measured"))
mockdata$variable = factor(mockdata$variable, levels = c("A", "B", "C", "", "a", "b", "c", "d", "e","f"))
ggplot(mockdata, aes(variable, Measurement)) +
geom_tile(fill = NA, colour = NA) +
geom_tile(data = mockdata[which(mockdata$variable==""),], fill = "white", colour = "white") +
geom_tile(data = mockdata[which(mockdata$variable!=""),], aes(fill = plotval), colour = "dark red") +
scale_fill_gradient2(limits=c(-20, 20),high = "firebrick3", low = "dodgerblue4") +
theme_minimal() +
theme(axis.text.x=element_text(size=28, angle=90), axis.text.y=element_text(size=28)) +
labs(title="", x="", y="", fill="")
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