问题描述
我想使用 R 中的 plot() 函数从数据框 A 绘制一个图。A 中的列称为“SNP_pos”、“X”，然后是 16 列称为“p0.5”、“p1.5” ","p2.5",..."p15.5"。
plot(A$SNP_pos,-log10(A$p1.5),type="p",cex = 0.6,pch = 16,col="blue",lwd=0.1,frame.plot = F,xaxt = 'n',ylim = c(0,8),las = 2,xlim = c(min(A$SNP_pos),max(A$SNP_pos)),cex.lab=1,ann = FALSE,mgp = c(3,0.8,0))
我想使用 points() 函数绘制表示“p0.5”、“p1.5”、“p2.5”、...“p15.5”列中值的点，每列有 1 种颜色从 R 图形。为了从名为“等离子”的调色板中获得 16 种颜色，我使用了 viridis 包。为了给每列分配 1 种颜色，我使用了 foreach 包。
可能有更简单的方法，但这是我制作的脚本：
library(foreach)
library(viridis)
INT = seq(0.5,15.5,1)
colID = viridis_pal(option = "plasma")(16)
foreach(k = INT,j = colID) %do% {
INT2 = A$get(paste0("p",k,sep=""))
points(-log10(A$INT2),col=j,pch=19,cex=0.4)
}
但是，不知何故，我的脚本无法识别列的名称 (get(paste0("p",sep="")))
这是使用 dput(A) 获得的 A 样本：
结构（列表（p0.5 = c（0.242747188094946，0.168997486361476， 0.107928390753494,0.00051908418471065,0.148653246954464,0.433668277360466,0.275291500174496,0.899508301641167,0.457700101660136,0.159278241228698,0.105476048060019,0.0957898181759544,0.0262806475294918,0.20386786083848,0.0135962839615987,0.0562814320632579,0.0761538252424941,0.11445675670503 ),p1.5 = c(0.0456675606337706,0.579032583070177,0.0733987371701725,0.0125483229728762,0.0628715045603653,0.211266478201916,0.110695151122545,0.243109951551235,0.0210778532524462,0.0493031519980267,0.0390144011015269,0.0304772224622842,0.0084556138719978,0.0111889644811375,0.00158950157629228,0.0899572299188477,0.117447319097037,0.0403839701897273),p2.5 = c(0.106205033576986,0.999008499893865,0.0000977605223585761,0.0000222204471434021,0.0608965716779278,0.120029817275325,0.265571691424294,0.553076531536749,0.122071577513883,0.0142361473839313,0.0140659128442708,0.0106173904925838,0.0100709738419846,0.0220269042478114,0.0197389283217971,0.056918781795781,0.0843907457940626,0.0065953679321777),p3.5 = c(0.0949379614316481,0.6576913449417,0.357953467962908,0.673495175075545,0.00356364218471085,0.00579718014023882,0.100106211569328,0.0158453918358466,0.0969391239180496,0.0142849538835522,0.010588950662722,0.00841341473657932,0.0107418165679845,0.00342963776145622,0.00248045395676769,0.0256439166722159,0.0379307961204795,0.00520668432606975),p4.5 = c(0.0000187175832404615,0.0449205528979275,0.454245793136244,0.625484812568163,0.00087144135901471,0.00125393954966476,0.000495356005020231,0.00853418997106188,0.0860658004805283,0.0138964693607855,0.00778626888227587,0.00880374257771237,0.00992849326319861,0.00236193358591027,0.000317125830225305,0.00270570068269156,0.00268651630233588,0.016006809066345),p5.5 = c(0.0297229014556236,0.450573991501786,0.538565537374086,0.199241650260579,0.140114219338775,0.298810808152817,0.457059301374272,0.000465970378076238,0.015596915949386,0.00498096604293199,0.00180173547360725,0.00241248090553604,0.100258152124521,0.0347312413053782,0.0259487420621233,0.029439670274164,0.0509346154635958),p6.5 = c(0.00157124564715232,0.00617602657108606,0.40323546403784,0.975963386485613,0.000498705229682038,0.00197961640689226,0.00607507536590394,0.00475879649921192,0.0432054681761673,0.000208405926305886,0.000124485834074587,0.000104249584130051,0.000154505394307958,0.000466823941774422,0.00014809982985565,0.000957049520089973,0.000907016506181029,0.000638562546332883 ),p7.5 = c(0.00967614058865758,0.00611666067998298,0.344939438378035,0.829946421184631,0.0000872148308332329,0.0010787446205654,0.00099396409402685,0.000185220001498869,0.00445122847464564,0.0000699305779467999,0.0000270797969253489,0.0000395841851201029,0.0000351568889193048,0.000308108117176226,0.0000505880748474765,0.0000182107980767294,0.0000307213569343469,0.0000538257344596745 ),p8.5 = c(0.0298272314697819,0.00439975455976159,0.615119474893023,0.737847234479775,0.00000260534870255568,0.0000806900093438783,0.0000951477742356736,0.000792707417353214,0.00612215906548817,0.00032734137698918,0.000257161919558846,0.000372124861505317,0.000146537968590819,0.000549732712368789,0.000418621454407308,0.000245993613431499,0.000379405893229818,0.0000736041041229257 ),p9.5 = c(0.0211527099658549,0.0000934929361262732,0.82437218981407,0.519167449006819,0.000523156922133462,0.00258360415905021,0.00204220285347531,0.0000154562053722482,0.00566515791218741,0.000103533046675889,0.0000698932530663413,0.00011717001113944,0.0000664828013933368,0.0000997250603534792,0.000357450389587003,0.000716062592119114,0.000846881645964889,0.000451224448732578 ),p10.5 = c(0.029971421047914,0.00268695456539587,0.424557917592327,0.915046515914916,0.000568515266303506,0.00245516212053905,0.00929053858074703,0.00415983684212026,0.0259746272819724,0.00052532073328366,0.000590465479955006,0.00103194578557607,0.00122815984445129,0.000698956470929661,0.00159091618143714,0.000867824024120008,0.00124655848935054,0.000332038074892812 ),p11.5 = c(0.035609130492743,0.237964075968414,0.690124238372624,0.648900366291513,0.00004710004866214,0.000275145894207551,0.00614799286615342,0.000186840750332432,0.000914981442505171,0.165208893610543,0.115721716938258,0.13093915642351,0.118863703039706,0.0159269747563521,0.00308345643003936,0.00862720882125511,0.0117091662666689,0.0108686512973407),p12.5 = c(0.00672976815913322,0.000638938427403905,0.814337286838706,0.623969439817503,0.000807819084297629,0.00232440718185704,0.000740458747187747,0.000728021148772152,0.0000559657131149375,0.00978645701481258,0.0140829048116248,0.0193192878124661,0.0498439328612731,0.00412982514514444,0.00424479231301975,0.00196617578444213,0.00221470494971319,0.00308388908487704),p13.5 = c(0.0063414607849774,0.000455425918835152,0.52835103362498,0.457946740156627,0.0151431361797825,0.0479667906414369,0.00402089598655567,0.00408601310637604,0.00610753504352883,0.00182377496358575,0.00180612043092252,0.00341152291235735,0.00622315616784477,0.00136290325730425,0.00093534946282569,0.00190275139707705,0.00264021255779838,0.00153154541556427 ),p14.5 = c(0.0172886796088735,0.00262673599171581,0.75486705783085,0.861664714579806,0.00442495915096256,0.0145607545288462,0.026313481660887,0.00338158384879001,0.00324014806350329,0.00334338760170889,0.00336113782656065,0.00618978341717156,0.0134855539039173,0.00131871554558236,0.000970572324960001,0.000308088006042178,0.000485416518092221,0.00039877284691957),p15.5 = c(0.0129036907113826,0.000768695252300225,0.857105484361189,0.652985460943366,0.0678412616065989,0.117470700206561,0.251848121581743,0.0266333988671643,0.0597033572250765,0.00673143398709981,0.00578628321608891,0.00862746246608992,0.118781559566082,0.00377416600326799,0.0416466163677339,0.0114618669238643,0.0101411929303934,0.00439323486043991),SNP_pos = 1:18),.Names = c("p0.5",“p1.5”、“p2.5”、“p3.5”、“p4.5”、“p5.5”、“p6.5”、“p7.5”、“p8.5”、 “p9.5”、“p10.5”、“p11.5”、“p12.5”、“p13.5”、“p14.5”、“p15.5”、 "SNP_pos"),row.names = c(NA,-18L),class = c("tbl_df","tbl","data.frame"))
请帮忙
解决方法
这是我将如何使用 tidyr 和 ggplot2 解决它：
library(tidyr)
library(ggplot2)
A %>%
pivot_longer(cols = -SNP_pos) %>%
ggplot(aes(x = SNP_pos)) +
geom_point(aes(y = value,color = name)) +
scale_y_log10()
在基本图形中，这应该有效：
purrr::iwalk(INT,\(INT,i) {
INT2 = A[[paste0("p",INT)]]
points(seq_along(INT2),-log10(INT2),col = colID[i],pch = 19,cex = 0.4)
})