绘制有关如何展示数据中非常小的变化/差异的想法

Question

我还有更多技术问题。我面临的任务是必须表示使用两种不同方法获得的相同样本的两组观察值之间非常小的差异。

我想知道我应该使用什么情节。我尝试了各种风格/风格的条形图、蜘蛛图等，但不幸的是，差异很小，即使是

log

规模也无济于事......

我将在下面发布

dput

的数据，这些是 279 个样本，每个样本都有一对观察结果；数量也可能是选择正确的数据表示方式的一个因素，以便传达有意义的信息。

structure(list(sample = c("abh100", "abh107", "ALB212", "Ale14", 
"Ale20", "Ale22", "Ale32", "altai363p", "armenia293", "Armenian222", 
"Ayodo_430C", "Ayodo_502C", "Ayodo_81S", "B11", "B17", "Bishkek28439", 
"Bishkek28440", "Bu16", "Bu5", "BulgarianB4", "BulgarianC1", 
"ch113", "CHI-007", "CHI-034", "DNK05", "DNK07", "DNK11", "Dus16", 
"Dus22", "Esk29", "Est375", "Est400", "HG00126", "HG00128", "HG00174", 
"HG00190", "HG00360", "HG01503", "HG01504", "HG01600", "HG01846", 
"HG02464", "HG02494", "HG02574", "HG02724", "HG02783", "HG02790", 
"HG02943", "HG03006", "HG03007", "HG03078", "HG03085", "HG03100", 
"HGDP00019", "HGDP00027", "HGDP00058", "HGDP00090", "HGDP00124", 
"HGDP00125", "HGDP00157", "HGDP00160", "HGDP00195", "HGDP00208", 
"HGDP00216", "HGDP00232", "HGDP00286", "HGDP00328", "HGDP00338", 
"HGDP00428", "HGDP00449", "HGDP00457", "HGDP00461", "HGDP00474", 
"HGDP00476", "HGDP00526", "HGDP00530", "HGDP00540", "HGDP00541", 
"HGDP00543", "HGDP00545", "HGDP00547", "HGDP00548", "HGDP00549", 
"HGDP00550", "HGDP00551", "HGDP00552", "HGDP00553", "HGDP00554", 
"HGDP00555", "HGDP00556", "HGDP00569", "HGDP00597", "HGDP00616", 
"HGDP00650", "HGDP00656", "HGDP00660", "HGDP00702", "HGDP00706", 
"HGDP00713", "HGDP00717", "HGDP00722", "HGDP00725", "HGDP00737", 
"HGDP00749", "HGDP00773", "HGDP00775", "HGDP00783", "HGDP00785", 
"HGDP00796", "HGDP00798", "HGDP00846", "HGDP00852", "HGDP00855", 
"HGDP00857", "HGDP00887", "HGDP00903", "HGDP00915", "HGDP00928", 
"HGDP00932", "HGDP00936", "HGDP00951", "HGDP00956", "HGDP00987", 
"HGDP00991", "HGDP01012", "HGDP01015", "HGDP01018", "HGDP01028", 
"HGDP01030", "HGDP01032", "HGDP01034", "HGDP01035", "HGDP01036", 
"HGDP01044", "HGDP01047", "HGDP01078", "HGDP01079", "HGDP01095", 
"HGDP01098", "HGDP01153", "HGDP01163", "HGDP01168", "HGDP01172", 
"HGDP01179", "HGDP01188", "HGDP01191", "HGDP01198", "HGDP01199", 
"HGDP01203", "HGDP01211", "HGDP01215", "HGDP01223", "HGDP01228", 
"HGDP01240", "HGDP01242", "HGDP01246", "HGDP01250", "HGDP01253", 
"HGDP01274", "HGDP01286", "HGDP01297", "HGDP01306", "HGDP01308", 
"HGDP01312", "HGDP01314", "HGDP01315", "HGDP01320", "HGDP01323", 
"HGDP01333", "HGDP01335", "HGDP01338", "HGDP01344", "HGDP01345", 
"HGDP01350", "HGDP01355", "HGDP01364", "HGDP01365", "HGDP01401", 
"HGDP01402", "HGDP01414", "HGDP01417", "I1", "I3", "Igor20", 
"Igor21", "IHW9118", "IHW9193", "iran11", "iran17", "IraqiJew1771", 
"IraqiJew4291", "Jordan214", "Jordan445", "Jordan603", "K1", 
"K4", "Kayseri23827", "Kayseri24424", "KD4", "Kor82", "Kusunda02", 
"Kusunda15", "lez42", "lez49", "M13", "M4", "Mansi41", "Mansi79", 
"mg27", "mg31", "mixa0099", "mixa0105", "mixe0002", "mixe0007", 
"mixe0042", "ML2", "ML3", "NA00726", "NA11200", "NA11201", "NA13604", 
"NA13607", "NA13616", "NA15202", "NA15203", "NA15728", "NA15761", 
"NA15763", "NA17374", "NA17377", "NA17385", "NA17386", "NA18940", 
"NA19023", "NA19044", "NA21490", "NA21581", "ND15865", "ND19394", 
"Nesk_22", "Nesk_25", "Nlk1", "Nlk18", "Nlk3", "NOR111", "NorthOssetia12", 
"NorthOssetia5", "Peru60", "R3", "R6", "SA0342", "SA0722", "SAH31", 
"SAH41", "Sam02", "Sir19", "Sir26", "Sir40", "tdj409_shugnan", 
"tdj430_shugnan", "TGBS21", "Tuba19", "Tuba9", "TZ-11", "Ul31", 
"Ul5", "Utsa21", "Utsa22", "Y4", "Y8", "YemeniteJew4695", "YemeniteJew5433", 
"zapo0098", "zapo0099"), mapQ_maf = c(51.3318, 52.0371, 52.0618, 
51.2768, 53.0228, 52.8693, 51.0675, 50.3963, 51.4613, 51.4009, 
51.6526, 52.4884, 52.3255, 50.5967, 50.6899, 51.7723, 51.1071, 
48.2015, 46.3805, 52.3599, 52.1812, 48.5712, 50.4989, 48.805, 
44.7193, 42.7712, 40.866, 40.3355, 49.7041, 51.3019, 51.9338, 
51.3288, 51.2351, 51.686, 51.4889, 51.5026, 48.5749, 52.2824, 
52.6757, 52.7577, 52.2485, 51.331, 47.7513, 52.3725, 51.1054, 
51.9709, 52.0962, 51.9522, 51.8825, 52.0826, 52.1396, 52.7826, 
52.3238, 51.5472, 51.6484, 50.0393, 50.3506, 51.7079, 51.6768, 
52.9288, 51.867, 51.8801, 52.0619, 50.4482, 53.125, 52.3357, 
52.816, 52.5152, 51.7736, 49.8493, 52.1821, 52.4682, 51.0904, 
49.5032, 50.9671, 51.0171, 50.7398, 47.0521, 48.5701, 50.9928, 
50.3521, 51.596, 51.1105, 47.7884, 51.525, 50.8221, 50.9485, 
51.1167, 47.8239, 51.5555, 51.635, 52.2752, 52.2336, 52.767, 
51.7505, 51.3195, 51.2002, 50.818, 53.1088, 52.6154, 51.5, 51.8356, 
49.8197, 50.5, 51.6658, 50.1782, 51.7846, 50.6128, 52.7269, 51.7692, 
52.2724, 51.9711, 51.7343, 51.9081, 48.1557, 52.0555, 52.572, 
52.5065, 52.0605, 50.7464, 51.7327, 47.0268, 48.3672, 51.3776, 
51.2066, 50.9555, 52.1492, 51.8555, 52.0242, 46.6163, 51.6446, 
51.8008, 50.2222, 49.3377, 52.4293, 52.7631, 50.4982, 51.8155, 
46.8689, 50.8998, 45.9822, 49.1481, 50.8468, 46.4479, 48.6341, 
49.304, 49.7352, 51.3607, 51.9807, 52.0291, 52.6724, 51.752, 
49.0993, 52.0465, 51.9151, 51.8038, 47.1955, 52.2359, 52.0719, 
50.4266, 51.7034, 47.9903, 50.536, 51.5959, 51.6944, 51.4107, 
51.2578, 52.3531, 50.1017, 50.4551, 51.8518, 50.43, 51.3676, 
51.6284, 50.2119, 51.8424, 52.5848, 51.3947, 52.5787, 52.6858, 
50.7802, 51.1075, 50.2174, 49.9568, 47.7315, 51.7323, 51.575, 
51.9317, 53.3082, 49.544, 47.7445, 54.2588, 50.583, 52.9579, 
50.9192, 50.9247, 51.5299, 51.9528, 50.41, 52.2549, 42.6424, 
47.1109, 52.0163, 52.0505, 49.7774, 50.0732, 51.8771, 51.6594, 
52.0591, 52.3718, 51.7483, 51.8466, 51.5798, 50.0967, 51.7887, 
50.9332, 50.7897, 50.3685, 49.8983, 51.7238, 50.081, 50.3079, 
50.9562, 52.5925, 53.24, 50.3914, 50.4385, 50.8704, 50.9534, 
51.4158, 45.9595, 44.0182, 51.7673, 52.4899, 51.9145, 50.5711, 
51.088, 48.0898, 50.495, 51.3161, 52.0721, 51.7328, 52.013, 52.1414, 
51.8915, 51.7133, 51.0804, 50.6501, 50.7889, 50.7946, 50.2624, 
49.683, 50.6939, 50.501, 50.179, 51.0268, 52.8178, 52.3571, 49.6437, 
50.2697, 49.6214, 51.3621, 52.3774, 51.0716, 52.148, 52.3823, 
51.9636, 52.0685, 50.7393, 51.2419, 51.6267, 50.9586, 51.4505, 
51.7462), mapQ_per = c(51.4002, 52.1072, 52.1402, 51.3469, 53.0962, 
52.9369, 51.1275, 50.475, 51.5259, 51.468, 51.7054, 52.5514, 
52.3876, 50.6625, 50.7622, 51.8278, 51.1685, 48.2555, 46.4379, 
52.4358, 52.2446, 48.6296, 50.5664, 48.8323, 44.7637, 42.8087, 
40.9128, 40.393, 49.765, 51.3683, 51.9999, 51.4048, 51.2982, 
51.7562, 51.5662, 51.572, 48.6385, 52.3564, 52.751, 52.8375, 
52.3152, 51.3879, 47.825, 52.4211, 51.1708, 52.0364, 52.1623, 
52.0091, 51.9487, 52.1493, 52.1908, 52.8463, 52.3931, 51.5322, 
51.7248, 50.1088, 50.416, 51.7663, 51.7454, 52.9902, 51.9309, 
51.9439, 52.1272, 50.5228, 53.1995, 52.4124, 52.8846, 52.5887, 
51.8412, 49.8999, 52.2324, 52.5083, 51.1311, 49.5656, 51.044, 
51.0929, 50.8083, 47.1127, 48.6395, 51.0641, 50.4207, 51.6702, 
51.1757, 47.8547, 51.5993, 50.8942, 51.0165, 51.185, 47.8906, 
51.6221, 51.7011, 52.3458, 52.3028, 52.8412, 51.8208, 51.3205, 
51.2791, 50.8979, 53.1831, 52.6768, 51.5693, 51.9037, 49.8857, 
50.5681, 51.7345, 50.0584, 51.8432, 50.6796, 52.8075, 51.8363, 
52.3431, 52.0428, 51.805, 51.9762, 48.2206, 52.1192, 52.6169, 
52.5496, 52.1116, 50.5871, 51.7976, 47.089, 48.4152, 51.4247, 
51.2697, 50.8119, 52.2265, 51.905, 52.0721, 46.6659, 51.6905, 
51.8588, 50.1415, 49.4006, 52.498, 52.8259, 50.5594, 51.8886, 
46.9353, 50.9722, 46.0356, 49.2167, 50.9176, 46.4329, 48.7023, 
49.3685, 49.7999, 51.4124, 52.0433, 52.1015, 52.746, 51.8288, 
49.0851, 52.1276, 51.9933, 51.8666, 47.2636, 52.2937, 52.1412, 
50.294, 51.7708, 48.0571, 50.4741, 51.6685, 51.7599, 51.48, 51.3255, 
52.4275, 50.1645, 50.5223, 51.9289, 50.4967, 51.4471, 51.6901, 
50.2178, 51.9119, 52.6546, 51.4695, 52.6416, 52.7371, 50.8436, 
51.1703, 50.2816, 50.0161, 47.7964, 51.5594, 51.2898, 51.9958, 
53.3722, 49.6092, 47.8065, 54.3391, 50.6782, 53.0195, 50.9823, 
50.9908, 51.5932, 52.0201, 50.4696, 52.3334, 42.6956, 47.1807, 
52.0893, 52.1287, 49.8437, 50.131, 51.9385, 51.7154, 52.1328, 
52.4355, 51.8202, 51.9091, 51.6535, 50.3008, 51.8669, 51.0015, 
50.8537, 50.4405, 49.9713, 51.7989, 50.1528, 50.3084, 51.0177, 
52.6634, 53.3042, 50.461, 50.5164, 50.9452, 51.015, 51.4863, 
46.0235, 44.0706, 51.825, 52.5523, 51.9755, 50.6349, 51.1504, 
48.1593, 50.5677, 51.3852, 52.1441, 51.7923, 52.0814, 52.2119, 
51.9574, 51.7878, 51.1539, 50.7177, 50.8423, 50.8626, 50.305, 
49.7109, 50.7641, 50.5659, 50.2013, 51.1001, 52.8881, 52.4267, 
49.7125, 50.336, 49.6884, 51.4247, 52.4449, 50.2337, 52.195, 
52.4476, 52.0357, 52.137, 50.7942, 51.294, 51.6883, 51.0232, 
51.5161, 51.812)), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA, 
-274L))

原则上，现阶段差异很小，但下游对后续分析的影响更大；因此，我试图用更图形化的方法/风格来传达信息，而不是求助于一张巨大的桌子。非常感谢任何帮助，提前致谢！

Answer 1

配对差异的排序点图将显示，对于大多数样本，“per”变量大于“maf”变量。

mutate(df, mapQ_dif=mapQ_maf - mapQ_per) |>
  ggplot(aes(y=fct_reorder(sample, mapQ_dif), x=mapQ_dif)) +
  geom_point(size=1) +
  theme(axis.text.y=element_text(size=4)) +
  geom_vline(xintercept=0, lty=2, col="blue") +
  labs(x="mapQ_maf - mapQ_per", y="Sample")

library(forcats)
library(ggplot2)
library(dplyr)

Answer 2

假设您的数据位于

d

，那么...

d %>% 
  mutate(delta = mapQ_maf - mapQ_per, row = row_number()) %>%
  ggplot() + 
    geom_line(aes(x = row, y = delta)) + 
    geom_hline(
      aes(yintercept = c(0.05, -0.1)), 
      colour = "grey", 
      linetype = "dashed", 
      data = tibble()
    )

参考线是任意的。