我在R中有这个数据框。它具有谱系数据框的结构，具有id，fid，mid和sex列。
pedigree <- structure(list(id = c(212, 214, 263, 266, 273, 274, 275, 279,
280, 281, 286, 287, 312, 313, 314, 315, 316, 317, 318, 319, 320,
321, 322, 323, 324, 325, 326, 327, 332, 333, 334, 335, 336, 337,
338, 339, 340, 341, 346, 347, 348, 349, 389, 390, 391, 392, 413,
414, 415, 416, 466, 475, 476, 477, 478, 479, 480, 483, 486, 487,
491, 492, 493, 494, 498, 501, 502, 506, 507, 508, 509, 510, 511,
512, 513, 514, 518, 519, 542, 543, 544, 545, 546, 547, 551, 552,
553, 554, 555, 556, 564, 565, 568, 569, 570, 575, 576, 579, 580,
584, 585, 586, 589, 590, 593, 595, 596, 597, 598, 599, 614, 615,
616, 617, 618, 619, 620, 621, 622, 623, 624, 625, 653, 654, 662,
663, 671, 672, 673, 674, 675, 676, 681, 682, 683, 684, 688, 689,
693, 694, 695, 696, 697, 698, 701, 702, 703, 704, 709, 710, 715,
716, 718, 720, 721, 722, 723, 724, 725, 726, 727, 730, 731, 736,
737, 738, 739, 740, 744, 745, 842, 843, 874, 875, 884, 885, 886,
887, 889, 890, 894, 895, 896, 897, 898, 903, 905, 906, 907, 908,
909, 910, 911, 912, 913, 914, 915, 917, 925, 926, 927, 928, 929,
931, 932, 936, 965, 999, 1000, 1006, 1007, 1041, 1043, 1044,
1046, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075, 1099, 1100,
1101, 1321, 1322, 1368, 1551, 1552, 1553, 1554, 1555), fid = c(0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 326, 326, 326, 326, 279, 320, 320, 320, 320, 320, 320,
320, 320, 320, 324, 324, 324, 324, 322, 322, 322, 324, 324, 324,
324, 324, 324, 324, 324, 324, 318, 318, 326, 326, 326, 326, 326,
326, 326, 326, 326, 326, 326, 326, 332, 332, 287, 287, 287, 287,
287, 286, 286, 346, 346, 346, 348, 348, 348, 326, 326, 326, 326,
326, 332, 332, 320, 320, 320, 320, 320, 287, 346, 346, 346, 346,
273, 273, 273, 273, 266, 334, 334, 334, 334, 334, 336, 336, 336,
336, 336, 336, 334, 334, 334, 334, 334, 334, 338, 338, 338, 338,
340, 340, 340, 338, 338, 334, 334, 334, 334, 334, 334, 334, 334,
314, 314, 314, 314, 314, 314, 314, 312, 312, 0, 0, 286, 286,
314, 314, 314, 314, 314, 314, 334, 334, 334, 334, 334, 389, 389,
389, 389, 389, 389, 389, 389, 389, 389, 389, 389, 338, 332, 332,
332, 332, 332, 332, 332, 346, 274, 391, 391, 391, 391, 0, 0,
0, 0, 316, 316, 316, 316, 316, 316, 316, 316, 842, 842, 842,
1041, 1041, 1041, 1043, 1043, 1043, 1043, 1043), mid = c(0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
0, 0, 327, 327, 327, 327, 275, 321, 321, 321, 321, 321, 321,
321, 321, 321, 325, 325, 325, 325, 323, 323, 323, 325, 325, 325,
325, 325, 325, 325, 325, 325, 319, 319, 327, 327, 327, 327, 327,
327, 327, 327, 327, 327, 327, 327, 333, 333, 212, 212, 212, 212,
212, 214, 214, 347, 347, 347, 349, 349, 349, 327, 327, 327, 327,
327, 333, 333, 321, 321, 321, 321, 321, 212, 347, 347, 347, 347,
281, 281, 281, 281, 263, 335, 335, 335, 335, 335, 337, 337, 337,
337, 337, 337, 335, 335, 335, 335, 335, 335, 339, 339, 339, 339,
341, 341, 341, 339, 339, 335, 335, 335, 335, 335, 335, 335, 335,
315, 315, 315, 315, 315, 315, 315, 313, 313, 0, 0, 214, 214,
315, 315, 315, 315, 315, 315, 335, 335, 335, 335, 335, 390, 390,
390, 390, 390, 390, 390, 390, 390, 390, 390, 390, 339, 333, 333,
333, 333, 333, 333, 333, 347, 280, 392, 392, 392, 392, 0, 0,
0, 0, 317, 317, 317, 317, 317, 317, 317, 317, 843, 843, 843,
1044, 1044, 1044, 1046, 1046, 1046, 1046, 1046), sex = structure(c(1L,
1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 2L,
1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L,
1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L,
2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L,
2L, 2L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L,
2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L,
2L, 2L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L,
1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 2L,
2L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L,
1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 1L, 2L, 2L, 2L,
1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L,
2L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L), levels = c("1", "2"), class = "factor")), row.names = c(NA,
-234L), class = c("tbl_df", "tbl", "data.frame"))这是一个结构，其中有234个人：
str(pedigree)
Classes ‘tbl_df’, ‘tbl’ and 'data.frame': 234 obs. of 4 variables:
$ id : num 212 214 263 266 273 274 275 279 280 281 ...
$ fid: num 0 0 0 0 0 0 0 0 0 0 ...
$ mid: num 0 0 0 0 0 0 0 0 0 0 ...
$ sex: Factor w/ 2 levels "1","2": 1 1 1 2 2 2 1 2 1 1 ...我正在尝试使用pedtools进行谱系分析。
为了将这个dataframe转换为ped对象，我使用了这个as.ped(pedigree)函数。
然而，我看到这个畸形的血统信息：
as.ped(pedigree)
Error: Malformed pedigree.
Individual 287 is female, but appear as the father of 568
Individual 212 is male, but appear as the mother of 568我检查了id 568、287和212，但是所有的都被正确地分配了。这意味着287是568的母亲（它被包含在fid中），类似地，212是568的父亲（并且被包含在mid中）。
作为惯例，1指男性，2指女性。
会发生什么事？
2条答案
按热度按时间kpbwa7wx1#
我检查了id 568，287和212，但是所有的都被正确的分配了。这意味着287是568的母亲（它包含在fid中），287也是如此。
看看你的数据集，有568个州的记录
287在fid列，而不是你说的中间列。数据中的某个地方有错误（要么fid和mid在这里被交换了，要么287和212的性别值被交换了）
编辑：经过进一步检查，有几个记录显示287是父亲，212是母亲，具体如下：
这可能表明287和212的sex值不正确（而不是fid和mid在几个记录之间交换），但您需要检查数据源（或处理管道）来确认
3duebb1j2#
问题是男性（1）被指定为母亲（2），女性被指定为父亲。R只返回它评估的第一个案例的错误。
您可以使用colnames重命名，然后运行代码：
你也可以直接在df中更改名称。