我在 RStudio 中有一些大型資料框，它們具有以下結構：
原始資料結構
structure(list(CHROM = c("scaffold1000|size223437", "scaffold1000|size223437",
"scaffold1000|size223437", "scaffold1000|size223437"), POS = c(666,
1332, 3445, 4336), REF = c("A", "TA", "CTTGA", "GCTA"), RO = c(20,
14, 9, 25), ALT_1 = c("GAT", "TGC", "AGC", "T"), ALT_2 = c("CAG",
"TGA", "CGC", NA), ALT_3 = c("G", NA, "TGA", NA), ALT_4 = c("AGT",
NA, NA, NA), AO_1 = c(13, 4, 67, 120), AO_2 = c(12, 5, 34, NA
), AO_3 = c(6, NA, 18, NA), AO_4 = c(101, NA, NA, NA), AOF_1 = c(8.55263157894737,
17.3913043478261, 52.34375, 82.7586206896552), AOF_2 = c(7.89473684210526,
21.7391304347826, 26.5625, NA), AOF_3 = c(3.94736842105263, NA,
14.0625, NA), AOF_4 = c(66.4473684210526, NA, NA, NA)), class = "data.frame", row.names = c(NA,
-4L))
但是對于分析，我需要它看起來像這樣：
期望輸出
structure(list(CHROM = c("scaffold1000|size223437", "scaffold1000|size223437",
"scaffold1000|size223437", "scaffold1000|size223437"), POS = c(666,
1332, 3445, 4336), REF = c("A", "TA", "CTTGA", "GCTA"), RO = c(20,
14, 9, 25), ALT_1 = c("AGT", "TGA", "AGC", "T"), ALT_2 = c("CAG",
"TGC", "CGC", NA), ALT_3 = c("G", NA, "TGA", NA), ALT_4 = c("GAT",
NA, NA, NA), AO_1 = c(101, 5, 67, 120), AO_2 = c(12, 4, 34, NA
), AO_3 = c(6, NA, 18, NA), AO_4 = c(13, NA, NA, NA), AOF_1 = c(66.4473684210526,
21.7391304347826, 52.34375, 82.7586206896552), AOF_2 = c(7.89473684210526,
17.3913043478261, 26.5625, NA), AOF_3 = c(3.94736842105263, NA,
14.0625, NA), AOF_4 = c(8.55263157894737, NA, NA, NA)), class = "data.frame", row.names = c(NA,
-4L))
所以我想做的是將一行的內容以某種方式重新排列，即ALT_1、ALT_2、ALT_3、ALT_4列按字母順序排列，但同時我也需要重新排列AO和AOF對應的列，以便值仍然匹配。（AO_1 的值仍應與 ALT_1 中的序列匹配。因此，如果排序資料框中的 ALT_1 變為 ALT_2，則 AO_1 也應變為 AO_2）
到目前為止我嘗試過但沒有用的：
將 ALT_1、AO_1、AOF_1 的值全部粘貼在一個欄位中，因此我將它們與
if (is.na(X[i,6]) == FALSE) {
X[i,6] <- paste(X[i,6],X[i,10],X[i,14],sep=" ")
}
}
然后我想提取每一行作為向量來對值進行排序并將其放回資料框中，但我沒有設法做到這一點。
所以問題是我如何訂購資料幀以獲得所需的輸出？（我需要將其應用于 32 個資料幀，每個資料幀都有 >100.000 個值）
uj5u.com熱心網友回復：
這是一種data.table方法
library(data.table)
# Set to data.table format
setDT(mydata)
# Melt to long format
DT.melt <- melt(mydata, measure.vars = patterns(ALT = "^ALT_", AO = "^AO_", AOF = "^AOF_"))
# order by groups, na's at the end
setorderv(DT.melt, cols = c("CHROM", "POS", "ALT"), na.last = TRUE)
# cast to wide again, use rowid() for numbering
dcast(DT.melt, CHROM POS REF RO ~ rowid(REF), value.var = list("ALT", "AO", "AOF"))
# CHROM POS REF RO ALT_1 ALT_2 ALT_3 ALT_4 AO_1 AO_2 AO_3 AO_4 AOF_1 AOF_2 AOF_3 AOF_4
# 1: scaffold1000|size223437 666 A 20 AGT CAG G GAT 101 12 6 13 66.44737 7.894737 3.947368 8.552632
# 2: scaffold1000|size223437 1332 TA 14 TGA TGC <NA> <NA> 5 4 NA NA 21.73913 17.391304 NA NA
# 3: scaffold1000|size223437 3445 CTTGA 9 AGC CGC TGA <NA> 67 34 18 NA 52.34375 26.562500 14.062500 NA
# 4: scaffold1000|size223437 4336 GCTA 25 T <NA> <NA> <NA> 120 NA NA NA 82.75862 NA NA NA
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