從R中的不同劑量矩陣計算次要等位基因頻率-有解無憂

我有一個變體劑量矩陣，想計算資料幀的每個變體（行）的次要等位基因頻率（MAF）dose_df。

我想問你是否正確地說變體的等位基因頻率 (AF) 將通過考慮sum一行中的每個值除以個體總數的兩倍來計算。那么如果AF值小于0.5就被認為是MAF，否則1-AF_value將是 MAF 值。如果是，則下面的 for 回圈是否可以完成這項作業。

根據上述假設，這里是劑量矩陣的一部分，稱為dose_df：

dose_df <- structure(list(CHR = c("chr22", "chr22", "chr22", "chr22", "chr22", 
"chr22", "chr22", "chr22", "chr22", "chr22", "chr22", "chr22", 
"chr22", "chr22", "chr22", "chr22", "chr22", "chr22", "chr22", 
"chr22"), POS = c(10519389L, 10526179L, 10526296L, 10527090L, 
10530609L, 10557732L, 10557819L, 10557824L, 10557840L, 10558138L, 
10559721L, 10559769L, 10560849L, 10560850L, 10560850L, 10560915L, 
10561980L, 10562747L, 10562991L, 10563056L), ID = c("chr22_10519389_T_C_b38", 
"chr22_10526179_G_A_b38", "chr22_10526296_G_A_b38", "chr22_10527090_C_T_b38", 
"chr22_10530609_C_T_b38", "chr22_10557732_G_A_b38", "chr22_10557819_C_G_b38", 
"chr22_10557824_AC_A_b38", "chr22_10557840_G_A_b38", "chr22_10558138_CT_C_b38", 
"chr22_10559721_AG_A_b38", "chr22_10559769_G_T_b38", "chr22_10560849_C_T_b38", 
"chr22_10560850_G_A_b38", "chr22_10560850_G_C_b38", "chr22_10560915_C_T_b38", 
"chr22_10561980_A_T_b38", "chr22_10562747_AGTTTT_A_b38", "chr22_10562991_G_T_b38", 
"chr22_10563056_C_T_b38"), `GTEX-1122O` = c(0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), `GTEX-11EM3` = c(0, 
0, 0, 0, 1, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0, 1), `GTEX-11EMC` = c(1, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), `GTEX-11EQ9` = c(1, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), `GTEX-11I78` = c(1, 
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0), `GTEX-11VI4` = c(0, 
0, 2, 0, 0, 2, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0), `GTEX-11ZTT` = c(2, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0), `GTEX-1211K` = c(2, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0), `GTEX-1212Z` = c(2, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), `GTEX-12696` = c(2, 
0, 0, 0, 2, 0, 2, 0, 0, 2, 0, 0, 2, 0, 0, 2, 2, 1, 0, 2), `GTEX-1269C` = c(2, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), `GTEX-12C56` = c(2, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0), `GTEX-12WSJ` = c(2, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0), `GTEX-12WSL` = c(2, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0), `GTEX-12WSN` = c(0, 
2, 0, 1, 0, 1, 0, 0, 2, 0, 0, 0, 0, 2, 0, 0, 0, 0, 2, 0), `GTEX-13111` = c(2, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0), `GTEX-1399R` = c(2, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0)), row.names = c(NA, 
-20L), class = c("data.table", 
"data.frame"))

我試圖通過一個回圈來完成這項作業：

for (i in 1:nrow(dose_df)){
            dose_df$maf[i] <- sum(dose_df[i, -c(1,2,3)])/(2 * length(dose_df[, -c(1,2,3)]))
                  if (dose_df$maf[i] < 0.5){
                      dose_df$maf[i] <- dose_df$maf[i]
                  } else if (dose_df$maf[i] > 0.5)  {
                             dose_df$maf[i] <- 1 - dose_df$maf[i]
                        }
}

這是dose_df$maf：

> dose_df$maf
 [1] 0.32352941 0.07434641 0.07434641 0.04656863 0.10212418 0.10212418 0.07434641 0.04656863 0.12990196 0.07434641 0.01879085
[12] 0.12990196 0.10212418 0.12990196 0.04656863 0.10212418 0.10212418 0.26879085 0.07434641 0.10212418

uj5u.com熱心網友回復：

這可以用向量化rowSums而ifelse不是回圈遍歷每一行

tmp <- rowSums(dose_df[,-(1:3)])/(2 * (ncol(dose_df) - 3))
ifelse(tmp > 0.5, 1 - tmp, tmp)

-輸出

[1] 0.32352941 0.05882353 0.05882353 0.02941176 0.08823529 0.08823529 0.05882353 0.02941176 0.11764706 0.05882353 0.00000000 0.11764706 0.08823529 0.11764706 0.02941176 0.08823529
[17] 0.08823529 0.26470588 0.05882353 0.08823529

for回圈輸出不正確，因為在第一次迭代中添加了列maf。因此，當我們取時length，它將增加 1（在第一次迭代之后）。防止這種情況的一種方法是length在我們回圈之前采用初始值

tmp1 <- dose_df[, -c(1,2,3)]
l1 <- ncol(tmp1)
dose_df$maf <- NA_real_
for (i in 1:nrow(dose_df)){
            dose_df$maf[i] <- sum(tmp1[i,])/(2 * l1)
                  if (dose_df$maf[i] < 0.5){
                      dose_df$maf[i] <- dose_df$maf[i]
                  } else if (dose_df$maf[i] > 0.5)  {
                             dose_df$maf[i] <- 1 - dose_df$maf[i]
                        }
}

-輸出

> dose_df$maf
 [1] 0.32352941 0.05882353 0.05882353 0.02941176 0.08823529 0.08823529 0.05882353 0.02941176 0.11764706 0.05882353 0.00000000 0.11764706 0.08823529 0.11764706 0.02941176 0.08823529
[17] 0.08823529 0.26470588 0.05882353 0.08823529

轉載請註明出處，本文鏈接：https://www.uj5u.com/ruanti/505231.html

標籤：r for循环 vcf 变体调用格式

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