Question

我有一个带有表达式值的数据帧df，而我在数据帧Weights中具有权重。对于df中的每一列，我想将df中的每一行与Weights中具有相似行名的对应行相乘。

然后对于df中的每一列，您将获得行的加权值。

请查看我的检查输出。

df

Gene              MMRF_1021    MMRF_1024   MMRF_1029   MMRF_1030    MMRF_1031
ENSG00000007062   0.05374547   0.01258559   0.0000000   1.2985088   0.37618693
ENSG00000012124   0.13436368   0.27688288   0.2780448   0.7158432   0.03271195

重量

   Gene                   Pre.BI       Pre.BII       Immature     Naive         Memory       Plasmacell
   ENSG00000007062        0.006368928  0.000000e+00  0.000000000  0.0000000000  0.000000000  0.000000000
   ENSG00000012124        0.000000000  0.000000e+00  0.000000000  0.0000000000  0.000000000 -0.009728154

退出：

 Sample    Gene            Pre.BI            Pre.BI   Immature     Naive         Memory       Plasmacell
 MMRF_1021 ENSG00000007062 0.000342301       0        0            0             0             0
 MMRF_1021 ENSG00000012124 0                 0        0            0             0            -0.001307111
 MMRF_1024 ENSG00000007062 8.015672e-05      0        0            0             0             0
 MMRF_1024 ENSG00000012124 0                 0        0            0             0            -0.002693559
 .....

dput df：

structure(list(MMRF_1021 = c(0.0537454710193116, 0.134363677548279
), MMRF_1024 = c(0.0125855939107651, 0.276882875966623), MMRF_1029 = c(0, 
0.278044754955015), MMRF_1030 = c(1.29850876031527, 0.715843203834688
), MMRF_1031 = c(0.37618693249153, 0.032711952160723)), row.names = c("ENSG00000007062", 
"ENSG00000012124"), class = "data.frame")

输出权重：

structure(list(Pre.BI = c(0.006368928, 0), Pre.BII = c(0, 0), 
    Immature = c(0, 0), Naive = c(0, 0), Memory = c(0, 0), Plasmacell = c(0, 
    -0.009728154)), row.names = c("ENSG00000007062", "ENSG00000012124"
), class = "data.frame")

Answer 1

我认为您可能正在寻找：

library(tidyverse)

joinedDataframe <- df %>%
    rownames_to_column("gene") %>%
    gather("sample", "value", -gene) %>%
    left_join(weights %>%
                  rownames_to_column("gene")
              , by = "gene")

joinedDataframe %>%
    mutate(Pre.BI = Pre.BI * value
           , Pre.BII = Pre.BII * value
           , Immature = Immature * value
           , Naive = Naive * value
           , Memory = Memory * value
           , Plasmacell = Plasmacell * value) %>%
    select(-value)

              gene    sample       Pre.BI Pre.BII Immature Naive Memory    Plasmacell
1  ENSG00000007062 MMRF_1021 3.423010e-04       0        0     0      0  0.0000000000
2  ENSG00000012124 MMRF_1021 0.000000e+00       0        0     0      0 -0.0013071105
3  ENSG00000007062 MMRF_1024 8.015674e-05       0        0     0      0  0.0000000000
4  ENSG00000012124 MMRF_1024 0.000000e+00       0        0     0      0 -0.0026935593
5  ENSG00000007062 MMRF_1029 0.000000e+00       0        0     0      0  0.0000000000
6  ENSG00000012124 MMRF_1029 0.000000e+00       0        0     0      0 -0.0027048622
7  ENSG00000007062 MMRF_1030 8.270109e-03       0        0     0      0  0.0000000000
8  ENSG00000012124 MMRF_1030 0.000000e+00       0        0     0      0 -0.0069638329
9  ENSG00000007062 MMRF_1031 2.395907e-03       0        0     0      0  0.0000000000
10 ENSG00000012124 MMRF_1031 0.000000e+00       0        0     0      0 -0.0003182269

Answer 2

看到您的预期结果，我认为以下是您所追求的。例如，Plasmacell的{{1}}是-0.002693559（0.27688288 * -0.009728154）。为了获得此数字，我将两个数据帧都转换为长格式数据。然后，我加入了他们。到此时，您有两列要处理乘法（即gene_value和value）。之后，我将数据转换为宽格式的数据框。

MMRF_1024 ENSG00000012124

Answer 3

这是基本的R解决方案

dfout <- do.call(rbind,
                 c(make.row.names = F,
                   lapply(seq(ncol(df)), 
                          function(k) cbind(Gene = rownames(df[k]), 
                                            Sample = names(df[k]), 
                                            df[,k]*weights[match(rownames(weights),rownames(df)),]))))

这样

> dfout
              Gene    Sample       Pre.BI Pre.BII Immature Naive Memory    Plasmacell
1  ENSG00000007062 MMRF_1021 3.423010e-04       0        0     0      0  0.0000000000
2  ENSG00000012124 MMRF_1021 0.000000e+00       0        0     0      0 -0.0013071105
3  ENSG00000007062 MMRF_1024 8.015674e-05       0        0     0      0  0.0000000000
4  ENSG00000012124 MMRF_1024 0.000000e+00       0        0     0      0 -0.0026935593
5  ENSG00000007062 MMRF_1029 0.000000e+00       0        0     0      0  0.0000000000
6  ENSG00000012124 MMRF_1029 0.000000e+00       0        0     0      0 -0.0027048622
7  ENSG00000007062 MMRF_1030 8.270109e-03       0        0     0      0  0.0000000000
8  ENSG00000012124 MMRF_1030 0.000000e+00       0        0     0      0 -0.0069638329
9  ENSG00000007062 MMRF_1031 2.395907e-03       0        0     0      0  0.0000000000
10 ENSG00000012124 MMRF_1031 0.000000e+00       0        0     0      0 -0.0003182269

将数据帧与来自另一个数据帧的权重相乘

3 个答案: