按样本列名称平均质量规格峰值计数

Question

希望这是直截了当的，我只是想得太仔细了。我有一个质谱(MS)的峰值计数矩阵，其中峰值是行，列是样本名。样本地点有几个取样点，我想在各地点之间添加计数。

例如，一个具有三个副本的样本被识别为"S19S_0010_Sed_Field_ICR.D_p2“、"S19S_0010_Sed_Field_ICR.M_p2”和"S19S_0010_Sed_Field_ICR.U_p2“，它们位于同一位置，但位于下游(D)、中流(M)和上游(U)。前两个样本每个都有一个特定峰值的计数，所以我想将这三个样本合并为"S19S_0010_Sed_Field_ICR.all_p2“和两个波长计数。示例数据集：

> dput(data.sed.ex)
structure(list(S19S_0004_Sed_Field_ICR.M_p15 = c(0, 0, 0, 0, 
0, 0, 0, 0, 0, 0), S19S_0006_Sed_Field_ICR.D_p2 = c(0, 0, 0, 
0, 0, 0, 1, 1, 0, 0), S19S_0006_Sed_Field_ICR.M_p2 = c(0, 0, 
0, 0, 0, 0, 1, 0, 0, 0), S19S_0006_Sed_Field_ICR.U_p2 = c(0, 
0, 0, 0, 0, 0, 1, 1, 0, 0), S19S_0008_Sed_Field_ICR.M_p15 = c(0, 
0, 0, 0, 0, 0, 0, 1, 0, 0), S19S_0009_Sed_Field_ICR.M_p2 = c(0, 
0, 1, 0, 0, 0, 1, 0, 0, 0), S19S_0009_Sed_Field_ICR.U_p2 = c(0, 
0, 0, 0, 0, 0, 1, 0, 0, 0), S19S_0010_Sed_Field_ICR.D_p15 = c(0, 
0, 0, 0, 0, 0, 1, 0, 0, 0), S19S_0010_Sed_Field_ICR.M_p15 = c(0, 
0, 0, 0, 0, 0, 1, 0, 0, 0), S19S_0010_Sed_Field_ICR.U_p15 = c(0, 
0, 0, 0, 0, 0, 0, 0, 0, 0)), row.names = c("200.002276", "200.015107", 
"200.0564158", "200.0565393", "200.0578394", "200.0677581", "200.092796", 
"200.1291723", "200.1292836", "200.9238455"), class = "data.frame")

提亚

Answer 1

也许长篇大论的争论会有所帮助。在这种格式中，您可以使用sum、mean、sd等按组(例如示例或示例和位置)进行汇总。

希望这能帮上忙

转换为长格式

## dd is the `data.sed.ex` object above

library(tidyverse)                                                                                                                                                           
ddLong <- dd %>%
  rownames_to_column(var = "peak") %>%
  pivot_longer(cols = matches("^S")) %>%
  mutate(sample = gsub("(.*)\\.(.*)", "\\1", name),           ## pull sample info                                                                                          
         location = gsub("(.*)\\.([DMU])_(.*)", "\\2", name), ## pull D M U                                                                                                
         p = gsub("(.*)\\.([DMU])_(p.*)", "\\3", name),       ## get p2, p15                                                                                               
         peak = as.numeric(peak))             ## coerce peak to numeric                                                                                                    

ddLong
#> # A tibble: 100 × 6
#>     peak name                          value sample               location p    
#>    <dbl> <chr>                         <dbl> <chr>                <chr>    <chr>
#>  1  200. S19S_0004_Sed_Field_ICR.M_p15     0 S19S_0004_Sed_Field… M        p15  
#>  2  200. S19S_0006_Sed_Field_ICR.D_p2      0 S19S_0006_Sed_Field… D        p2   
#>  3  200. S19S_0006_Sed_Field_ICR.M_p2      0 S19S_0006_Sed_Field… M        p2   
#>  4  200. S19S_0006_Sed_Field_ICR.U_p2      0 S19S_0006_Sed_Field… U        p2   
#>  5  200. S19S_0008_Sed_Field_ICR.M_p15     0 S19S_0008_Sed_Field… M        p15  
#>  6  200. S19S_0009_Sed_Field_ICR.M_p2      0 S19S_0009_Sed_Field… M        p2   
#>  7  200. S19S_0009_Sed_Field_ICR.U_p2      0 S19S_0009_Sed_Field… U        p2   
#>  8  200. S19S_0010_Sed_Field_ICR.D_p15     0 S19S_0010_Sed_Field… D        p15  
#>  9  200. S19S_0010_Sed_Field_ICR.M_p15     0 S19S_0010_Sed_Field… M        p15  
#> 10  200. S19S_0010_Sed_Field_ICR.U_p15     0 S19S_0010_Sed_Field… U        p15  
#> # … with 90 more rows

按一个或多个组进行总结

## summarise using group_by + verbs                                                                                                                                          
ddLong %>%                                                                                                                                                                   
  group_by(sample, location) %>%                                                                                                                                           
  summarise(n = n(),                                                                                                                                                       
            sum.value = sum(value),                                                                                                                                        
            mean.peak = mean(peak))                                                                                                                                        
#> `summarise()` has grouped output by 'sample'. You can override using the
#> `.groups` argument.
#> # A tibble: 10 × 5
#> # Groups:   sample [5]
#>    sample                  location     n sum.value mean.peak
#>    <chr>                   <chr>    <int>     <dbl>     <dbl>
#>  1 S19S_0004_Sed_Field_ICR M           10         0      200.
#>  2 S19S_0006_Sed_Field_ICR D           10         2      200.
#>  3 S19S_0006_Sed_Field_ICR M           10         1      200.
#>  4 S19S_0006_Sed_Field_ICR U           10         2      200.
#>  5 S19S_0008_Sed_Field_ICR M           10         1      200.
#>  6 S19S_0009_Sed_Field_ICR M           10         2      200.
#>  7 S19S_0009_Sed_Field_ICR U           10         1      200.
#>  8 S19S_0010_Sed_Field_ICR D           10         1      200.
#>  9 S19S_0010_Sed_Field_ICR M           10         1      200.
#> 10 S19S_0010_Sed_Field_ICR U           10         0      200.

                                                                                                    
ddLong %>%                                                                                                                                                                   
    group_by(sample, p) %>%                                             
    summarise(n = n(),                                                                                                                                                       
              sum.value = sum(value),                                                                                                                                        
              mean.peak = mean(peak))                                                                                                                                        
#> `summarise()` has grouped output by 'sample'. You can override using the
#> `.groups` argument.
#> # A tibble: 5 × 5
#> # Groups:   sample [5]
#>   sample                  p         n sum.value mean.peak
#>   <chr>                   <chr> <int>     <dbl>     <dbl>
#> 1 S19S_0004_Sed_Field_ICR p15      10         0      200.
#> 2 S19S_0006_Sed_Field_ICR p2       30         5      200.
#> 3 S19S_0008_Sed_Field_ICR p15      10         1      200.
#> 4 S19S_0009_Sed_Field_ICR p2       20         3      200.
#> 5 S19S_0010_Sed_Field_ICR p15      30         2      200.