使用 R 将行转换为列并 header

Converting rows into columns and header using R

您好,有一个文本文件 summary.txt 看起来像这样

snp_fp_overlapp_count: 0
snp_fn_overlapp_count: 0
snp_fn_ca_overlapp_count: 0
snp_fn_ca_0: 0
indel_fp_overlapp_count: 0
indel_fn_overlapp_count: 0
indel_fn_ca_overlapp_count: 0
indel_fn_ca_0: 0
-------------------------------------
snp_hard_count: 0
indel_hard_count: 0
unknown_count: 0
-------------------------------------
total_baseline_snp: 12405
total_baseline_indel: 1137
-------------------------------------
Precision_SNP: 0.790329
Sensitivity_SNP: 0.972350
F_Measure_SNP: 0.871941
-------------------------------------
Precision_INDEL: 0.119915
Sensitivity_INDEL: 0.941073
F_Measure_INDEL: 0.212724
-------------------------------------
Annotation Percent Match:
-------------------------------------
-------------------------------------

我需要将指标名称转换为列并将其值转换为 R 中的第 2 行,下面的代码片段

Precision_INDEL Sensitivity_INDEL   F_Measure_INDEL
0.119915    0.941073    0.212724

不确定如何解决这个问题,我一直在与 tidyverse 作斗争,但这似乎不是解决方案

mydata = read_table("summary.txt")

mydata %>% 
  rownames_to_column() %>% 
  gather(variable, value, -rowname) %>% 
  separate(variable ,sep = ":",into = c("metric","value")) %>%
  spread(rowname, value)

任何 pointers/solutions 都会有用

谢谢

这是你需要的吗?我不确定你的意思 'in table format'.

dat = data.table::fread('snp_fp_overlapp_count: 0
snp_fn_overlapp_count: 0
snp_fn_ca_overlapp_count: 0
snp_fn_ca_0: 0
indel_fp_overlapp_count: 0
indel_fn_overlapp_count: 0
indel_fn_ca_overlapp_count: 0
indel_fn_ca_0: 0
snp_hard_count: 0
indel_hard_count: 0
unknown_count: 0
total_baseline_snp: 12405
total_baseline_indel: 1137
Precision_SNP: 0.790329
Sensitivity_SNP: 0.972350
F_Measure_SNP: 0.871941
Precision_INDEL: 0.119915
Sensitivity_INDEL: 0.941073
F_Measure_INDEL: 0.212724
Annotation Percent Match:
', sep=" ")
a = dat %>% tidyr::pivot_wider(names_from="V1", values_from="V2")
# A tibble: 1 x 19
  `snp_fp_overlapp_co… `snp_fn_overlapp_co… `snp_fn_ca_overlapp_… `snp_fn_ca_0:`
                 <dbl>                <dbl>                 <dbl>          <dbl>
1                    0                    0                     0              0
# … with 15 more variables: indel_fp_overlapp_count: <dbl>,
#   indel_fn_overlapp_count: <dbl>, indel_fn_ca_overlapp_count: <dbl>,
#   indel_fn_ca_0: <dbl>, snp_hard_count: <dbl>, indel_hard_count: <dbl>,
#   unknown_count: <dbl>, total_baseline_snp: <dbl>,
#   total_baseline_indel: <dbl>, Precision_SNP: <dbl>, Sensitivity_SNP: <dbl>,
#   F_Measure_SNP: <dbl>, Precision_INDEL: <dbl>, Sensitivity_INDEL: <dbl>,
#   F_Measure_INDEL: <dbl>
> colnames(a)
 [1] "snp_fp_overlapp_count:"      "snp_fn_overlapp_count:"     
 [3] "snp_fn_ca_overlapp_count:"   "snp_fn_ca_0:"               
 [5] "indel_fp_overlapp_count:"    "indel_fn_overlapp_count:"   
 [7] "indel_fn_ca_overlapp_count:" "indel_fn_ca_0:"             
 [9] "snp_hard_count:"             "indel_hard_count:"          
[11] "unknown_count:"              "total_baseline_snp:"        
[13] "total_baseline_indel:"       "Precision_SNP:"             
[15] "Sensitivity_SNP:"            "F_Measure_SNP:"             
[17] "Precision_INDEL:"            "Sensitivity_INDEL:"         
[19] "F_Measure_INDEL:"           
> as.numeric(a[1,])
 [1]     0.000000     0.000000     0.000000     0.000000     0.000000
 [6]     0.000000     0.000000     0.000000     0.000000     0.000000
[11]     0.000000 12405.000000  1137.000000     0.790329     0.972350
[16]     0.871941     0.119915     0.941073     0.212724