合并文本文件中的多个表（相同的标题）

【问题标题】：Merge multiple tables (identical headers) within a text file合并文本文件中的多个表（相同的标题）
【发布时间】：2022-01-09 02:20:32
【问题描述】：

假设我有 200 多个文件，每个文件的结构如下所示：

# Peptide length 11
# Rank Threshold for Strong binding peptides   0.500
# Rank Threshold for Weak binding peptides   2.000
-----------------------------------------------------------------------------------
  pos          HLA      peptide         Core Offset  I_pos  I_len  D_pos  D_len        iCore        Identity 1-log50k(aff) Affinity(nM)    %Rank  BindLevel
-----------------------------------------------------------------------------------
    0    HLA-B4402  GSHDLGIILQK    GSHDLGIIL      0      0      0      0      0    GSHDLGIIL NM_000094_3_COL         0.015     42580.79    90.00
    1    HLA-B4402  SHDLGIILQKI    SLGIILQKI      0      0      0      1      2  SHDLGIILQKI NM_000094_3_COL         0.024     38731.55    65.00
    2    HLA-B4402  HDLGIILQKIR    HDLIILQKI      0      0      0      3      1   HDLGIILQKI NM_000094_3_COL         0.024     38400.24    65.00
    3    HLA-B4402  DLGIILQKIRD    DLGIILQKI      0      0      0      0      0    DLGIILQKI NM_000094_3_COL         0.011     44267.78    95.00
    4    HLA-B4402  LGIILQKIRDM    LGIILQRDM      0      0      0      6      2  LGIILQKIRDM NM_000094_3_COL         0.024     38411.46    65.00
    5    HLA-B4402  GIILQKIRDMP    GIILQIRDM      0      0      0      5      1   GIILQKIRDM NM_000094_3_COL         0.017     41463.75    80.00
    6    HLA-B4402  IILQKIRDMPY    IILQKIRDY      0      0      0      8      2  IILQKIRDMPY NM_000094_3_COL         0.025     38152.18    65.00
    7    HLA-B4402  ILQKIRDMPYM    ILQKIRMPY      0      0      0      6      1   ILQKIRDMPY NM_000094_3_COL         0.025     37993.98    60.00
    8    HLA-B4402  LQKIRDMPYMD    QKIRDMPYM      1      0      0      0      0    QKIRDMPYM NM_000094_3_COL         0.015     42595.54    90.00
    9    HLA-B4402  QKIRDMPYMDP    QKIRDMPYM      0      0      0      0      0    QKIRDMPYM NM_000094_3_COL         0.017     41645.82    85.00
   10    HLA-B4402  KIRDMPYMDPS    KDMPYMDPS      0      0      0      1      2  KIRDMPYMDPS NM_000094_3_COL         0.023     39039.53    70.00
   11    HLA-B4402  IRDMPYMDPSX    RDMPYMPSX      1      0      0      6      1   RDMPYMDPSX NM_000094_3_COL         0.036     33871.57    41.00
-----------------------------------------------------------------------------------

Protein NM_000094_3_COL. Allele HLA-B4402. Number of high binders 0. Number of weak binders 0. Number of peptides 12

-----------------------------------------------------------------------------------
# Rank Threshold for Strong binding peptides   0.500
# Rank Threshold for Weak binding peptides   2.000
-----------------------------------------------------------------------------------
  pos          HLA      peptide         Core Offset  I_pos  I_len  D_pos  D_len        iCore        Identity 1-log50k(aff) Affinity(nM)    %Rank  BindLevel
-----------------------------------------------------------------------------------
    0    HLA-B4402  PVTGYKVQYTS    TGYKVQYTS      2      0      0      0      0    TGYKVQYTS NM_000094_3_COL         0.011     44190.25    95.00
    1    HLA-B4402  VTGYKVQYTSL    VTGYQYTSL      0      0      0      4      2  VTGYKVQYTSL NM_000094_3_COL         0.020     40061.36    75.00
    2    HLA-B4402  TGYKVQYTSLT    TGYKVYTSL      0      0      0      5      1   TGYKVQYTSL NM_000094_3_COL         0.020     40487.08    75.00
    3    HLA-B4402  GYKVQYTSLTG    YVQYTSLTG      1      0      0      1      1   YKVQYTSLTG NM_000094_3_COL         0.017     41521.20    80.00
    4    HLA-B4402  YKVQYTSLTGL    YQYTSLTGL      0      0      0      1      2  YKVQYTSLTGL NM_000094_3_COL         0.031     35710.76    49.00
    5    HLA-B4402  KVQYTSLTGLG    KVQYTSLTL      0      0      0      8      1   KVQYTSLTGL NM_000094_3_COL         0.029     36392.20    55.00
    6    HLA-B4402  VQYTSLTGLGQ    VQYTSLTGL      0      0      0      0      0    VQYTSLTGL NM_000094_3_COL         0.016     42180.50    85.00
    7    HLA-B4402  QYTSLTGLGQP    QYTSLTGLG      0      0      0      0      0    QYTSLTGLG NM_000094_3_COL         0.011     44293.17    95.00
    8    HLA-B4402  YTSLTGLGQPL    YTSLLGQPL      0      0      0      4      2  YTSLTGLGQPL NM_000094_3_COL         0.034     34547.04    44.00
    9    HLA-B4402  TSLTGLGQPLP    SLTGLGQPL      1      0      0      0      0    SLTGLGQPL NM_000094_3_COL         0.024     38475.10    65.00
   10    HLA-B4402  SLTGLGQPLPS    SLTGLGQPL      0      0      0      0      0    SLTGLGQPL NM_000094_3_COL         0.026     37575.76    60.00
   11    HLA-B4402  LTGLGQPLPSX    LLGQPLPSX      0      0      0      1      2  LTGLGQPLPSX NM_000094_3_COL         0.014     42874.84    90.00
-----------------------------------------------------------------------------------

Protein NM_000094_3_COL. Allele HLA-B4402. Number of high binders 0. Number of weak binders 0. Number of peptides 12

-----------------------------------------------------------------------------------
# Rank Threshold for Strong binding peptides   0.500
# Rank Threshold for Weak binding peptides   2.000
-----------------------------------------------------------------------------------
  pos          HLA      peptide         Core Offset  I_pos  I_len  D_pos  D_len        iCore        Identity 1-log50k(aff) Affinity(nM)    %Rank  BindLevel
-----------------------------------------------------------------------------------
    0    HLA-B4402  FLRLLDLAQEE    RLLDLAQEE      2      0      0      0      0    RLLDLAQEE NM_000106_5_CYP         0.014     42841.45    90.00
    1    HLA-B4402  LRLLDLAQEEL    RLLDLAQEL      1      0      0      7      1   RLLDLAQEEL NM_000106_5_CYP         0.029     36648.25    55.00
    2    HLA-B4402  RLLDLAQEELK    RLLDLAQEL      0      0      0      7      1   RLLDLAQEEL NM_000106_5_CYP         0.029     36350.87    55.00
    3    HLA-B4402  LLDLAQEELKE    LLDLAQEEL      0      0      0      0      0    LLDLAQEEL NM_000106_5_CYP         0.013     43487.79    95.00
    4    HLA-B4402  LDLAQEELKEE    LDQEELKEE      0      0      0      2      2  LDLAQEELKEE NM_000106_5_CYP         0.008     45629.40    99.00
    5    HLA-B4402  DLAQEELKEES    AQEELKEES      2      0      0      0      0    AQEELKEES NM_000106_5_CYP         0.009     45287.57    99.00
    6    HLA-B4402  LAQEELKEESG    AEELKEESG      1      0      0      1      1   AQEELKEESG NM_000106_5_CYP         0.013     43568.32    95.00
    7    HLA-B4402  AQEELKEESGF    AELKEESGF      0      0      0      1      2  AQEELKEESGF NM_000106_5_CYP         0.231      4113.65     2.50
    8    HLA-B4402  QEELKEESGFL    QELKEESGF      0      0      0      1      1   QEELKEESGF NM_000106_5_CYP         0.123     13202.71     6.00
    9    HLA-B4402  EELKEESGFLR    EELKEESGF      0      0      0      0      0    EELKEESGF NM_000106_5_CYP         0.076     21904.46    13.00
   10    HLA-B4402  ELKEESGFLRE    ELKEESGFL      0      0      0      0      0    ELKEESGFL NM_000106_5_CYP         0.030     36301.74    55.00
   11    HLA-B4402  LKEESGFLREX    KEESFLREX      1      0      0      4      1   KEESGFLREX NM_000106_5_CYP         0.060     26205.35    19.00
-----------------------------------------------------------------------------------

可以看出，每个文件基本上都是表格的组合（具有相同的标题），表格之间有文本。我想只保留表格 - 如果可能的话，去掉那些虚线，只保留每行用 \t 分隔的数据（和标题）。

最佳结果是这样的：

pos          HLA      peptide         Core Offset  I_pos  I_len  D_pos  D_len        iCore        Identity 1-log50k(aff) Affinity(nM)    %Rank  BindLevel
    0    HLA-B4402  GSHDLGIILQK    GSHDLGIIL      0      0      0      0      0    GSHDLGIIL NM_000094_3_COL         0.015     42580.79    90.00
    1    HLA-B4402  SHDLGIILQKI    SLGIILQKI      0      0      0      1      2  SHDLGIILQKI NM_000094_3_COL         0.024     38731.55    65.00
    2    HLA-B4402  HDLGIILQKIR    HDLIILQKI      0      0      0      3      1   HDLGIILQKI NM_000094_3_COL         0.024     38400.24    65.00
    3    HLA-B4402  DLGIILQKIRD    DLGIILQKI      0      0      0      0      0    DLGIILQKI NM_000094_3_COL         0.011     44267.78    95.00
    4    HLA-B4402  LGIILQKIRDM    LGIILQRDM      0      0      0      6      2  LGIILQKIRDM NM_000094_3_COL         0.024     38411.46    65.00
    5    HLA-B4402  GIILQKIRDMP    GIILQIRDM      0      0      0      5      1   GIILQKIRDM NM_000094_3_COL         0.017     41463.75    80.00
    6    HLA-B4402  IILQKIRDMPY    IILQKIRDY      0      0      0      8      2  IILQKIRDMPY NM_000094_3_COL         0.025     38152.18    65.00
    7    HLA-B4402  ILQKIRDMPYM    ILQKIRMPY      0      0      0      6      1   ILQKIRDMPY NM_000094_3_COL         0.025     37993.98    60.00
    8    HLA-B4402  LQKIRDMPYMD    QKIRDMPYM      1      0      0      0      0    QKIRDMPYM NM_000094_3_COL         0.015     42595.54    90.00
    9    HLA-B4402  QKIRDMPYMDP    QKIRDMPYM      0      0      0      0      0    QKIRDMPYM NM_000094_3_COL         0.017     41645.82    85.00
   10    HLA-B4402  KIRDMPYMDPS    KDMPYMDPS      0      0      0      1      2  KIRDMPYMDPS NM_000094_3_COL         0.023     39039.53    70.00
   11    HLA-B4402  IRDMPYMDPSX    RDMPYMPSX      1      0      0      6      1   RDMPYMDPSX NM_000094_3_COL         0.036     33871.57    41.00
    0    HLA-B4402  PVTGYKVQYTS    TGYKVQYTS      2      0      0      0      0    TGYKVQYTS NM_000094_3_COL         0.011     44190.25    95.00
    1    HLA-B4402  VTGYKVQYTSL    VTGYQYTSL      0      0      0      4      2  VTGYKVQYTSL NM_000094_3_COL         0.020     40061.36    75.00
    2    HLA-B4402  TGYKVQYTSLT    TGYKVYTSL      0      0      0      5      1   TGYKVQYTSL NM_000094_3_COL         0.020     40487.08    75.00
    3    HLA-B4402  GYKVQYTSLTG    YVQYTSLTG      1      0      0      1      1   YKVQYTSLTG NM_000094_3_COL         0.017     41521.20    80.00
    4    HLA-B4402  YKVQYTSLTGL    YQYTSLTGL      0      0      0      1      2  YKVQYTSLTGL NM_000094_3_COL         0.031     35710.76    49.00
    5    HLA-B4402  KVQYTSLTGLG    KVQYTSLTL      0      0      0      8      1   KVQYTSLTGL NM_000094_3_COL         0.029     36392.20    55.00
    6    HLA-B4402  VQYTSLTGLGQ    VQYTSLTGL      0      0      0      0      0    VQYTSLTGL NM_000094_3_COL         0.016     42180.50    85.00
    7    HLA-B4402  QYTSLTGLGQP    QYTSLTGLG      0      0      0      0      0    QYTSLTGLG NM_000094_3_COL         0.011     44293.17    95.00
    8    HLA-B4402  YTSLTGLGQPL    YTSLLGQPL      0      0      0      4      2  YTSLTGLGQPL NM_000094_3_COL         0.034     34547.04    44.00
    9    HLA-B4402  TSLTGLGQPLP    SLTGLGQPL      1      0      0      0      0    SLTGLGQPL NM_000094_3_COL         0.024     38475.10    65.00
   10    HLA-B4402  SLTGLGQPLPS    SLTGLGQPL      0      0      0      0      0    SLTGLGQPL NM_000094_3_COL         0.026     37575.76    60.00
   11    HLA-B4402  LTGLGQPLPSX    LLGQPLPSX      0      0      0      1      2  LTGLGQPLPSX NM_000094_3_COL         0.014     42874.84    90.00
    0    HLA-B4402  FLRLLDLAQEE    RLLDLAQEE      2      0      0      0      0    RLLDLAQEE NM_000106_5_CYP         0.014     42841.45    90.00
    1    HLA-B4402  LRLLDLAQEEL    RLLDLAQEL      1      0      0      7      1   RLLDLAQEEL NM_000106_5_CYP         0.029     36648.25    55.00
    2    HLA-B4402  RLLDLAQEELK    RLLDLAQEL      0      0      0      7      1   RLLDLAQEEL NM_000106_5_CYP         0.029     36350.87    55.00
    3    HLA-B4402  LLDLAQEELKE    LLDLAQEEL      0      0      0      0      0    LLDLAQEEL NM_000106_5_CYP         0.013     43487.79    95.00
    4    HLA-B4402  LDLAQEELKEE    LDQEELKEE      0      0      0      2      2  LDLAQEELKEE NM_000106_5_CYP         0.008     45629.40    99.00
    5    HLA-B4402  DLAQEELKEES    AQEELKEES      2      0      0      0      0    AQEELKEES NM_000106_5_CYP         0.009     45287.57    99.00
    6    HLA-B4402  LAQEELKEESG    AEELKEESG      1      0      0      1      1   AQEELKEESG NM_000106_5_CYP         0.013     43568.32    95.00
    7    HLA-B4402  AQEELKEESGF    AELKEESGF      0      0      0      1      2  AQEELKEESGF NM_000106_5_CYP         0.231      4113.65     2.50
    8    HLA-B4402  QEELKEESGFL    QELKEESGF      0      0      0      1      1   QEELKEESGF NM_000106_5_CYP         0.123     13202.71     6.00
    9    HLA-B4402  EELKEESGFLR    EELKEESGF      0      0      0      0      0    EELKEESGF NM_000106_5_CYP         0.076     21904.46    13.00
   10    HLA-B4402  ELKEESGFLRE    ELKEESGFL      0      0      0      0      0    ELKEESGFL NM_000106_5_CYP         0.030     36301.74    55.00
   11    HLA-B4402  LKEESGFLREX    KEESFLREX      1      0      0      4      1   KEESGFLREX NM_000106_5_CYP         0.060     26205.35    19.00

这就是我正在努力解决的问题：

1。如何将同一文件中的所有表连接到一个表中？

2。是否可以将所有文件中的所有表连接到一个表中？

如果有办法在 R 中做到这一点，也可以。

非常感谢！

PS：我浏览了类似问题部分，但在这一行中找不到任何解决方案。

【问题讨论】：

    标签： r linux dataframe


    【解决方案1】：

    应该是这样的：

    df_list <- lapply(file_names, read.table, skip = 6)
df <- do.call('rbind', df_list)

    然后在末尾添加您的列名。

    【讨论】：

      【解决方案2】：

      这将从一个文件中提取和解析数据。

      我尝试拆分数据并添加标题，但我不能 100% 确定它是否正常工作，

      library(dplyr)

original_df <-
  as.data.frame(readLines("ProteinData.txt", warn = FALSE))

colnames(original_df) <- c("Column1")

header <- original_df %>% filter(str_detect(Column1, "^\\s+pos"))

header <- unlist(str_split(head(header, 1), "\\s+"))

header <- replace(header, header == "" , "Unused")

parsed_df <- original_df %>%
  filter(str_detect(Column1, "^\\W+\\d")) %>%
  separate(Column1, header, sep = "\\s+") %>%
  select(!c(1))
      pos HLA peptide Core Offset I_pos I_len D_pos D_len iCore Identity 1-log50k(aff) Affinity(nM) %Rank BindLevel
      0 HLA-B4402 GSHDLGIILQK GSHDLGIIL 0 0 0 0 0 GSHDLGIIL NM_000094_3_COL 0.015 42580.79 90.00 NA
      1 HLA-B4402 SHDLGIILQKI SLGIILQKI 0 0 0 1 2 SHDLGIILQKI NM_000094_3_COL 0.024 38731.55 65.00 NA
      2 HLA-B4402 HDLGIILQKIR HDLIILQKI 0 0 0 3 1 HDLGIILQKI NM_000094_3_COL 0.024 38400.24 65.00 NA
      3 HLA-B4402 DLGIILQKIRD DLGIILQKI 0 0 0 0 0 DLGIILQKI NM_000094_3_COL 0.011 44267.78 95.00 NA
      4 HLA-B4402 LGIILQKIRDM LGIILQRDM 0 0 0 6 2 LGIILQKIRDM NM_000094_3_COL 0.024 38411.46 65.00 NA
      5 HLA-B4402 GIILQKIRDMP GIILQIRDM 0 0 0 5 1 GIILQKIRDM NM_000094_3_COL 0.017 41463.75 80.00 NA
      6 HLA-B4402 IILQKIRDMPY IILQKIRDY 0 0 0 8 2 IILQKIRDMPY NM_000094_3_COL 0.025 38152.18 65.00 NA
      7 HLA-B4402 ILQKIRDMPYM ILQKIRMPY 0 0 0 6 1 ILQKIRDMPY NM_000094_3_COL 0.025 37993.98 60.00 NA
      8 HLA-B4402 LQKIRDMPYMD QKIRDMPYM 1 0 0 0 0 QKIRDMPYM NM_000094_3_COL 0.015 42595.54 90.00 NA
      9 HLA-B4402 QKIRDMPYMDP QKIRDMPYM 0 0 0 0 0 QKIRDMPYM NM_000094_3_COL 0.017 41645.82 85.00 NA
      10 HLA-B4402 KIRDMPYMDPS KDMPYMDPS 0 0 0 1 2 KIRDMPYMDPS NM_000094_3_COL 0.023 39039.53 70.00 NA
      11 HLA-B4402 IRDMPYMDPSX RDMPYMPSX 1 0 0 6 1 RDMPYMDPSX NM_000094_3_COL 0.036 33871.57 41.00 NA
      0 HLA-B4402 PVTGYKVQYTS TGYKVQYTS 2 0 0 0 0 TGYKVQYTS NM_000094_3_COL 0.011 44190.25 95.00 NA
      1 HLA-B4402 VTGYKVQYTSL VTGYQYTSL 0 0 0 4 2 VTGYKVQYTSL NM_000094_3_COL 0.020 40061.36 75.00 NA
      2 HLA-B4402 TGYKVQYTSLT TGYKVYTSL 0 0 0 5 1 TGYKVQYTSL NM_000094_3_COL 0.020 40487.08 75.00 NA
      3 HLA-B4402 GYKVQYTSLTG YVQYTSLTG 1 0 0 1 1 YKVQYTSLTG NM_000094_3_COL 0.017 41521.20 80.00 NA
      4 HLA-B4402 YKVQYTSLTGL YQYTSLTGL 0 0 0 1 2 YKVQYTSLTGL NM_000094_3_COL 0.031 35710.76 49.00 NA
      5 HLA-B4402 KVQYTSLTGLG KVQYTSLTL 0 0 0 8 1 KVQYTSLTGL NM_000094_3_COL 0.029 36392.20 55.00 NA
      6 HLA-B4402 VQYTSLTGLGQ VQYTSLTGL 0 0 0 0 0 VQYTSLTGL NM_000094_3_COL 0.016 42180.50 85.00 NA
      7 HLA-B4402 QYTSLTGLGQP QYTSLTGLG 0 0 0 0 0 QYTSLTGLG NM_000094_3_COL 0.011 44293.17 95.00 NA
      8 HLA-B4402 YTSLTGLGQPL YTSLLGQPL 0 0 0 4 2 YTSLTGLGQPL NM_000094_3_COL 0.034 34547.04 44.00 NA
      9 HLA-B4402 TSLTGLGQPLP SLTGLGQPL 1 0 0 0 0 SLTGLGQPL NM_000094_3_COL 0.024 38475.10 65.00 NA
      10 HLA-B4402 SLTGLGQPLPS SLTGLGQPL 0 0 0 0 0 SLTGLGQPL NM_000094_3_COL 0.026 37575.76 60.00 NA
      11 HLA-B4402 LTGLGQPLPSX LLGQPLPSX 0 0 0 1 2 LTGLGQPLPSX NM_000094_3_COL 0.014 42874.84 90.00 NA
      0 HLA-B4402 FLRLLDLAQEE RLLDLAQEE 2 0 0 0 0 RLLDLAQEE NM_000106_5_CYP 0.014 42841.45 90.00 NA
      1 HLA-B4402 LRLLDLAQEEL RLLDLAQEL 1 0 0 7 1 RLLDLAQEEL NM_000106_5_CYP 0.029 36648.25 55.00 NA
      2 HLA-B4402 RLLDLAQEELK RLLDLAQEL 0 0 0 7 1 RLLDLAQEEL NM_000106_5_CYP 0.029 36350.87 55.00 NA
      3 HLA-B4402 LLDLAQEELKE LLDLAQEEL 0 0 0 0 0 LLDLAQEEL NM_000106_5_CYP 0.013 43487.79 95.00 NA
      4 HLA-B4402 LDLAQEELKEE LDQEELKEE 0 0 0 2 2 LDLAQEELKEE NM_000106_5_CYP 0.008 45629.40 99.00 NA
      5 HLA-B4402 DLAQEELKEES AQEELKEES 2 0 0 0 0 AQEELKEES NM_000106_5_CYP 0.009 45287.57 99.00 NA
      6 HLA-B4402 LAQEELKEESG AEELKEESG 1 0 0 1 1 AQEELKEESG NM_000106_5_CYP 0.013 43568.32 95.00 NA
      7 HLA-B4402 AQEELKEESGF AELKEESGF 0 0 0 1 2 AQEELKEESGF NM_000106_5_CYP 0.231 4113.65 2.50 NA
      8 HLA-B4402 QEELKEESGFL QELKEESGF 0 0 0 1 1 QEELKEESGF NM_000106_5_CYP 0.123 13202.71 6.00 NA
      9 HLA-B4402 EELKEESGFLR EELKEESGF 0 0 0 0 0 EELKEESGF NM_000106_5_CYP 0.076 21904.46 13.00 NA
      10 HLA-B4402 ELKEESGFLRE ELKEESGFL 0 0 0 0 0 ELKEESGFL NM_000106_5_CYP 0.030 36301.74 55.00 NA
      11 HLA-B4402 LKEESGFLREX KEESFLREX 1 0 0 4 1 KEESGFLREX NM_000106_5_CYP 0.060 26205.35 19.00 NA

      【讨论】：

        猜你喜欢
        • 2021-06-15
        • 2020-12-19
        • 2019-06-25
        • 1970-01-01
        • 2013-05-29
        • 2013-04-15
        • 1970-01-01
        • 1970-01-01
        • 2017-06-18
        相关资源
        最近更新 更多
        热门标签
        Java Python linux javascript Mysql C# Docker 算法 前端 SpringBoot Redis Vue spring 设计模式 .net core .net kubernetes c++ 数据库 数据结构 大数据 js 机器学习 微服务 Android Go 程序员 面试 JVM ASP.net core 云原生 人工智能 后端 PHP git CSS golang k8s Nginx Django mybatis 深度学习 多线程 React 架构 devops 爬虫 云计算 Spring Boot LeetCode