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select rows with specific columns and values between two data tables ?

I have two sorted data tables (A and B), in table A, 3 first columns are genomic coordinates. I like to extract some specific rows from A table but based on some common columns/values of B table.

For example: First, I would like to match column 6 of A table and column 1 of B table, then if there is a 1 value in the third column of B table, select those rows (from A table) which have the same value (first match) in the fourth column of A and B tables and the coordinates before. But if there is a - 1 value in the third column of B table, select those rows (from A table) which have the same value (last match) in the fourth column of A and B tables and the coordinates after.

Input A:

17  50094737    50094898    1   ENST00000007708 ENSG00000005882 
17  50096132    50096286    2   ENST00000007708 ENSG00000005882 
17  50097423    50097564    3   ENST00000007708,ENST00000503176,ENST00000614357 ENSG00000005882
17  50105371    50105442    3   ENST00000007708,ENST00000503176,ENST00000614357 ENSG00000005882
17  50109957    50111058    1   ENST00000007708 ENSG00000005882 
17  50109957    50111368    2   ENST00000614357 ENSG00000005882 
17  50109957    50112152    1   ENST00000503176 ENSG00000005882 
8   22987417    22987563    2   ENST00000519685 ENSG00000008853 
8   22999579    23000105    1   ENST00000251822 ENSG00000008853 
8   23004425    23004626    2   ENST00000251822,ENST00000519685 ENSG00000008853
8   23005372    23005475    2   ENST00000251822,ENST00000519685 ENSG00000008853
8   23006728    23007746    2   ENST00000251822,ENST00000519685 ENSG00000008853
8   23015638    23015743    2   ENST00000251822,ENST00000519685 ENSG00000008853
8   23017252    23020199    1   ENST00000251822 ENSG00000008853 
X   119539386   119539789   1   ENST00000644802 ENSG00000018610 
X   119541328   119541420   2   ENST00000320339,ENST00000644802 ENSG00000018610
X   119544353   119544491   2   ENST00000320339,ENST00000644802 ENSG00000018610
X   119560268   119560385   2   ENST00000320339,ENST00000644802 ENSG00000018610
X   119565232   119565401   1   ENST00000644802 ENSG00000018610 
10  14518560    14521306    1   ENST00000181796 ENSG00000065809 
10  14521158    14521306    1   ENST00000479731 ENSG00000065809 
10  14521869    14522019    8    ENST00000181796,ENST00000378458,ENST00000378467,ENST00000378470,ENST00000468747,ENST00000478076,ENST00000479731,ENST00000622567    ENSG00000065809
10  14530332    14530515    8    ENST00000181796,ENST00000378458,ENST00000378467,ENST00000378470,ENST00000468747,ENST00000478076,ENST00000479731,ENST00000622567    ENSG00000065809
10  14553322    14553387    2   ENST00000378458,ENST00000378467 ENSG00000065809
10  14571763    14572189    2   ENST00000378458,ENST00000622567 ENSG00000065809
10  14572229    14572314    1   ENST00000479731 ENSG00000065809 
10  14667634    14667691    1   ENST00000181796 ENSG00000065809 
10  14774253    14774897    1   ENST00000181796 ENSG00000065809

Input B: 

ENSG00000005882 PDK2     1  3
ENSG00000008853 RHOBTB2  1  2
ENSG00000018610 CXorf56 -1  2
ENSG00000065809 FAM107B -1  8

Desire Output: 

17  50094737    50094898    1   ENST00000007708 ENSG00000005882 
17  50096132    50096286    2   ENST00000007708 ENSG00000005882 
17  50097423    50097564    3   ENST00000007708,ENST00000503176,ENST00000614357 ENSG00000005882
8   22987417    22987563    2   ENST00000519685 ENSG00000008853 
X   119560268   119560385   2   ENST00000320339,ENST00000644802 ENSG00000018610
X   119565232   119565401   1   ENST00000644802 ENSG00000018610 
10  14530332    14530515    8   ENST00000181796,ENST00000378458,ENST00000378467,ENST00000378470,ENST00000468747,ENST00000478076,ENST00000479731,ENST00000622567 ENSG00000065809
10  14553322    14553387    2   ENST00000378458,ENST00000378467 ENSG00000065809
10  14571763    14572189    2   ENST00000378458,ENST00000622567 ENSG00000065809
10  14572229    14572314    1   ENST00000479731 ENSG00000065809 
10  14667634    14667691    1   ENST00000181796 ENSG00000065809 
10  14774253    14774897    1   ENST00000181796 ENSG00000065809

Thanks a lot in advance for any possible solution!

r linux if-statement dplyr ifelse
• 2,806 views • link
updated by Chirag Parsania Chirag Parsania • written by star star

Hi star, show us what you have tried, now it is like you want us to do your job...

• 0 views • link
written by Benn Benn

I have tried with If else but, I do not know how to select first and the last match for 1 and -1 value or the coordinates after and before them.

It the cod that I have tried but it is not what I want:

if (A$V6 %in% B$V1 & B$V3 == '1') {
  A[which(A$V4 == B$V4),] & A[which(A$V4 < B$V4),]
} else if  (A$V6 %in% B$V1 & B$V3 == '- 1') {
  A[which(A$V4 == B$V4),] & A[which(A$V4 > B$V4),]
} else {
  print ("NA")
}
• 0 views • link
written by star star

I think learning some basic tricks with dplyr would be useful for you.

NB. There seems to be commas in your first table, but not consistent. R might get troubles with that.

• 0 views • link
written by Benn Benn 
dfa = A 
dfb = B  
dfa[which(dfa$V6 == dfb$V1 | (dfb$V3 == 1 & dfb$V4 == dfa$V4) | (dfb$V3 == -1 & dfb$V4 == dfa$V4)),]

I get a slightly different output than your desired one, but maybe this helps you already

• 0 views • link
updated by Ram Ram • written by sim.j.baum sim.j.baum

2 answers 

library(tidyverse)

NOTE Due to character limit i removed chr 8 and 10 from input data.

get input_A in R

   ## get input_A in R
input_A <- tibble::tribble(
        ~col_1,    ~col_2,      ~col_3, ~col_4,                                                                                                                            ~col_5,            ~col_6,
        "17",  50094737,  50094898,      1,                                                                                                                 "ENST00000007708", "ENSG00000005882",
        "17",  50096132,  50096286,      2,                                                                                                                 "ENST00000007708", "ENSG00000005882",
        "17",  50097423,  50097564,      3,                                                                                 "ENST00000007708,ENST00000503176,ENST00000614357", "ENSG00000005882",
        "17",  50105371,  50105442,      3,                                                                                 "ENST00000007708,ENST00000503176,ENST00000614357", "ENSG00000005882",
        "17",  50109957,  50111058,      1,                                                                                                                 "ENST00000007708", "ENSG00000005882",
        "17",  50109957,  50111368,      2,                                                                                                                 "ENST00000614357", "ENSG00000005882",
        "17",  50109957,  50112152,      1,                                                                                                                 "ENST00000503176", "ENSG00000005882",
         "X", 119539386, 119539789,      1,                                                                                                                 "ENST00000644802", "ENSG00000018610",
         "X", 119541328, 119541420,      2,                                                                                                 "ENST00000320339,ENST00000644802", "ENSG00000018610",
         "X", 119544353, 119544491,      2,                                                                                                 "ENST00000320339,ENST00000644802", "ENSG00000018610",
         "X", 119560268, 119560385,      2,                                                                                                 "ENST00000320339,ENST00000644802", "ENSG00000018610",
         "X", 119565232, 119565401,      1,                                                                                                                 "ENST00000644802", "ENSG00000018610",
        )%>% 
        rename_all(~(paste(. , "A"  , sep = "_")))

get input_B in R

input_B  <- tibble::tribble(
                   ~col_1,    ~col_2, ~col_3, ~col_4,
        "ENSG00000005882",    "PDK2",      1,      3,
        "ENSG00000008853", "RHOBTB2",      1,      2,
        "ENSG00000018610", "CXorf56",     -1,      2,
        "ENSG00000065809", "FAM107B",     -1,      8
        ) %>% 
        rename_all(~(paste(. , "B"  , sep = "_")))

if there is a 1 value in the 3rd column of B table

out_1  <- input_A %>% left_join(input_B ,  by = c( "col_6_A" = "col_1_B")) %>% 
        filter(col_3_B == 1) %>% ## value 1 in  third column of B table
        filter(col_4_A == col_4_B) ##  rows (from A table) which have the same value in the fourth column of A and B tables

out_1

if there is a -1 value in the 3rd column of B table

out_2  <- input_A %>% left_join(input_B ,  by = c( "col_6_A" = "col_1_B")) %>% 
        filter(col_3_B == -1) %>% ##  value -1 in  third column of B table
        filter(col_4_A == col_4_B) ##   rows (from A table) which have the same value in the fourth column of A and B tables
out_2

What is don't get here is

first match

and

last match

stuff. However, I believe, out_1 and out_2 should be enough to get desire rows and columns.

• 0 views • link
written by Chirag Parsania Chirag Parsania

Read in your input A:

dfA <- "17  50094737    50094898    1   ENST00000007708 ENSG00000005882 
17  50096132    50096286    2   ENST00000007708 ENSG00000005882 
17  50097423    50097564    3   ENST00000007708,ENST00000503176,ENST00000614357 ENSG00000005882
17  50105371    50105442    3   ENST00000007708,ENST00000503176,ENST00000614357 ENSG00000005882
17  50109957    50111058    1   ENST00000007708 ENSG00000005882 
17  50109957    50111368    2   ENST00000614357 ENSG00000005882 
17  50109957    50112152    1   ENST00000503176 ENSG00000005882 
8   22987417    22987563    2   ENST00000519685 ENSG00000008853 
8   22999579    23000105    1   ENST00000251822 ENSG00000008853 
8   23004425    23004626    2   ENST00000251822,ENST00000519685 ENSG00000008853
8   23005372    23005475    2   ENST00000251822,ENST00000519685 ENSG00000008853
8   23006728    23007746    2   ENST00000251822,ENST00000519685 ENSG00000008853
8   23015638    23015743    2   ENST00000251822,ENST00000519685 ENSG00000008853
8   23017252    23020199    1   ENST00000251822 ENSG00000008853 
X   119539386   119539789   1   ENST00000644802 ENSG00000018610 
X   119541328   119541420   2   ENST00000320339,ENST00000644802 ENSG00000018610
X   119544353   119544491   2   ENST00000320339,ENST00000644802 ENSG00000018610
X   119560268   119560385   2   ENST00000320339,ENST00000644802 ENSG00000018610
X   119565232   119565401   1   ENST00000644802 ENSG00000018610 
10  14518560    14521306    1   ENST00000181796 ENSG00000065809 
10  14521158    14521306    1   ENST00000479731 ENSG00000065809 
10  14521869    14522019    8    ENST00000181796,ENST00000378458,ENST00000378467,ENST00000378470,ENST00000468747,ENST00000478076,ENST00000479731,ENST00000622567    ENSG00000065809
10  14530332    14530515    8    ENST00000181796,ENST00000378458,ENST00000378467,ENST00000378470,ENST00000468747,ENST00000478076,ENST00000479731,ENST00000622567    ENSG00000065809
10  14553322    14553387    2   ENST00000378458,ENST00000378467 ENSG00000065809
10  14571763    14572189    2   ENST00000378458,ENST00000622567 ENSG00000065809
10  14572229    14572314    1   ENST00000479731 ENSG00000065809 
10  14667634    14667691    1   ENST00000181796 ENSG00000065809 
10  14774253    14774897    1   ENST00000181796 ENSG00000065809"
dfA <- unlist(strsplit(dfA, split = "\n"))

Read in your input B

dfB <- "ENSG00000005882 PDK2     1  3
ENSG00000008853 RHOBTB2  1  2
ENSG00000018610 CXorf56 -1  2
ENSG00000065809 FAM107B -1  8"
dfB <- unlist(strsplit(dfB, split = "\n"))
dfB_sub <- as.data.frame(unlist(strsplit(dfB, split = " ")))

Create here the strings you are interested in and format it:

dfB_sub_ENS <- unlist(dfB_sub[grep(dfB_sub$`unlist(strsplit(dfB, split = " "))`, pattern = "ENSG"),])

dfB_sub_ENS <- as.character(droplevels(dfB_sub_ENS))

extract your data from input A which matches the categories from input B:

dfA[grep(x = dfA, pattern = paste((dfB_sub_ENS), collapse = "|"))]

output (shortened) (further formating may be required):

 [1] "17  50094737    50094898    1   ENST00000007708 ENSG00000005882 "                                                                                                                   
 [2] "17  50096132    50096286    2   ENST00000007708 ENSG00000005882 "                                                                                                                   
 [3] "17  50097423    50097564    3   ENST00000007708,ENST00000503176,ENST00000614357 ENSG00000005882"                                                                                    
 [4] "17  50105371    50105442    3   ENST00000007708,ENST00000503176,ENST00000614357 ENSG00000005882"                                                                                    
 [5] "17  50109957    50111058    1   ENST00000007708 ENSG00000005882 "                                                                                                                   
 [6] "17  50109957    50111368    2   ENST00000614357 ENSG00000005882 "                                                                                                                   
 [7] "17  50109957    50112152    1   ENST00000503176 ENSG00000005882 "                                                                                                                   
...                                                                                                                
[27] "10  14667634    14667691    1   ENST00000181796 ENSG00000065809 "                                                                                                                   
[28] "10  14774253    14774897    1   ENST00000181796 ENSG00000065809"
• 0 views • link
updated by Ram Ram • written by sim.j.baum sim.j.baum

The way to get a data.frame from text is read.table(text = "...", ...), not what you're doing. Column names like

dfB_sub$`unlist(strsplit(dfB, split = " "))`

look so crazy! Please clean up your code.

• 0 views • link
written by Ram Ram

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