如果行在第二个表的列中包含值，则过滤表以排除行

Question

I have got one main table with over 608,000 rows (the first 7 rows are depicted below). These correspond to locations in the genome along with one (or two identifiers) given to them by Affymetrix (and dbSNP).

Affy SNP ID dbSNP RS ID Chromosome  Chromosome Start
Affx-26018273   rs10056215  5   163542505

I then have another table with only 46 rows. I need to remove the rows from the main table if they have both the Chromosome and Chromosome Start values found in one of the 46 rows in the second table. Here is the second table; it does not have the Affymetrix/dbSNP identifiers.

1   5641055

How can I filter out these records?

Answer 1

Using R , you can remove all the rows from Tab1 that have in the last column a number that appears in the second column of the 46-row table Tab2 with

 Tab1 <- Tab1[-which(Tab1[,ncol(Tab1)] %in% Tab2[,2]),]

Hope this helps.

Answer 2

You could use the anti_join function from the dplyr package, or that package's filter function.

Say your data.frame was the built-in mtcars and you wanted to filter out cars with cylinder values from the following data.frame, ie, with 4 or 6 cylinders:

dontuse <- data.frame(cyl = c(4,6), blah = c(1,2))

You could run:

anti_join(mtcars, dontuse)

or

mtcars %>%
  filter(! cyl %in% dontuse$cyl)

Both of these return rows where cyl is not 4 or 6.

    mpg cyl  disp  hp drat    wt  qsec vs am gear carb
1  18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2
2  14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4
3  16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3
4  17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3
5  15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3
6  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4
7  10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4
8  14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4
9  15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2
10 15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2
11 13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4
12 19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2
13 15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4
14 15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8