How to filter a dataframe in R but also get the row before and after the filter

Now my problem is that the values are not always matching so I need to also see the line before and after of the dataframe after the filter (basically one row around the filter) so as to make sure Im not missing something. I tried lag and lead and data.table shift but there is always some unnecessary data output that I cant get rid of

I have a file indicating genomic distance that looks like this

I want to filter based on chr and pos and output the slice.
filter(data, chr == chromosome & pos >= start_pos & pos <= end_pos)

Given that your data seems insufficient to reflect the issue adequately (as per comments), here's some toy data and a generic solution to your problem (which, BTW, is a frequent problem or task and where there is suprisingly not yet a neat function available):

Data:

df <- data.frame(
  x = c("B","A","A","A","B","C","B", "A", "C", "A"),
  y = c(1,2,1,3,1,2,1,5,1,2)
)

Task:

Suppose I need to filter all rows where x == "A" & y > 2 PLUS the immediately surrounding rows (above and below).

Solution:

The solution I propose involves writing a function that:

• gets the indices of the filtered rows PLUS those of the surrounding rows:

Function:

row_sequence <- function(value1, value2) {
  inds <- which(value1 == "A" & value2 > 2)  
  sort(unique(c(inds-1, inds, inds + 1)))
}

Now just input the function row_sequence into a call to slice:

Implementation:

library(dplyr)
df %>% 
  slice(row_sequence(x, y))
  x y
1 A 1
2 A 3   # <- filtered
3 B 1
4 B 1
5 A 5   # <- filtered
6 C 1

You could first add a couple of filtering markers to your dataset, here filter_mark identifies filtered records and window_mark leading/lagging rows. During actual subsetting you either include or exclude those extra rows:

library(dplyr)
chromosome <- "chr8"
start_pos  <- 166818 + 1
end_pos    <- 181076 - 1

df_ <- df_ %>% 
  mutate(filter_mark = chr == chromosome & pos >= start_pos & pos <= end_pos,
         window_mark = lag(filter_mark) | lead(filter_mark))

df_ %>% filter(filter_mark | window_mark)
#> # A tibble: 3 × 6
#>   chr   snp           pos cM    filter_mark window_mark
#>   <chr> <chr>       <dbl> <lgl> <lgl>       <lgl>      
#> 1 chr8  rs2003497  166818 NA    FALSE       TRUE       
#> 2 chr8  rs10488368 180568 NA    TRUE        FALSE      
#> 3 chr8  rs10488369 181076 NA    FALSE       TRUE

Input data:

df_ <- readr::read_table("
chr snp pos cM
chr8    rs2003497   166818  NA
chr8    rs10488368  180568  NA
chr8    rs10488369  181076  NA")

^{Created on 2023-05-28 with reprex v2.0.2}