overlap stats

gistfile1.txt

with combined 3-colbed + 4th col. id
```r
library(data.table)

y = data.table(chr=c("Chr1", "Chr1", "Chr1"), start=c(1, 15,1), 
               end=c(4, 18, 55), id=letters[1:3])
setkey(y, chr, start, end)

dt <- foverlaps(y, y, type="any")
```

then get overlap stats
```r
comn_df <- . %>% 
    as.data.frame() %>% 
    filter(id != i.id) %>% 
    rowwise() %>% 
    mutate(len_l    = end - start, 
           len_r    = i.end - i.start,
           len_i    = min(end, i.end) - max(start, i.start),
           frac_i_l = len_i / len_l,
           frac_i_r = len_i / len_r) %>% 
    arrange(chr,start,end)

```

quick visual parse

library(dplyr)
library(ggvis)

y = data.table(chr=c("Chr1", "Chr1", "Chr1"), start=c(1, 15,1), 
               end=c(4, 18, 55), id=letters[1:3])

as.data.frame(y) %>% 
    tbl_df() %>% 
    ggvis() %>% 
    layer_rects(y=~id,x=~start,x2=~end,height=band())