gistfile1.txt

``` r
library(tidyverse)

# How abundant is Xrn1?

tab <- readr::read_tsv("https://yeastgfp.yeastgenome.org/allOrfData.txt")
#> Warning: Missing column names filled in: 'X33' [33]
#> Parsed with column specification:
#> cols(
#>   .default = col_logical(),
#>   orfid = col_integer(),
#>   yORF = col_character(),
#>   `gene name` = col_character(),
#>   `GFP tagged?` = col_character(),
#>   `GFP visualized?` = col_character(),
#>   `TAP visualized?` = col_character(),
#>   abundance = col_character(),
#>   error = col_double(),
#>   `localization summary` = col_character(),
#>   X33 = col_character()
#> )
#> See spec(...) for full column specifications.
#> Warning in rbind(names(probs), probs_f): number of columns of result is not
#> a multiple of vector length (arg 1)
#> Warning: 6234 parsing failures.
#> row # A tibble: 5 x 5 col     row col   expected   actual     file                                   expected   <int> <chr> <chr>      <chr>      <chr>                                  actual 1     1 <NA>  33 columns 34 columns 'https://yeastgfp.yeastgenome.org/all… file 2     2 <NA>  33 columns 34 columns 'https://yeastgfp.yeastgenome.org/all… row 3     3 <NA>  33 columns 34 columns 'https://yeastgfp.yeastgenome.org/all… col 4     4 <NA>  33 columns 34 columns 'https://yeastgfp.yeastgenome.org/all… expected 5     5 <NA>  33 columns 34 columns 'https://yeastgfp.yeastgenome.org/all…
#> ... ................. ... .......................................................................... ........ .......................................................................... ...... .......................................................................... .... .......................................................................... ... .......................................................................... ... .......................................................................... ........ ..........................................................................
#> See problems(...) for more details.

all <- tab %>%
  select(yORF, abundance) %>%
  mutate(abundance = as.numeric(abundance)) %>%
  na.omit()
#> Warning in evalq(as.numeric(abundance), <environment>): NAs introduced by
#> coercion

all
#> # A tibble: 3,868 x 2
#>    yORF    abundance
#>    <chr>       <dbl>
#>  1 YAL001C       125
#>  2 YAL002W       736
#>  3 YAL005C    269000
#>  4 YAL007C     26300
#>  5 YAL008W      1920
#>  6 YAL009W       861
#>  7 YAL010C       768
#>  8 YAL011W      1380
#>  9 YAL012W     38300
#> 10 YAL016W     16900
#> # ... with 3,858 more rows

# Histogram of protein abundances in yeast
ggplot(all, aes(x = log10(abundance))) + geom_histogram()
#> `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
```

![](https://i.imgur.com/PDAoo1q.png)

``` r

# Xrn1 is YGL173C
all %>% 
  arrange(desc(abundance)) %>%
  mutate(rank = row_number()) %>%
  filter(yORF == "YGL173C")
#> # A tibble: 1 x 3
#>   yORF    abundance  rank
#>   <chr>       <dbl> <int>
#> 1 YGL173C     11700   552
```

Created on 2018-07-14 by the [reprex package](http://reprex.tidyverse.org) (v0.2.0).