Quiz 3

Using small_brca as your tibble, write code that reports the gene with the highest count in each tumor sample.

library(tidyverse)

## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──

## ✓ ggplot2 3.3.2     ✓ purrr   0.3.4
## ✓ tibble  3.0.4     ✓ dplyr   1.0.2
## ✓ tidyr   1.1.2     ✓ stringr 1.4.0
## ✓ readr   1.4.0     ✓ forcats 0.5.0

## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag()    masks stats::lag()

load("/cloud/project/data/small_brca.Rdata")

small_brca %>%
  filter(tumor == TRUE) %>%
  select(ANLN:TMEM45B) %>%
  rowwise() %>%
  summarise(highest.gene = names(.)[which.max(c_across(ANLN:TMEM45B))],
            max.value = max(c_across(ANLN:TMEM45B)), 
            .groups = 'drop')

## # A tibble: 1,102 x 2
##    highest.gene max.value
##    <chr>            <dbl>
##  1 MMP11           108677
##  2 MMP11            89135
##  3 SLC39A6         138393
##  4 KRT5            102256
##  5 ESR1            133812
##  6 ERBB2           811281
##  7 SLC39A6          70814
##  8 KRT14           198790
##  9 SLC39A6          53480
## 10 SLC39A6         305439
## # … with 1,092 more rows