EX5_ANSWERS_RU_tidyverse_readr

 

These exercises cover the sections of Data wrangling with tidy.

All files can be found in the “dataset” directory.

 

Exercise 5

 

• Read in count data as different data types. What happens when we extract the vector of these counts?

ANSWERS

Load in dataset and packages

library(tidyverse)

Answer

untidy_counts_test <- read_csv("dataset/hemato_rnaseq_counts.csv", col_types = cols(
    ENTREZ = col_character(),
    CD34_1 = col_integer(),
    ORTHO_1 = col_character(),
    CD34_2 = col_factor(),
    ORTHO_2 = col_logical()
  ))

## Warning: 62 parsing failures.
## row     col           expected actual                               file
##   2 ORTHO_2 1/0/T/F/TRUE/FALSE   39   'dataset/hemato_rnaseq_counts.csv'
##   3 ORTHO_2 1/0/T/F/TRUE/FALSE   86   'dataset/hemato_rnaseq_counts.csv'
##   5 ORTHO_2 1/0/T/F/TRUE/FALSE   16   'dataset/hemato_rnaseq_counts.csv'
##   8 ORTHO_2 1/0/T/F/TRUE/FALSE   4051 'dataset/hemato_rnaseq_counts.csv'
##  10 ORTHO_2 1/0/T/F/TRUE/FALSE   1114 'dataset/hemato_rnaseq_counts.csv'
## ... ....... .................. ...... ..................................
## See problems(...) for more details.

untidy_counts_test$CD34_1 %>% head(n=8)

## [1]   204 15586   842     0   123     1   380   572

untidy_counts_test$ORTHO_1 %>% head(n=8)

## [1] "0"    "479"  "355"  "0"    "291"  "1"    "3"    "2225"

untidy_counts_test$CD34_2 %>% head(n=8)

## [1] 103   10476 1188  0     139   0     177   597  
## 82 Levels: 103 10476 1188 0 139 177 597 1 46 15 4 51 24 833 2741 148 138 4970 2576 1767 ... 3053

untidy_counts_test$ORTHO_2 %>% head(n=8)

## [1] FALSE    NA    NA FALSE    NA FALSE FALSE    NA