EX10_ANSWERS_RU_tidyverse_forcats

 

These exercises cover the sections of Data wrangling with tidy.

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

 

Exercise 10

 

1. Create new categorical variable for the counts dataframe (tidy_counts_expressed_norm) based on whether a gene is short (0-3000), medium (0-6000) or long (6000+)
2. Ensure categorical variable is a factor which is ordered from long, medium then short
3. Draw a boxplot of TPMs comparing between our new groups

ANSWERS

Load in dataset and packages

load(file='dataset/my_tidy.Rdata')
library(tidyverse)

Answer 1

tidy_counts_expressed_norm %>%
  mutate(length_cat=if_else(LENGTH<3000, 'short', if_else(LENGTH>6000, 'long', 'medium')))

## # A tibble: 376 x 12
## # Groups:   Sample [4]
##    ENTREZ Sample  CellType Rep   counts count_total     CPM SYMBOL CHR   LENGTH    TPM length_cat
##    <chr>  <chr>   <chr>    <chr>  <int>       <int>   <dbl> <chr>  <chr>  <int>  <dbl> <chr>     
##  1 350    CD34_1  CD34     1        204         307   1362. APOH   chr17   1201  3069. short     
##  2 350    ORTHO_1 ORTHO    1          0         307      0  APOH   chr17   1201     0  short     
##  3 350    CD34_2  CD34     2        103         307    975. APOH   chr17   1201  2027. short     
##  4 350    ORTHO_2 ORTHO    2          0         307      0  APOH   chr17   1201     0  short     
##  5 351    CD34_1  CD34     1      15586       26580 104068. APP    chr21   4480 62851. medium    
##  6 351    ORTHO_1 ORTHO    1        479       26580   5825. APP    chr21   4480  3333. medium    
##  7 351    CD34_2  CD34     2      10476       26580  99125. APP    chr21   4480 55281. medium    
##  8 351    ORTHO_2 ORTHO    2         39       26580   1185. APP    chr21   4480   703. medium    
##  9 353    CD34_1  CD34     1        842        2471   5622. APRT   chr16    807 18849. short     
## 10 353    ORTHO_1 ORTHO    1        355        2471   4317. APRT   chr16    807 13711. short     
## # … with 366 more rows

Answer 2

tidy_counts_expressed_norm %>%
  mutate(length_cat=if_else(LENGTH<3000, 'short', if_else(LENGTH>6000, 'long', 'medium'))) %>%
  mutate(length_cat=as_factor(length_cat)) %>%
  mutate(length_cat=fct_relevel(length_cat,levels=c('long', 'medium','short')))

## Warning: Outer names are only allowed for unnamed scalar atomic inputs

## Warning: Outer names are only allowed for unnamed scalar atomic inputs

## Warning: Outer names are only allowed for unnamed scalar atomic inputs

## Warning: Outer names are only allowed for unnamed scalar atomic inputs

## # A tibble: 376 x 12
## # Groups:   Sample [4]
##    ENTREZ Sample  CellType Rep   counts count_total     CPM SYMBOL CHR   LENGTH    TPM length_cat
##    <chr>  <chr>   <chr>    <chr>  <int>       <int>   <dbl> <chr>  <chr>  <int>  <dbl> <fct>     
##  1 350    CD34_1  CD34     1        204         307   1362. APOH   chr17   1201  3069. short     
##  2 350    ORTHO_1 ORTHO    1          0         307      0  APOH   chr17   1201     0  short     
##  3 350    CD34_2  CD34     2        103         307    975. APOH   chr17   1201  2027. short     
##  4 350    ORTHO_2 ORTHO    2          0         307      0  APOH   chr17   1201     0  short     
##  5 351    CD34_1  CD34     1      15586       26580 104068. APP    chr21   4480 62851. medium    
##  6 351    ORTHO_1 ORTHO    1        479       26580   5825. APP    chr21   4480  3333. medium    
##  7 351    CD34_2  CD34     2      10476       26580  99125. APP    chr21   4480 55281. medium    
##  8 351    ORTHO_2 ORTHO    2         39       26580   1185. APP    chr21   4480   703. medium    
##  9 353    CD34_1  CD34     1        842        2471   5622. APRT   chr16    807 18849. short     
## 10 353    ORTHO_1 ORTHO    1        355        2471   4317. APRT   chr16    807 13711. short     
## # … with 366 more rows

Answer 3

tidy_counts_expressed_norm %>%
  mutate(length_cat=if_else(LENGTH<3000, 'short', if_else(LENGTH>6000, 'long', 'medium'))) %>%
  mutate(length_cat=as_factor(length_cat)) %>%
  mutate(length_cat=fct_relevel(length_cat,levels=c('long', 'medium','short')))  %>% 
  ggplot(aes(x=length_cat, y=TPM)) + 
  geom_boxplot() + 
  scale_y_continuous(trans='log2')

## Warning: Outer names are only allowed for unnamed scalar atomic inputs

## Warning: Outer names are only allowed for unnamed scalar atomic inputs

## Warning: Outer names are only allowed for unnamed scalar atomic inputs

## Warning: Outer names are only allowed for unnamed scalar atomic inputs

## Warning: Transformation introduced infinite values in continuous y-axis

## Warning: Removed 46 rows containing non-finite values (stat_boxplot).