Data reshaping

This lesson will be about data reshaping and data presentation in tables. We will read data, transform and finally present them in customable tables.

Cooked product

Virus detection in qRT-PCR
Sample	Primers
	T41-5	T41-6a	T41-7	T41-8
T1	0	0	0	0
T2	0	0	0	0
T3	0	0	0	0
T4	0	0	0	0
T5	0	0	0	1
T6	0	0	0	0
T7	0	0	0	0
T8	0	0	0	0
T9	1	0	0	1
T10	0	0	1	0
T11	0	0	0	0
T12	0	0	0	0
a Not present in any sample

Ingredients

1. Tidy data

2. select, mutate, filter, group by and summarise (dplyr package)

3. pivot longer and pivot wider (tidyr package)

4. gt package

Recipe

################################################################################
# Scritp for R intermidiate course
# Data reshaping lesson
################################################################################

# LOAD LIBRARIES
library(tidyverse)
library(gt)

# READ DATA IN
raw  <- read_csv("material/raw.csv") %>%
            select(Sample, Cq) %>%
            mutate(Cq = str_replace(.$Cq, ",", ".") %>% as.numeric(),
                   Sample = str_c("T", Sample)) %>%
            separate(Sample, sep = "-", extra = "merge", c("Sample", "Primer")) 


df <- raw %>%
    group_by(Sample, Primer) %>%
    summarise_at(vars(Cq), list(Max = max, Min = min), na.rm = FALSE) %>%
    mutate(Exp = case_when(
                          Max < 30 & Min < 30 ~ 1,
                          TRUE ~ 0),
           Max = replace(Max, is.infinite(Max), 40),
           Min = replace(Min, is.infinite(Min), 40))

df2 <- df %>%
    pivot_wider(id_cols = -(Max:Min),
                names_from = Primer,
                values_from = Exp) %>%
    mutate(order = as.numeric(str_remove(Sample, "T"))) %>%
    arrange(order) %>%
    select(-order) %>%
    ungroup

tab <- df2 %>%
    mutate(pippo = rowSums(select(., -Sample))) %>%
    gt() %>%
    tab_header(title = "Virus detection in qRT-PCR") %>%
    tab_spanner(
    label = "Primers",
    columns = vars(`T41-5`, `T41-6`, `T41-7`, `T41-8`)
    ) %>%
    tab_options(
    column_labels.font.size = "smaller",
    table.font.size = "smaller",
    data_row.padding = px(3)
    ) %>%
    tab_footnote(
    footnote = "Not present in any sample",
    locations = cells_column_labels(columns = vars(`T41-6`))
    ) %>%
    opt_footnote_marks(marks = "letters") %>%
    tab_style(
    style = list(
      cell_fill(color = "#F9E3D6")
      ),
    locations = cells_body(
      rows = pippo > 0)
    ) %>% 
    cols_hide(
              columns = vars(pippo)
    )