10.2 Rapid processing of experimental data

In biological experiments, it is often necessary to perform rapid processing and analysis of experimental data (e.g., counting mouse weight, calculating QPCR results, etc.). Complex statistical analysis can be done quickly by datapasta and EasyMultiProfiler packages.

🏷️Example： Quick calculation of mouse weighing data.

Step1：Copy the data in an excel file and execute the command below in R.

datapasta::tribble_paste()

Step2：In the Rstudio, the copied data has been automatically organized into tribble format.

Step3：Easily import the data into the MAE object.

coldata <- df |> dplyr::select(Num,cage,week,Group) |>
  tibble::column_to_rownames('Num')

assay_data <- df |>dplyr::select(Num,weight) |>
  tibble::column_to_rownames('Num') |> t() |> as.data.frame() |>
  tibble::rownames_to_column('feature')

MAE <- EMP_easy_import(data = assay_data,coldata = coldata,type = 'normal')

Step4：Perform data analysis.

Observe the approximate distribution of mouse body weight.

MAE |>
  EMP_assay_extract('experiment') |>
  EMP_structure_plot(estimate_group='Group')

Compare the body weight in different groups.

MAE |>
  EMP_assay_extract('experiment') |>
  EMP_boxplot(estimate_group='Group',method='t.test')

MAE |>
  EMP_assay_extract('experiment') |>
  EMP_boxplot(estimate_group='cage',method='t.test')