Takes a matrix where each row is a time point and each column is a well and converts it to a DataFrame containing a column for the well, a column for the row, a column for the column, a column for the time and a column for the values.
well_mat_frames_to_df(mat, value = "value")A matrix where each column is a well and each row is a frame from a multi time point experiment.
Name for the column containing the values in the resulting data frame.
a tibble
df_list <- lapply(1:10, function(x) {
df <- wellr::well_plate()
df$value <- rnorm(96)
df$frame <- x
df
})
df_frames <- do.call(rbind, df_list)
# convert the data frame to multi-frame matrix
mat <- well_df_to_mat_frames(
data = df_frames,
value = value,
frame = frame,
well = well
)
head(mat[, 1:14])
#> A01 A02 A03 A04 A05 A06 A07
#> 1 -0.99245858 -1.0545187 -0.4161150 0.5625075 -0.3367150 -1.3768313 -2.1292973
#> 2 -0.02757795 0.6607691 0.9821496 0.6420557 -0.2158402 0.8831702 0.3376460
#> 3 2.22284516 -0.8234090 0.2421807 -0.8905326 0.6211323 0.6714203 -1.5745748
#> 4 0.15550390 0.4370337 -0.9379269 -0.1165375 -1.2840265 1.2300224 -0.1963194
#> 5 -0.86911632 0.3723881 1.5058585 -0.9419748 -1.3000924 1.6454679 0.9150601
#> 6 -1.17448945 -1.6467491 -1.0658512 1.1158279 -0.3767695 -0.1829260 1.0786365
#> A08 A09 A10 A11 A12 B01
#> 1 1.0245716 -0.2805163 0.2661688 1.2124483 1.7631306 -0.99593086
#> 2 -0.6591855 0.5748366 0.5284032 -0.4453630 2.0258461 0.42011400
#> 3 -0.3863044 -0.2056768 -0.5793881 1.1386675 0.4276188 -0.06286163
#> 4 -0.2424989 0.2348805 0.9421994 0.1905235 -0.5664793 -0.08013185
#> 5 0.2205932 0.1106283 -0.7063614 -1.3663936 -0.8338353 -0.03228341
#> 6 -1.4810900 0.2742022 -1.2754021 -1.2981026 0.3982592 -0.71898093
#> B02
#> 1 -2.03102701
#> 2 2.75076475
#> 3 1.51366972
#> 4 0.03398894
#> 5 0.74079278
#> 6 -1.27080818
# convert the matrix back to a dataframe
well_mat_frames_to_df(mat)
#> # A tibble: 960 × 5
#> frame well value row col
#> <chr> <chr> <dbl> <dbl> <dbl>
#> 1 1 A01 -0.992 1 1
#> 2 1 A02 -1.05 1 2
#> 3 1 A03 -0.416 1 3
#> 4 1 A04 0.563 1 4
#> 5 1 A05 -0.337 1 5
#> 6 1 A06 -1.38 1 6
#> 7 1 A07 -2.13 1 7
#> 8 1 A08 1.02 1 8
#> 9 1 A09 -0.281 1 9
#> 10 1 A10 0.266 1 10
#> # ℹ 950 more rows