Fnorm is the ratio of the mean fluorescence in a "hot" window, while the IR
laser is on, to the mean fluorescence in a "cold" window just before it,
expressed in per mille. Recalculating Fnorm from read_mst_traces()
lets you choose the windows without going back to MO.Affinity Analysis.
Usage
mst_fnorm(data, hot, cold = c(-1, 0))Arguments
- data
A data frame of traces, as returned by
read_mst_traces(), with columnstimeandfluorescence.- hot, cold
Start and end times of the hot and cold windows, in seconds, as numeric vectors of length 2. The hot window depends on how long the laser was on; look up the one used in MO.Affinity Analysis with
read_mst_metadata().
Value
A tibble with one row per capillary, with the columns of data
other than time, fluorescence and fluorescence_raw, plus
response_type (always
"fnorm") and response, the Fnorm in per mille. This is the same form as
read_mst_dose_response(), ready for mst_fit().
Details
Windows include their start and exclude their end, as MO.Affinity Analysis does, so the results match its Fnorm for the same windows.
Examples
traces <- read_mst_traces(tidymst_example("dppr10-cy5_traces.xlsx"))
mst_fnorm(traces, hot = c(19, 20))
#> # A tibble: 80 × 16
#> merge_set run capillary measured_at capillary_type ligand
#> <chr> <chr> <int> <dttm> <chr> <chr>
#> 1 dPPR10-Cy5 Tray Run atpH… 1 2018-11-21 09:42:32 Unspecified c… dPPR1…
#> 2 dPPR10-Cy5 Tray Run atpH… 2 2018-11-21 09:43:14 Unspecified c… dPPR1…
#> 3 dPPR10-Cy5 Tray Run atpH… 3 2018-11-21 09:43:57 Unspecified c… dPPR1…
#> 4 dPPR10-Cy5 Tray Run atpH… 4 2018-11-21 09:44:39 Unspecified c… dPPR1…
#> 5 dPPR10-Cy5 Tray Run atpH… 5 2018-11-21 09:45:22 Unspecified c… dPPR1…
#> 6 dPPR10-Cy5 Tray Run atpH… 6 2018-11-21 09:46:05 Unspecified c… dPPR1…
#> 7 dPPR10-Cy5 Tray Run atpH… 7 2018-11-21 09:46:47 Unspecified c… dPPR1…
#> 8 dPPR10-Cy5 Tray Run atpH… 8 2018-11-21 09:47:30 Unspecified c… dPPR1…
#> 9 dPPR10-Cy5 Tray Run atpH… 9 2018-11-21 09:48:13 Unspecified c… dPPR1…
#> 10 dPPR10-Cy5 Tray Run atpH… 10 2018-11-21 09:48:55 Unspecified c… dPPR1…
#> # ℹ 70 more rows
#> # ℹ 10 more variables: ligand_concentration <dbl>, target <chr>,
#> # target_concentration <dbl>, mst_power <chr>, excitation_power <dbl>,
#> # excitation_type <chr>, thermostat_setpoint <chr>, included <lgl>,
#> # response_type <chr>, response <dbl>
# Use a shorter hot window, excluding outliers
traces |>
dplyr::filter(included) |>
mst_fnorm(hot = c(1.5, 2.5))
#> # A tibble: 79 × 16
#> merge_set run capillary measured_at capillary_type ligand
#> <chr> <chr> <int> <dttm> <chr> <chr>
#> 1 dPPR10-Cy5 Tray Run atpH… 1 2018-11-21 09:42:32 Unspecified c… dPPR1…
#> 2 dPPR10-Cy5 Tray Run atpH… 2 2018-11-21 09:43:14 Unspecified c… dPPR1…
#> 3 dPPR10-Cy5 Tray Run atpH… 3 2018-11-21 09:43:57 Unspecified c… dPPR1…
#> 4 dPPR10-Cy5 Tray Run atpH… 4 2018-11-21 09:44:39 Unspecified c… dPPR1…
#> 5 dPPR10-Cy5 Tray Run atpH… 5 2018-11-21 09:45:22 Unspecified c… dPPR1…
#> 6 dPPR10-Cy5 Tray Run atpH… 6 2018-11-21 09:46:05 Unspecified c… dPPR1…
#> 7 dPPR10-Cy5 Tray Run atpH… 7 2018-11-21 09:46:47 Unspecified c… dPPR1…
#> 8 dPPR10-Cy5 Tray Run atpH… 8 2018-11-21 09:47:30 Unspecified c… dPPR1…
#> 9 dPPR10-Cy5 Tray Run atpH… 9 2018-11-21 09:48:13 Unspecified c… dPPR1…
#> 10 dPPR10-Cy5 Tray Run atpH… 10 2018-11-21 09:48:55 Unspecified c… dPPR1…
#> # ℹ 69 more rows
#> # ℹ 10 more variables: ligand_concentration <dbl>, target <chr>,
#> # target_concentration <dbl>, mst_power <chr>, excitation_power <dbl>,
#> # excitation_type <chr>, thermostat_setpoint <chr>, included <lgl>,
#> # response_type <chr>, response <dbl>