Read a MO.Affinity Analysis export

read_mst() detects the type of export with mst_export_type() and reads its main table:

Usage

read_mst(path)

Arguments

path: Path to an .xlsx file exported from MO.Affinity Analysis, or a .moc or .nta project file.

Value

A tibble.

Details

MST Traces: read_mst_traces().
Capillary Scan: read_mst_capillary_scan().
Compare Results (Chart) and Dose-Response (Grouped and Flat): read_mst_dose_response().
Compare Results (Grid): read_mst_fit().
MO.Control (.moc) and MO.Affinity Analysis (.nta) project files: read_mst_traces().

Project files

MO.Control (.moc) and MO.Affinity Analysis (.nta) save projects as SQLite databases, which hold everything the Excel exports are made from. read_mst_traces(), read_mst_capillary_scan() and read_mst_metadata() read both kinds of project; read_mst_dose_response() and read_mst_fit() read MO.Affinity Analysis projects, which include the analysis. They return the same columns as for the Excel exports, with these differences:

An analysis_set column names the analysis set, as a project can hold several. A trace in more than one analysis set appears once for each. MO.Control projects have no analysis, so analysis_set, merge_set and included are missing, and run is named as MO.Affinity Analysis would name it.
Traces also have fluorescence_raw, the fluorescence in raw counts. fluorescence is normalised to the mean before the laser switches on, which is within about 0.2% of MO.Affinity Analysis's normalisation.
Measurement times are in UTC (the Excel exports use local time), and temperature is the measured temperature in degrees Celsius.
mst_power is a percentage, such as "40%", rather than a label such as "Medium", and excitation_type is not available.
The fits from read_mst_fit() are those saved in the project, which may differ from an export made at another time. They include each parameter's standard error as reported by MO.Affinity Analysis (*_std_error), and fixed lists any parameters that were fixed.

Fit curves (read_mst_fit_curve()) are not read from projects; calculate them with mst_fit() and mst_curve().

Examples

read_mst(tidymst_example("dppr10-cy5_dose-response-flat.xlsx"))
#> # A tibble: 48 × 25
#>    merge_set       run              capillary target target_concentration ligand
#>    <chr>           <chr>                <int> <chr>                 <dbl> <chr> 
#>  1 dPPR10-Cy5 Tray Run atpH-fl_50_…         1 atpH-…           0.00000005 dPPR1…
#>  2 dPPR10-Cy5 Tray Run atpH-fl_50_…         2 atpH-…           0.00000005 dPPR1…
#>  3 dPPR10-Cy5 Tray Run atpH-fl_50_…         3 atpH-…           0.00000005 dPPR1…
#>  4 dPPR10-Cy5 Tray Run atpH-fl_50_…         4 atpH-…           0.00000005 dPPR1…
#>  5 dPPR10-Cy5 Tray Run atpH-fl_50_…         5 atpH-…           0.00000005 dPPR1…
#>  6 dPPR10-Cy5 Tray Run atpH-fl_50_…         6 atpH-…           0.00000005 dPPR1…
#>  7 dPPR10-Cy5 Tray Run atpH-fl_50_…         7 atpH-…           0.00000005 dPPR1…
#>  8 dPPR10-Cy5 Tray Run atpH-fl_50_…         8 atpH-…           0.00000005 dPPR1…
#>  9 dPPR10-Cy5 Tray Run atpH-fl_50_…         9 atpH-…           0.00000005 dPPR1…
#> 10 dPPR10-Cy5 Tray Run atpH-fl_50_…        10 atpH-…           0.00000005 dPPR1…
#> # ℹ 38 more rows
#> # ℹ 19 more variables: ligand_concentration <dbl>, response_type <chr>,
#> #   response <dbl>, project <chr>, analysis_set <chr>, analysis_type <chr>,
#> #   evaluation_strategy <chr>, origin <chr>, measured_at <dttm>,
#> #   cold_start <dbl>, cold_end <dbl>, hot_start <dbl>, hot_end <dbl>,
#> #   mst_power <chr>, excitation_power <dbl>, temperature <dbl>,
#> #   exported_on <dttm>, bleaching_rate <dbl>, initial_fluorescence <dbl>

# A project file from MO.Affinity Analysis
read_mst(tidymst_example("dppr10-cy5.nta"))
#> # A tibble: 29,415 × 18
#>    analysis_set    merge_set       run   capillary measured_at         mst_power
#>    <chr>           <chr>           <chr>     <int> <dttm>              <chr>    
#>  1 Analysis-Set #1 dPPR10-Cy5 Tray Run …         1 2018-11-21 01:42:32 40%      
#>  2 Analysis-Set #1 dPPR10-Cy5 Tray Run …         1 2018-11-21 01:42:32 40%      
#>  3 Analysis-Set #1 dPPR10-Cy5 Tray Run …         1 2018-11-21 01:42:32 40%      
#>  4 Analysis-Set #1 dPPR10-Cy5 Tray Run …         1 2018-11-21 01:42:32 40%      
#>  5 Analysis-Set #1 dPPR10-Cy5 Tray Run …         1 2018-11-21 01:42:32 40%      
#>  6 Analysis-Set #1 dPPR10-Cy5 Tray Run …         1 2018-11-21 01:42:32 40%      
#>  7 Analysis-Set #1 dPPR10-Cy5 Tray Run …         1 2018-11-21 01:42:32 40%      
#>  8 Analysis-Set #1 dPPR10-Cy5 Tray Run …         1 2018-11-21 01:42:32 40%      
#>  9 Analysis-Set #1 dPPR10-Cy5 Tray Run …         1 2018-11-21 01:42:32 40%      
#> 10 Analysis-Set #1 dPPR10-Cy5 Tray Run …         1 2018-11-21 01:42:32 40%      
#> # ℹ 29,405 more rows
#> # ℹ 12 more variables: excitation_power <dbl>, thermostat_setpoint <chr>,
#> #   temperature <dbl>, capillary_type <chr>, ligand <chr>,
#> #   ligand_concentration <dbl>, target <chr>, target_concentration <dbl>,
#> #   included <lgl>, time <dbl>, fluorescence <dbl>, fluorescence_raw <dbl>