Reads the fits that MO.Affinity Analysis made to each merge set. These are included in Compare Results (Chart and Grid) and Dose-Response (Grouped) exports.
Value
A tibble with one row per merge set, with columns:
series,merge_set,target,target_concentrationandligandidentify the merge set.seriesis missing for Grid exports.model: the fit model,"kd"or"hill".unboundandbound: the response of the unbound and bound states.kdandkd_confidence(Kd model): the dissociation constant and its confidence, in molar.target_concentration_fit(Kd model): the target concentration used in the fit, which may differ from the nominaltarget_concentrationif it was a free parameter.ec50,ec50_confidenceandhill(Hill model): the half-maximal concentration, its confidence, and the Hill coefficient.std_dev: the standard deviation of the residuals.
Grid exports also include fit statistics such as std_error,
reduced_chi_sq and signal_to_noise. MO.Affinity Analysis project
files (.nta) give one row per merge set per model fitted, with
standard errors instead of confidences; see the Project files section of
read_mst().
Examples
read_mst_fit(tidymst_example("dppr10-cy5_compare-fnorm.xlsx"))
#> # A tibble: 2 × 12
#> series merge_set target target_concentration ligand model bound unbound
#> <int> <chr> <chr> <dbl> <chr> <chr> <dbl> <dbl>
#> 1 1 dPPR10-Cy5 Tr… atpH-… 0.00000005 dPPR1… kd 8.52e+2 1093.
#> 2 2 dPPR10-Cy5 Tr… NEAT1… 0.00000005 dPPR1… kd 4.67e-4 971.
#> # ℹ 4 more variables: kd <dbl>, target_concentration_fit <dbl>, std_dev <dbl>,
#> # kd_confidence <dbl>
read_mst_fit(tidymst_example("dsnppr10_compare-delta-fnorm.xlsx"))
#> # A tibble: 2 × 12
#> series merge_set target target_concentration ligand model bound unbound hill
#> <int> <chr> <chr> <dbl> <chr> <chr> <dbl> <dbl> <dbl>
#> 1 1 dsnPPR10 … RNAat… 0.00000005 dsnPP… hill 841. 1061. 1.35
#> 2 2 dsnPPR10 … RNAKP… 0.00000005 dsnPP… hill 973. 972. 1.8
#> # ℹ 3 more variables: ec50 <dbl>, std_dev <dbl>, ec50_confidence <dbl>