Create differential uptake dataset with p-value
create_p_diff_uptake_dataset.RdCreates differential deuterium uptake dataset with P-value from t-Student test for selected two biological states.
Usage
create_p_diff_uptake_dataset(
dat,
diff_uptake_dat = NULL,
protein = unique(dat[["Protein"]])[1],
state_1 = unique(dat[["State"]])[1],
state_2 = unique(dat[["State"]])[2],
p_adjustment_method = "none",
confidence_level = 0.98,
time_0 = min(dat[["Exposure"]]),
time_100 = max(dat[["Exposure"]]),
deut_part = 0.9
)Arguments
- dat
data imported by the
read_hdxfunction.- diff_uptake_dat
differential uptake data
- protein
chosen protein.
- state_1
biological state for chosen protein. From this state values the second state values are subtracted to get the deuterium uptake difference.
- state_2
biological state for chosen protein. This state values are subtracted from the first state values to get the deuterium uptake difference.
- p_adjustment_method
method of adjustment P-values for multiple comparisons. Possible methods: "BH" (Benjamini & Hochberg correction), "bonferroni" (Bonferroni correction) and "none" (default).
- confidence_level
confidence level for the t-test.
- time_0
minimal exchange control time point of measurement [min].
- time_100
maximal exchange control time point of measurement [min].
- deut_part
deuterium percentage in solution used in experiment, value from range [0, 1].
Value
a data.frame object with calculated deuterium uptake difference
in different forms with their uncertainty, P-value and -log(P-value) for the peptides
from the provided data.
Details
For peptides in all of the time points of measurement (except for minimal and maximal exchange control) the deuterium uptake difference between state_1 and state_2 is calculated, with its uncertainty (combined and propagated as described in `Data processing` article). For each peptide in time point the P-value is calculated using unpaired t-test. The deuterium uptake difference is calculated as the difference of measured masses in a given time point for two states. The tested hypothesis is that the mean masses for states from the replicates of the experiment are similar. The P-values indicates if the null hypothesis can be rejected - rejection of the hypothesis means that the difference between states is statistically significant at provided confidence level. The P-values can be adjusted using the provided method.
References
Hageman, T. S. & Weis, D. D. Reliable Identification of Significant Differences in Differential Hydrogen Exchange-Mass Spectrometry Measurements Using a Hybrid Significance Testing Approach. Anal Chem 91, 8008–8016 (2019).
Examples
p_diff_uptake_dat <- create_p_diff_uptake_dataset(alpha_dat)
head(p_diff_uptake_dat)
#> Protein Sequence Start End Exposure Modification ID MaxUptake
#> 1 db_eEF1Ba GFGDLKSPAGL 1 11 0.167 NA 1 9
#> 2 db_eEF1Ba GFGDLKSPAGL 1 11 1.000 NA 1 9
#> 3 db_eEF1Ba GFGDLKSPAGL 1 11 5.000 NA 1 9
#> 4 db_eEF1Ba GFGDLKSPAGL 1 11 25.000 NA 1 9
#> 5 db_eEF1Ba GFGDLKSPAGL 1 11 150.000 NA 1 9
#> 6 db_eEF1Ba GFGDLKSPAGL 1 11 1440.000 NA 1 9
#> Med_Sequence State_1 frac_deut_uptake_1 err_frac_deut_uptake_1
#> 1 6 ALPHA_Gamma 30.648518 0.22154053
#> 2 6 ALPHA_Gamma 52.330800 0.74197387
#> 3 6 ALPHA_Gamma 66.179800 1.15204366
#> 4 6 ALPHA_Gamma 86.300338 1.46322512
#> 5 6 ALPHA_Gamma 98.612529 1.63494174
#> 6 6 ALPHA_Gamma 1.434621 0.01002946
#> deut_uptake_1 err_deut_uptake_1 theo_frac_deut_uptake_1
#> 1 1.665053 0.003059254 17.33535
#> 2 2.842995 0.035068821 31.77278
#> 3 3.595375 0.057318502 40.99432
#> 4 4.688471 0.072421134 54.39185
#> 5 5.357359 0.080539467 62.59008
#> 6 5.432737 0.037980370 63.51395
#> err_theo_frac_deut_uptake_1 theo_deut_uptake_1 err_theo_deut_uptake_1
#> 1 0.03749574 1.414381 0.003059254
#> 2 0.42982083 2.592322 0.035068821
#> 3 0.70252393 3.344702 0.057318502
#> 4 0.88762927 4.437798 0.072421134
#> 5 0.98713157 5.106687 0.080539467
#> 6 0.46550621 5.182064 0.037980370
#> State_2 frac_deut_uptake_2 err_frac_deut_uptake_2 deut_uptake_2
#> 1 ALPHA_beta_gamma 29.413612 0.43761622 1.590581
#> 2 ALPHA_beta_gamma 44.591592 0.46016476 2.411351
#> 3 ALPHA_beta_gamma 59.188881 0.43761754 3.200719
#> 4 ALPHA_beta_gamma 76.891814 1.55917136 4.158029
#> 5 ALPHA_beta_gamma 97.832169 1.16778379 5.290407
#> 6 ALPHA_beta_gamma 1.427992 0.01055797 5.407635
#> err_deut_uptake_2 theo_frac_deut_uptake_2 err_theo_frac_deut_uptake_2
#> 1 0.02053577 16.42258 0.2516966
#> 2 0.01735971 26.48234 0.2127692
#> 3 0.00000000 36.15723 0.0000000
#> 4 0.07850979 47.89049 0.9622549
#> 5 0.04957693 61.76948 0.6076394
#> 6 0.03998177 63.20629 0.4900363
#> theo_deut_uptake_2 err_theo_deut_uptake_2 diff_frac_deut_uptake
#> 1 1.339908 0.02053577 1.234906456
#> 2 2.160678 0.01735971 7.739208705
#> 3 2.950046 0.00000000 6.990918595
#> 4 3.907356 0.07850979 9.408523973
#> 5 5.039734 0.04957693 0.780359881
#> 6 5.156963 0.03998177 0.006628648
#> err_diff_frac_deut_uptake diff_deut_uptake err_diff_deut_uptake
#> 1 0.49049787 0.07447260 0.02076239
#> 2 0.87308467 0.43164420 0.03913032
#> 3 1.23236102 0.39465576 0.05731850
#> 4 2.13823364 0.53044168 0.10681109
#> 5 2.00916736 0.06695263 0.09457525
#> 6 0.01456231 0.02510190 0.05514572
#> diff_theo_frac_deut_uptake err_diff_theo_frac_deut_uptake
#> 1 0.9127730 0.2544742
#> 2 5.2904450 0.4796005
#> 3 4.8370964 0.7025239
#> 4 6.5013558 1.3091295
#> 5 0.8206046 1.1591611
#> 6 0.3076613 0.6758932
#> diff_theo_deut_uptake err_diff_theo_deut_uptake P_value log_p_value
#> 1 0.07447260 0.02076239 0.065344248 2.7280859
#> 2 0.43164420 0.03913032 0.001789245 6.3259618
#> 3 0.39465576 0.05731850 NA NA
#> 4 0.53044168 0.10681109 0.023503782 3.7505939
#> 5 0.06695263 0.09457525 0.530754368 0.6334559
#> 6 0.02510190 0.05514572 0.672642212 0.3965417