process_input {htrSPRanalysis} | R Documentation |
Performs all functions selected in sample information, such as automated dissociation window detection, automated concentration range, automated bulk shift detection and returns a list object with the titration time series, processed sample information, all user inputs directing file outputs and fitting options
process_input(
sample_sheet_path = NULL,
data_file_path = NULL,
output_file_path = NULL,
output_pdf = NULL,
output_csv = NULL,
error_pdf = NULL,
num_cores = NULL,
min_allowed_kd = 10^(-5),
max_iterations = 1000,
ptol = 10^(-10),
ftol = 10^(-10),
min_RU_tol = 20,
max_RU_tol = 300
)
sample_sheet_path |
The full path to the sample information file. |
data_file_path |
The full path to the titration data file. |
output_file_path |
The full path where output should be stored. This directory needs to exist. |
output_pdf |
The name of the file for the pdf output. |
output_csv |
The name of the file for the csv output. |
error_pdf |
The name of the file for error output. |
num_cores |
The number of cores to use for parallel processing. The default is( the number of cores detected by |
min_allowed_kd |
The minimum value for the dissociation constant. The default is 10^(-5). |
max_iterations |
The maximum number of iterations for curve fitting. The default is 1000. |
ptol |
Curve fitting parameter. If the proposed changes in parameters is smaller than this value, the optimization is considered converged. The default is 10^(-10) |
ftol |
Curve fitting parameter. If the squared error between observed and predicted values is smaller than ftol, the optimization is considered converged. The default is 10^(-10) |
min_RU_tol |
Minimum RU required for dissociation window detection |
max_RU_tol |
Maximum RU required for dissociation window detection. Also used in curve fitting. |
A list object containing the following
expanded_sample_sheet |
The sample sheet expanded to include all spots that are represented, expanding the short-hand entries for Position/Block/Channel |
sample_info |
The expanded sample sheet with only the rows that are to be fit |
sample_info_fits |
The sample_info without rows that have encountered errors in initial processing |
Time |
The dataframe whose columns are the Time values for the input titration data. This only includes columns selected for analysis. |
RU |
The dataframe whose columns are the RU values for the input titration data. Only the columns for the samples to be analyzed are included |
correctedRU |
The |
keep_concentrations |
A vector containing the indices of the columns from |
all_concentrations_values |
A vector containing the concentration values corresponding to the columns of the |
incl_concentrations_values |
A vector containing the concentration values corresponding to the |
n_time_points |
The maximum length of titration time series |
max_RU_tol |
The maximum RU for dissociation window trimming to be automated |
min_RU_tol |
The minimum RU for dissociation window trimming to be automated |
min_RU_tol |
The minimum RU for dissociation window trimming to be automated |
nwells |
The number of rows in the |
n_fit_wells |
The number of rows in the |
ftol |
The ftol parameter passed to the |
ptol |
The ptol parameter passed to the |
ptol |
The ptol parameter passed to the |
output_pdf |
The full pathname for the output pdf file |
output_csv |
The full pathname for the output csv file |
error_pdf |
The full pathname for the pdf error file. This is where errors in processing can be found. |
error_idx_concentrations |
If there is an issue in determining the concentration window for some spots, they will be logged here |
# set up file paths for example
sample_sheet_path <- system.file("extdata",
"sample_sheet.xlsx", package="htrSPRanalysis")
fn <- paste0("https://gitlab.oit.duke.edu/janice/htrspranalysis/",
"-/raw/master/inst/extdata/titration_data.xlsx?ref_type=heads")
download.file(fn,
destfile = paste0(tempdir(),"/titration_data.xlsx"),
mode = "wb")
data_file_path <- paste0(tempdir(), "/titration_data.xlsx")
# process the input
processed_input <- process_input(sample_sheet_path = sample_sheet_path,
data_file_path = data_file_path,
num_cores = 2)