QuICSeedR (version 0.1.2)

SummarizeResult: Summarize Analysis Results

Description

This function combines analysis results from multiple tests with metadata, and determines overall significance based on a specified method. By default, it evaluates sample-level result by calculating the percentage of technical replicates that exceed the pre-defined threshold.

Usage

SummarizeResult(
  analysis = NULL,
  calculation,
  sig_method = "xth_percent",
  method_threshold = 50
)

Value

A data frame summarizing results of the analysis and calculation, with columns:

• result: Overall result based on the chosen method

• position: Location of the sample replications based on plate layout

• method: Method chosen for determination of the result

• *_sig: Significance indicator for each metric

• *_p: P-value or adjusted p-value for each metric

• metric_count: Count of significant results across all analyses

• xth_count: The number of reactions crossing the fluorescent threshold

• total_rep: Total number of replicates

• xth_percent: Percentage of replicates crossing the fluorescent threshold

Arguments

analysis

Output of GetAnalysis().

calculation

Output of GetCalculation().

sig_method

Specifies the approach for determining sample-level result. Available options include "xth_percent", "metric_count", "xth_count", or any metric name present in the analysis list. The default is "xth_percent".

method_threshold

Defines the threshold value for the "metric_count", "xth_count", and "xth_percent" methods. This parameter defaults to 50.

Examples

# Define the path to the plate data file
plate_path <- system.file("extdata/20240716_p3", 
                          file = '20240716_p3_plate.xlsx', 
                          package = "QuICSeedR")
  
# Read the plate data
plate <- readxl::read_xlsx(plate_path)

# Define the path to the raw data file
raw_path <- system.file("extdata/20240716_p3", 
                        file = '20240716_p3_raw.xlsx', 
                        package = "QuICSeedR")
# Read the raw data
raw <- readxl::read_xlsx(raw_path)

# Get replicate data
replicate <- GetReplicate(plate)

# Ensure time displayed as decimal hours
plate_time = ConvertTime(raw)

#Get metadata and display the few rows 
meta = CleanMeta(raw, plate, replicate)

#Clean data 
cleanraw <- CleanRaw(meta, raw, plate_time)

#Get calculations using positive controls to normalize values. 
calculation = GetCalculation(raw = cleanraw, meta, sd_fold = 10)

#Formatting calculations for analysis (also compatible with graphing softwares used in F-SAA 
#research)
calculation_spread = SpreadCalculation(calculation)

#Get analysis comparing samples to negative control using the one-tailed Wilcox Rank-Sum test.
analysis <- GetAnalysis(calculation_spread, control = "Neg", test = "wilcox", 
                        alternative = 'greater')
                        
#Summarization of results. Default method is rate of amyloid formation.
result <- SummarizeResult(analysis, calculation)

head(result)