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-#' Clonality

-#' 

-#' Creates a data frame giving the total number of sequences, number of unique 

-#' productive sequences, number of genomes, entropy, clonality, Gini 

-#' coefficient, and the frequency (\%) of the top productive sequences in a list 

-#' of sample data frames.

-#' 

-#' @param file.list A list of data frames consisting of antigen receptor 

-#' sequencing imported by the LymphoSeq function readImmunoSeq. "aminoAcid", "count", 

-#' and "frequencyCount" are required columns.  "estimatedNumberGenomes" is optional.  

-#' Note that clonality is usually calculated from productive nucleotide sequences.  

-#' Therefore, it is not recommended to run this function using a productive sequence

-#' list aggregated by amino acids.

-#' @return Returns a data frame giving the total number of sequences, number of 

-#' unique productive sequences, number of genomes, clonality, Gini coefficient, 

-#' and the frequency (\%) of the top productive sequence in each sample.

-#' @details Clonality is derived from the Shannon entropy, which is calculated 

-#' from the frequencies of all productive sequences divided by the logarithm of 

-#' the total number of unique productive sequences.  This normalized entropy 

-#' value is then inverted (1 - normalized entropy) to produce the clonality 

-#' metric.  

-#' 

-#' The Gini coefficient is an alternative metric used to calculate repertoire 

-#' diversity and is derived from the Lorenz curve.  The Lorenz curve is drawn 

-#' such that x-axis represents the cumulative percentage of unique sequences and 

-#' the y-axis represents the cumulative percentage of reads.  A line passing 

-#' through the origin with a slope of 1 reflects equal frequencies of all clones.  

-#' The Gini coefficient is the ratio of the area between the line of equality 

-#' and the observed Lorenz curve over the total area under the line of equality.  

-#' Both Gini coefficient and clonality are reported on a scale from 0 to 1 where 

-#' 0 indicates all sequences have the same frequency and 1 indicates the 

-#' repertoire is dominated by a single sequence.

-#' @examples

-#' file.path <- system.file("extdata", "TCRB_sequencing", package = "LymphoSeq")

-#' 

-#' file.list <- readImmunoSeq(path = file.path)

-#' 

-#' clonality(file.list = file.list)

-#' @seealso \code{\link{lorenzCurve}}

-#' @export

-#' @importFrom ineq Gini

-clonality <- function(file.list) {

-    table <- data.frame(samples = names(file.list))

-    i <- 1

-    for (i in 1:length(file.list)) {

-        file <- file.list[[i]]

-        total.reads <- nrow(file)

-        file$estimatedNumberGenomes <- suppressWarnings(as.integer(file$estimatedNumberGenomes))

-        total.genomes <- sum(file$estimatedNumberGenomes)

-        total.count <- sum(file$count)

-        productive <- file[!grepl("\\*", file$aminoAcid) & file$aminoAcid != "", ]

-        frequency <- productive$count/sum(productive$count)

-        entropy <- -sum(frequency * log2(frequency), na.rm = TRUE)

-        unique.productive <- nrow(productive)

-        clonality <- 1 - round(entropy/log2(unique.productive), digits = 6)

-        table$totalSequences[i] <- total.reads

-        table$uniqueProductiveSequences[i] <- unique.productive

-        table$totalGenomes[i] <- total.genomes

-        table$totalCount[i] <- total.count

-        table$clonality[i] <- clonality

-        table$giniCoefficient[i] <- ineq::Gini(frequency)

-        table$topProductiveSequence[i] <- max(frequency) * 100

-        if (any(grepl("estimatedNumberGenomes", colnames(file)))) {

-            file$estimatedNumberGenomes <- suppressWarnings(as.integer(file$estimatedNumberGenomes))

-            total.genomes <- sum(file$estimatedNumberGenomes)

-            table$totalGenomes[i] <- ifelse(total.genomes == 0, NA, total.genomes)

-        } else {

-            table$totalGenomes[i] <- NA

-        }

-    }

-    table <- table[order(table$topProductiveSequence, decreasing = TRUE), ]

-    rownames(table) <- NULL

-    return(table)

-} 

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