MeasureLST: Function to compute Large-scale state transitions (LST)
In SilvestriMR/Genomic.Instability: Genomic.Instability

Description Usage Arguments Details Value Author(s) References Examples

View source: R/MeasureLST.R

Starting from Copy Number Alteration data derived from Whole Genome Sequencing experiments, the function compute Large-scale state transitions (LST).

1	MeasureLST(data, window, ID, workflow = c("SS", "MS"))

`data`	data.frame object. First column must contain chromosome name (e.g chr1 - factor), the second and third column the start and end position of copy number event respectively (integer), the fourth the number of copy detected in each regions (integer - For a reliable results, regions without coverage or with no significant CNA calls should be set as -1).
`window`	window used for the copy number analysis estimation (i.e end-start). List of data.frame in Multi-sample case (see workflow parameter).
`ID`	Name of the Output. It will be used as Matrix rownames. List of character in Multi-sample case (see workflow parameter).
`workflow`	"SS" for single sample analysis, "MS" for multiple samples (one "data" object for each samples).

Chromosome Y will be excluded from the analysis.

In case of "SS" workflow, the function will returns a data.frame with LST score for each chromosome and a global score (column = "score") for one sample In case of "MS" workflow, the function will returns a data.frame with LST score for each chromosome and a global score (column = "score") for all sample considered.

Marco Silvestri

S. B. Greene et al., <e2><80><9c>Chromosomal Instability Estimation Based on Next Generation Sequencing and Single Cell Genome Wide Copy Number Variation Analysis,<e2><80><9d> PLoS One, vol. 11, no. 11, p. e0165089, Nov. 2016.

T. Popova et al., <e2><80><9c>Ploidy and Large-Scale Genomic Instability Consistently Identify Basal-like Breast Carcinomas with BRCA1/2 Inactivation,<e2><80><9d> Cancer Res November 1 2012 (72) (21) 5454-5462

data(ratio)
MeasureLST(data=ratio, window=ratio[1,3],ID="AA",workflow="SS")

## The function is currently defined as
function (data, window, ID, workflow = c("SS", "MS")) 
{
    if (workflow == "SS") {
        for (x in data[, 1]) {
            par <- 1e+07/window
            ch_name <- x
            idx <- data[data[, 1] %in% x, ]
            idx1 <- rle(idx[, 4])
            idx2 <- grep("-1", idx1$values)
            idx1$lengths[idx2] <- 0
            c <- as.vector(idx1$lengths)
            c <- append(c, 0)
            c[c < par] <- 0
            c[c > par] <- 1
            count <- as.data.frame(sum(rollsum(c, 2) > 1))
            colnames(count) <- x
            assign(x, count)
        }
        TabLST <- do.call(cbind, mget(ls(pattern = "^chr")))
        TabLST$Score <- rowSums(TabLST)
        rownames(TabLST) <- ID
        TabLST <- TabLST[, c("chr1", "chr2", "chr3", "chr4", 
            "chr5", "chr6", "chr7", "chr8", "chr9", "chr10", 
            "chr11", "chr12", "chr13", "chr14", "chr15", "chr16", 
            "chr17", "chr18", "chr19", "chr20", "chr21", "chr22", 
            "chrX", "Score")]
        TabLST
    }
    else {
        for (y in ID) {
            data <- data[[1]]
            wind <- window[1]
            for (x in data[, 1]) {
                par <- 1e+07/wind
                ch_name <- x
                idx <- data[data[, 1] %in% x, ]
                idx1 <- rle(idx[, 4])
                idx2 <- grep("-1", idx1$values)
                idx1$lengths[idx2] <- 0
                c <- as.vector(idx1$lengths)
                c <- append(c, 0)
                c[c < par] <- 0
                c[c > par] <- 1
                count <- as.data.frame(sum(rollsum(c, 2) > 1))
                colnames(count) <- x
                assign(x, count)
            }
            TabLST <- do.call(cbind, mget(ls(pattern = "^chr")))
            TabLST$Score <- rowSums(TabLST)
            rownames(TabLST) <- y
            assign(paste("Bind_", y, sep = ""), TabLST)
            data <- data[-1]
            window <- window[-1]
        }
        Tab_summ <- do.call(rbind, mget(ls(pattern = "^Bind_")))
        Tab_summ <- Tab_summ[, c("chr1", "chr2", "chr3", "chr4", 
            "chr5", "chr6", "chr7", "chr8", "chr9", "chr10", 
            "chr11", "chr12", "chr13", "chr14", "chr15", "chr16", 
            "chr17", "chr18", "chr19", "chr20", "chr21", "chr22", 
            "chrX", "Score")]
        Tab_summ
    }
  }