Main Results. Kevin R, Coombes. 10 September 2011

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1 Main Results Kevin R, Coombes 10 September 2011 Contents 1 Executive Summary Introduction Aims/Objectives Methods Description of the Data Statistical Methods Results Conclusions Details 2 3 Deletion 11q 5 4 Deletion 13q 6 5 Deletion 17p 8 6 Trisomy Appendix 13 1 Executive Summary 1.1 Introduction This report describes the analysis of a data set from Carmen Schweighofer, a member of the laboratory of Lynne V. Abruzzo. This dataset was acquired using Illumina 610 SNP chips Aims/Objectives To see how well our new algorithm works to identify clonal (or fractional) copy number change. To see how well the SNP calls match the FISH data for the standard set of abnormalities. 1

2 108-clones Methods Description of the Data Statistical Methods 1.3 Results 1.4 Conclusions 2 Details Load the segmented data > source("00rnw/snp-utils.r") > load("rewind.rda") Load some clinical data, and give simpler names to the FISH results. > load("o:/private/abruzzo/finaldatacopies/readytogo.rda") > fish12 <- clin$x..positive.cells.for.trisomy.12 > fish13 <- clin$x..positive.cells.for.del13q14.3..d13s319. > fish17 <- clin$x..positive.cells.for.del.17p13.1..p53. > fish11 <- clin$x..positive.cells.for.del.11q22.3..atm. > fish13lamp <- clin$x..positive.cells.for.del.13q34.lamp1. > names(fish12) <- names(fish11) <- names(fish13) <- names(fish13lamp) <- names(fish17) <- rown hex code: > hexagon <- function(x, y, radius, aspect = 1,...) { + circ <- seq(0, 2 * pi, length = 7) + X <- x + radius * cos(circ) + Y <- y + radius * aspect * sin(circ) + polygon(x, Y,...) > loser <- function(y) { + list(beta = (1 - y)/(2 - y), lambda = log10((2 - y)/2)) > lossf <- function(beta) -log10(2 * (1 - beta)) > lossp <- function(beta) (1-2 * beta)/(1 - beta) > winner <- function(z) { + list(beta = 1/(2 + z), lambda = -log10((2 + z)/2)) > gainf <- function(beta) -log10(2 * beta) Recall how we got here:

3 108-clones 3 Now we handle a very special case: samples with copy number two but four BAF bands. These always represent a mixture of two (clonal) cell populations. If they are actually copy number two, then it is a mixture of normalcells and a clone with LOH. However, a mixture of normal cells and a clone with single-copy-loss can look similar, but with a (slightly) negative LRR. If we know the percentage of cells with a single-copy loss, we can compute the expected value of the BAF component and of the LRR. Figure 1 shows the theoretical curve (in red) and the boundary between the fractional loss and fractional LOH components. > bb <- seq(0, 0.5, length = 300) > ll <- -log10(2 * (1 - bb)) > gg <- -log10(2 * bb) > w0 <- rewind$call == "N02.UnbalHet" > w0 <- rewind$call!= "N02.BalHet" > w0 <- rewind$nbafcomp == 3 > w0 <- rewind$nbafcomp == 4 &!is.na(rewind$nbafcomp) > special <- rewind > special <- rewind[w0, ] > bet <- special$mix > lam <- special$seg.median > l2 <- -log10(2 * (1 - bet))/2 > g2 <- -log10(2 * bet)/2 > bog <- data.frame(special[, c("chrom", "SamID", "seg.median", "Mix", + "Call")], l2 = l2, clonal = lam < l2 & lam > -0.15, g2 = g2) > showme <- function(position, logrr, bafr, sam, why, chr, start, end, + gene) { + chunk <- which(rewind$chrom == chr & rewind$samid == sam & rewind$loc.start <= + end + M & rewind$loc.end >= start - M) + ptcol <- "#888888" + genecol <- "purple" + opar <- par(mfrow = c(2, 1)) + top <- max(c(0, logrr), na.rm = TRUE) + n <- mean(logrr < -1, na.rm = TRUE) + bot <- ifelse(n > 0.05, min(logrr, na.rm = TRUE), -1) + plot(position, logrr, ylim = c(bot, top), main = paste(sam, "; Chr ", + chr, sep = ""), xlab = "Base position", ylab = "Log R Ratio", + pch = 16, col = ptcol) + abline(h = log10(1/2), col = "orange") + abline(h = log10(2/2), col = "blue") + abline(h = log10(3/2), col = "green") + for (i in chunk) {

4 108-clones BAF Component Log R Ratio Figure 1: Relation between B allele freqency and log R ratio for segments initially called N02.UnbalHet. Blue points retain this call; pink points are re-called as N01.UnbalHet, represnting a fractional loss. The red curve is the theoretical location of the (BAF,LRR) value for fractional losses. Vertical green bars are the locations corresponding (from right to left) to losses in 5, 10, 15, and 20% of the cells.

5 108-clones 5 + me <- rewind[i, "seg.median"] + lines(c(rewind[i, "loc.start"], rewind[i, "loc.end"]), c(me, + me), lwd = 3) + abline(v = c(start, end), col = genecol) + mtext(gene, side = 3, at = (start + end)/2, col = genecol, line = 0.5) + plot(position, bafr, main = why, xlab = "Base position", ylab = "B Allele Frequency", + pch = 16, col = ptcol) + abline(v = c(start, end), col = genecol) + abline(h = 0.5) + mtext(gene, side = 3, at = (start + end)/2, col = genecol, line = 0.5) + par(opar) 3 Deletion 11q > M <- 1e+06 > st11 < > en11 < > w <- which(special$chrom == 11 & special$loc.start < en11 & special$loc.end > + st11) > length(w) [1] 5 > who <- as.character(special$samid)[w] > table(snp = clin$stat11, FISH = fish11 > 0) FISH SNP FALSE TRUE Abnormal 2 16 Normal 94 3 > w1 <- names(which(clin$stat11 == "Abnormal" & fish11 == 0)) > w2 <- names(which(clin$stat11 == "Normal" & fish11 > 0)) > if (!file.exists("usualsuspects")) dir.create("usualsuspects") > seeme <- unique(c(who, w1, w2)) > for (sam in seeme) { + why <- "" + if (sam %in% w1) + why <- paste(why, "SNP+, FISH-") + if (sam %in% w2) + why <- paste(why, "SNP-, FISH+")

6 108-clones 6 + if (sam %in% who) + why <- paste(why, "clonal?") + lsd <- loadsnpdata(sam, "11") + posn <- lsd$position + lrr <- lsd$log.r.ratio + baf <- lsd$b.allele.freq + locus <- posn >= st11 - M & posn <= en11 + M + png(file = file.path("usualsuspects", paste("chr11-", sam, ".png", + sep = "")), height = 480, width = 960, bg = "white") + par(bg = "white") + showme(posn[locus], lrr[locus], baf[locus], sam, why, 11, st11, + en11, "ATM") + dev.off() > data.frame(bog[w, ], fish11 = fish11[who], pcell = round(100 * lossp(bog[w, + "Mix"]), 2)) chrom SamID seg.median Mix Call l2 clonal g CL N02.UnbalHet FALSE CL N01.UnbalHet FALSE CL N01.UnbalHet TRUE CL N01.UnbalHet FALSE CL N01.UnbalHet FALSE fish11 pcell NA NA > ww <- (rewind$chrom == 11 & rewind$loc.start < en11 & rewind$loc.end > + st11) > summary(ww) Mode FALSE TRUE NA's logical Deletion 13q > st13 < > en13 < > w <- which(special$chrom == 13 & special$loc.start < en13 & special$loc.end >

7 108-clones 7 + st13) > length(w) [1] 14 > who <- as.character(special$samid)[w] > table(snp = clin$stat13, FISH = fish13 > 0) FISH SNP FALSE TRUE Abnormal 6 50 Normal 53 6 > w1 <- names(which(clin$stat13 == "Abnormal" & fish13 == 0)) > w1 <- w1[-which(w1 == "CL113")] > w2 <- names(which(clin$stat13 == "Normal" & fish13 > 0)) > if (!file.exists("usualsuspects")) dir.create("usualsuspects") > seeme <- unique(c(who, w1, w2)) > for (sam in seeme) { + why <- "" + if (sam %in% w1) + why <- paste(why, "SNP+, FISH-") + if (sam %in% w2) + why <- paste(why, "SNP-, FISH+") + if (sam %in% who) + why <- paste(why, "clonal?") + lsd <- loadsnpdata(sam, "13") + posn <- lsd$position + lrr <- lsd$log.r.ratio + baf <- lsd$b.allele.freq + locus <- posn >= st13 - M & posn <= en13 + M + png(file = file.path("usualsuspects", paste("chr13-", sam, ".png", + sep = "")), height = 480, width = 960, bg = "white") + par(bg = "white") + showme(posn[locus], lrr[locus], baf[locus], sam, why, 13, st13, + en13, "MIR16-1 through DLEU7") + dev.off() > data.frame(bog[w, ], fish13 = fish13[who], pcell = round(100 * lossp(bog[w, + "Mix"]), 2)) chrom SamID seg.median Mix Call l2 clonal g CL N01.UnbalHet TRUE

8 108-clones CL N01.UnbalHet FALSE CL N01.UnbalHet FALSE CL N01.UnbalHet FALSE CL N01.UnbalHet FALSE CL N01.UnbalHet FALSE CL N01.UnbalHet FALSE CL N01.UnbalHet FALSE CL N01.UnbalHet FALSE CL N01.UnbalHet TRUE CL N01.UnbalHet TRUE CL N01.UnbalHet TRUE CLZ N01.UnbalHet FALSE CLZ N01.UnbalHet TRUE fish13 pcell NA NA NA NA NA NA NA > ww <- (rewind$chrom == 13 & rewind$loc.start < en13 & rewind$loc.end > + st13) > summary(ww) Mode FALSE TRUE NA's logical Deletion 17p > st17 < > en17 < > w <- which(special$chrom == 17 & special$loc.start < en17 & special$loc.end > + st17) > length(w)

9 108-clones 9 [1] 7 > who <- as.character(special$samid)[w] > table(snp = clin$stat17, FISH = fish17 > 0) FISH SNP FALSE TRUE Abnormal 1 6 Normal > w1 <- names(which(clin$stat17 == "Abnormal" & fish17 == 0)) > w2 <- names(which(clin$stat17 == "Normal" & fish17 > 0)) > if (!file.exists("usualsuspects")) dir.create("usualsuspects") > seeme <- unique(c(who, w1, w2)) > for (sam in seeme) { + why <- "" + if (sam %in% w1) + why <- paste(why, "SNP+, FISH-") + if (sam %in% w2) + why <- paste(why, "SNP-, FISH+") + if (sam %in% who) + why <- paste(why, "clonal?") + lsd <- loadsnpdata(sam, "17") + posn <- lsd$position + lrr <- lsd$log.r.ratio + baf <- lsd$b.allele.freq + locus <- posn >= st17 - M & posn <= en17 + M + png(file = file.path("usualsuspects", paste("chr17-", sam, ".png", + sep = "")), height = 480, width = 960, bg = "white") + par(bg = "white") + showme(posn[locus], lrr[locus], baf[locus], sam, why, 17, st17, + en17, "TP53") + dev.off() > data.frame(bog[w, ], fish17 = fish17[who], pcell = round(100 * lossp(bog[w, + "Mix"]), 2)) chrom SamID seg.median Mix Call l2 clonal g CL N01.UnbalHet TRUE CL N02.UnbalHet FALSE CL N02.UnbalHet FALSE CL N01.UnbalHet TRUE CL N01.UnbalHet TRUE

10 108-clones CL N01.UnbalHet TRUE CL N01.UnbalHet TRUE fish17 pcell NA > ww <- (rewind$chrom == 17 & rewind$loc.start < en17 & rewind$loc.end > + st17) > summary(ww) Mode FALSE TRUE NA's logical Trisomy 12 > st12 <- M > en12 < M > w <- which(special$chrom == 12 & special$loc.start < en12 & special$loc.end > + st12) > length(w) [1] 550 > who <- as.character(special$samid)[w] > table(snp = clin$stat12, FISH = fish12 > 0) FISH SNP FALSE TRUE Abnormal 2 21 Normal 91 1 > w1 <- names(which(clin$stat12 == "Abnormal" & fish12 == 0)) > w2 <- names(which(clin$stat12 == "Normal" & fish12 > 0)) > if (!file.exists("usualsuspects")) dir.create("usualsuspects") > seeme <- unique(c(w1, w2)) > for (sam in seeme) { + why <- "" + if (sam %in% w1)

11 108-clones 11 + why <- paste(why, "SNP+, FISH-") + if (sam %in% w2) + why <- paste(why, "SNP-, FISH+") + lsd <- loadsnpdata(sam, "12") + posn <- lsd$position + lrr <- lsd$log.r.ratio + baf <- lsd$b.allele.freq + locus <- posn >= st12 - M & posn <= en12 + M + png(file = file.path("usualsuspects", paste("chr12-", sam, ".png", + sep = "")), height = 480, width = 960, bg = "white") + par(bg = "white") + showme(posn[locus], lrr[locus], baf[locus], sam, why, 12, st12, + en12, "") + dev.off() > ww <- (rewind$chrom == 12 & rewind$loc.start < en12 & rewind$loc.end > + st12) > summary(ww) Mode FALSE TRUE NA's logical > w <- which(special$chrom == 13 & special$loc.start < en13 & special$loc.end > + st13) > length(w) [1] 14 > who <- as.character(special$samid)[w] > data.frame(bog[w, ], fish13 = fish13[who]) chrom SamID seg.median Mix Call l2 clonal g CL N01.UnbalHet TRUE CL N01.UnbalHet FALSE CL N01.UnbalHet FALSE CL N01.UnbalHet FALSE CL N01.UnbalHet FALSE CL N01.UnbalHet FALSE CL N01.UnbalHet FALSE CL N01.UnbalHet FALSE CL N01.UnbalHet FALSE CL N01.UnbalHet TRUE CL N01.UnbalHet TRUE

12 108-clones CL N01.UnbalHet TRUE CLZ N01.UnbalHet FALSE CLZ N01.UnbalHet TRUE fish NA NA NA NA NA NA NA > ww <- (rewind$chrom == 13 & rewind$loc.start < en13 & rewind$loc.end > + st13) > summary(ww) Mode FALSE TRUE NA's logical > chug <- fish13 > 0 > table(snp = clin$stat12, FISH = fish12 > 0) FISH SNP FALSE TRUE Abnormal 2 21 Normal 91 1 > w <- which(special$chrom == 12 & special$loc.start < en12 & special$loc.end > + st12) > length(w) [1] 550 > who <- as.character(special$samid)[w] > ww <- (rewind$chrom == 12 & rewind$loc.start < en12 & rewind$loc.end > + st12) > summary(ww)

13 108-clones 13 Mode FALSE TRUE NA's logical > plot(c(0, 0.5), c(-0.3, log10(8/2)), type = "n") > a <- 0.9/0.5 > r < > hexagon(0.5, 0, r, a, col = "gray") > hexagon(0, , r, a, col = "gray") > for (i in 3:8) hexagon(1/i, log10(i/2), r, a, col = "gray") > lines(bb, gg, col = "green", lwd = 2) > lines(bb, gg/2, col = "orange", lwd = 2) > lines(bb, ll, col = "red", lwd = 2) > abline(h = 0, col = "blue", lwd = 2) > lines(bb, ll/2, col = "purple", lwd = 2) > perc <- seq(0, 1, by = 0.1) > bl <- (1 - perc)/(2 - perc) > points(bl, lossf(bl), pch = 16, col = "black") > bg <- 1/(2 + perc) > points(bg, gainf(bg), pch = 16, col = "black") > points(perc/2, 0 * perc, pch = 16, col = "black") > lossf(0.1) [1] > whatever <- lam < l2 & lam > Appendix This analysis was run in the following directory: > getwd() [1] "c:/snp-cll/analysis03" Note that \\mdadqsfs02\bioinfo2 is the standard insititutional location for storing data and analyses; O: is the name given to that location on this machine. This analysis was run in the following software environment: > sessioninfo() R version ( ) Platform: x86_64-pc-mingw32/x64 (64-bit)

14 108-clones 14 locale: [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 [3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C [5] LC_TIME=English_United States.1252 attached base packages: [1] stats graphics grdevices utils datasets methods base