git-svn-id: file:///home/git/hedgehog.fhcrc.org/bioconductor/trunk/madman/Rpacks/crlmm@43958 bc3139a8-67e5-0310-9ffc-ced21a209358
Rob Scharp authored on 12/01/2010 16:00:31
| ... | ... |
@@ -1,7 +1,7 @@ |
| 1 | 1 |
Package: crlmm |
| 2 | 2 |
Type: Package |
| 3 | 3 |
Title: Genotype Calling (CRLMM) and Copy Number Analysis tool for Affymetrix SNP 5.0 and 6.0 and Illumina arrays. |
| 4 |
-Version: 1.5.19 |
|
| 4 |
+Version: 1.5.20 |
|
| 5 | 5 |
Date: 2009-12-24 |
| 6 | 6 |
Author: Rafael A Irizarry, Benilton S Carvalho <bcarvalh@jhsph.edu>, Robert Scharpf <rscharpf@jhsph.edu>, Matt Ritchie <mritchie@wehi.edu.au> |
| 7 | 7 |
Maintainer: Benilton S Carvalho <bcarvalh@jhsph.edu>, Robert Scharpf <rscharpf@jhsph.edu>, Matt Ritchie <mritchie@wehi.EDU.AU> |
| ... | ... |
@@ -50,7 +50,7 @@ importFrom(mvtnorm, dmvnorm) |
| 50 | 50 |
importFrom(ellipse, ellipse) |
| 51 | 51 |
|
| 52 | 52 |
exportMethods(A, B, copyNumber) |
| 53 |
-export(cnOptions, crlmm, crlmmCopynumber, ellipse, readIdatFiles, snprma) |
|
| 53 |
+export(cnOptions, crlmm, crlmmCopynumber, ellipse, readIdatFiles, snprma, getParam) |
|
| 54 | 54 |
|
| 55 | 55 |
##export(##viterbi.CNSet, ##move to VanillaICE |
| 56 | 56 |
## combineIntensities, |
| ... | ... |
@@ -59,3 +59,4 @@ export(cnOptions, crlmm, crlmmCopynumber, ellipse, readIdatFiles, snprma) |
| 59 | 59 |
## crlmmWrapper, |
| 60 | 60 |
## withinGenotypeMoments, |
| 61 | 61 |
## locationAndScale, getParam.SnpSuperSet) |
| 62 |
+export(thresholdModelParams, computeCopynumber.CNSet, nuphiAllele, coefs, biasAdjNP) |
| ... | ... |
@@ -32,8 +32,8 @@ generateIXTX <- function(x, nrow=3) {
|
| 32 | 32 |
|
| 33 | 33 |
nuphiAllele <- function(object, allele, Ystar, W, tmp.objects, cnOptions){
|
| 34 | 34 |
I <- isSnp(object) |
| 35 |
- object.snp <- object[I, ] |
|
| 36 | 35 |
Ystar <- Ystar[I, ] |
| 36 |
+ rownames(Ystar) <- featureNames(object)[isSnp(object)] |
|
| 37 | 37 |
complete <- rowSums(is.na(W)) == 0 & I |
| 38 | 38 |
W <- W[I, ] |
| 39 | 39 |
if(any(!is.finite(W))){## | any(!is.finite(V))){
|
| ... | ... |
@@ -73,7 +73,6 @@ nuphiAllele <- function(object, allele, Ystar, W, tmp.objects, cnOptions){
|
| 73 | 73 |
if(allele == "A") X <- cbind(1, 2:0) else X <- cbind(1, 0:2) |
| 74 | 74 |
if(NOHET) X <- X[-2, ] ##more than 1 X chromosome, but all homozygous |
| 75 | 75 |
} |
| 76 |
- |
|
| 77 | 76 |
##How to quickly generate Xstar, Xstar = diag(W) %*% X |
| 78 | 77 |
Xstar <- apply(W, 1, generateX, X) |
| 79 | 78 |
IXTX <- apply(Xstar, 2, generateIXTX, nrow=nrow(X)) |
| ... | ... |
@@ -118,12 +117,12 @@ nuphiAllele <- function(object, allele, Ystar, W, tmp.objects, cnOptions){
|
| 118 | 117 |
object <- pr(object, "phiBX", batch, phiBX) |
| 119 | 118 |
} |
| 120 | 119 |
} |
| 121 |
- THR.NU.PHI <- cnOptions$THR.NU.PHI |
|
| 122 |
- if(THR.NU.PHI){
|
|
| 123 |
- verbose <- cnOptions$verbose |
|
| 124 |
- if(verbose) message("Thresholding nu and phi")
|
|
| 125 |
- object <- thresholdModelParams(object, cnOptions) |
|
| 126 |
- } |
|
| 120 |
+## THR.NU.PHI <- cnOptions$THR.NU.PHI |
|
| 121 |
+## if(THR.NU.PHI){
|
|
| 122 |
+## verbose <- cnOptions$verbose |
|
| 123 |
+## if(verbose) message("Thresholding nu and phi")
|
|
| 124 |
+## object <- thresholdModelParams(object, cnOptions) |
|
| 125 |
+## } |
|
| 127 | 126 |
return(object) |
| 128 | 127 |
} |
| 129 | 128 |
|
| ... | ... |
@@ -246,11 +245,12 @@ crlmmCopynumber <- function(filenames, cnOptions, object, ...){
|
| 246 | 245 |
SKW=snprmaResult$SKW, |
| 247 | 246 |
mixtureParams=snprmaResult$mixtureParams, |
| 248 | 247 |
cdfName=snprmaResult$cdfName) |
| 248 |
+ cnOptions[["batch"]] <- cnOptions[["batch"]][snpI[["SNR"]] >= SNRmin] |
|
| 249 | 249 |
cnSet <- combineIntensities(res=snpI, |
| 250 | 250 |
NP=npI, |
| 251 | 251 |
callSet=callSet[index.snps, ]) |
| 252 | 252 |
if(any(cnSet$SNR > SNRmin)){
|
| 253 |
- warning(paste("Excluding samples with SNR < ", SNRmin))
|
|
| 253 |
+ message(paste("Excluding samples with SNR < ", SNRmin))
|
|
| 254 | 254 |
cnSet <- cnSet[, cnSet$SNR >= SNRmin] |
| 255 | 255 |
} |
| 256 | 256 |
rm(snpI, npI, snps, cnps, index.snps, index.nps); gc() |
| ... | ... |
@@ -765,6 +765,7 @@ nonpolymorphic <- function(object, cnOptions, tmp.objects){
|
| 765 | 765 |
phi2 <- 2^(Yhat2) |
| 766 | 766 |
nu1 <- 2^(mus[, 1]) - phi1 |
| 767 | 767 |
nu2 <- 2^(mus[, 2]) - 2*phi2 |
| 768 |
+ |
|
| 768 | 769 |
if(any(pseudoAR)){
|
| 769 | 770 |
nu1[pseudoAR] <- 2^(mus[pseudoAR, 1]) - 2*phi1[pseudoAR] |
| 770 | 771 |
} |
| ... | ... |
@@ -788,15 +789,25 @@ nonpolymorphic <- function(object, cnOptions, tmp.objects){
|
| 788 | 789 |
sig2A <- getParam(object, "sig2A", batch) |
| 789 | 790 |
normal.f <- normal[, object$gender==2] |
| 790 | 791 |
sig2A[!isSnp(object)] <- rowMAD(log2(A.female*normal.f), na.rm=TRUE)^2 |
| 792 |
+ sig2A[!isSnp(object) & is.na(sig2A)] <- median(sig2A[!isSnp(object)], na.rm=TRUE) |
|
| 791 | 793 |
##sig2T[, p] <- rowMAD(log2(NP*normalNP), na.rm=TRUE)^2 |
| 792 | 794 |
object <- pr(object, "sig2A", batch, sig2A) |
| 793 | 795 |
|
| 794 | 796 |
nuA[!isSnp(object)] <- nu2 |
| 795 |
- object <- pr(object, "nuA", batch, nuA) |
|
| 796 |
- ##nuT[, p] <- nu2 |
|
| 797 | 797 |
phiA[!isSnp(object)] <- phi2 |
| 798 |
- object <- pr(object, "phiA", batch, phiA) |
|
| 799 | 798 |
|
| 799 |
+ THR.NU.PHI <- cnOptions$THR.NU.PHI |
|
| 800 |
+ if(THR.NU.PHI){
|
|
| 801 |
+ verbose <- cnOptions$verbose |
|
| 802 |
+ ##Assign values to object |
|
| 803 |
+ object <- pr(object, "nuA", batch, nuA) |
|
| 804 |
+ object <- pr(object, "phiA", batch, phiA) |
|
| 805 |
+ if(verbose) message("Thresholding nu and phi")
|
|
| 806 |
+ object <- thresholdModelParams(object, cnOptions) |
|
| 807 |
+ } else {
|
|
| 808 |
+ object <- pr(object, "nuA", batch, nuA) |
|
| 809 |
+ object <- pr(object, "phiA", batch, phiA) |
|
| 810 |
+ } |
|
| 800 | 811 |
} else {
|
| 801 | 812 |
A <- A(object)[!isSnp(object), ] |
| 802 | 813 |
mus <- rowMedians(A * normal, na.rm=TRUE) |
| ... | ... |
@@ -805,6 +816,19 @@ nonpolymorphic <- function(object, cnOptions, tmp.objects){
|
| 805 | 816 |
logPhiT <- X %*% betahat |
| 806 | 817 |
phiA[!isSnp(object)] <- 2^(logPhiT) |
| 807 | 818 |
nuA[!isSnp(object)] <- mus-2*phiA[!isSnp(object)] |
| 819 |
+ |
|
| 820 |
+ THR.NU.PHI <- cnOptions$THR.NU.PHI |
|
| 821 |
+ if(THR.NU.PHI){
|
|
| 822 |
+ verbose <- cnOptions$verbose |
|
| 823 |
+ ##Assign values to object |
|
| 824 |
+ object <- pr(object, "nuA", batch, nuA) |
|
| 825 |
+ object <- pr(object, "phiA", batch, phiA) |
|
| 826 |
+ if(verbose) message("Thresholding nu and phi")
|
|
| 827 |
+ object <- thresholdModelParams(object, cnOptions) |
|
| 828 |
+ ##reassign values (now thresholded at MIN.NU and MIN.PHI |
|
| 829 |
+ nuA <- getParam(object, "nuA", batch) |
|
| 830 |
+ phiA <- getParam(object, "phiA", batch) |
|
| 831 |
+ } |
|
| 808 | 832 |
CA(object)[!isSnp(object), ] <- 1/phiA[!isSnp(object)]*(A - nuA[!isSnp(object)]) |
| 809 | 833 |
sig2A <- getParam(object, "sig2A", batch) |
| 810 | 834 |
sig2A[!isSnp(object)] <- rowMAD(log2(A*normal), na.rm=TRUE)^2 |
| ... | ... |
@@ -1307,8 +1331,9 @@ biasAdj <- function(object, cnOptions, tmp.objects){
|
| 1307 | 1331 |
## only exclude observations from one tail, depending on |
| 1308 | 1332 |
## whether more are up or down |
| 1309 | 1333 |
moreup <- rowSums(mostLikelyState > 3) > rowSums(mostLikelyState < 3) ##3 is normal |
| 1334 |
+ ## if equal, which points have a high posterior probability of altered copy number. drop those. |
|
| 1310 | 1335 |
NORM <- matrix(FALSE, nrow(A), ncol(A)) |
| 1311 |
- NORM[proportionSamplesAltered > 0.8, ] <- FALSE |
|
| 1336 |
+ ##NORM[proportionSamplesAltered > 0.8, ] <- FALSE |
|
| 1312 | 1337 |
ratioUp <- posteriorProb[, , 4]/posteriorProb[, , 3] |
| 1313 | 1338 |
NORM[ii & moreup, ] <- ratioUp[moreup & ii] < 1 ##normal more likely |
| 1314 | 1339 |
ratioDown <- posteriorProb[, , 2]/posteriorProb[, , 3] |
| ... | ... |
@@ -1338,7 +1363,16 @@ biasAdjNP <- function(object, cnOptions, tmp.objects){
|
| 1338 | 1363 |
lT <- log2(A) |
| 1339 | 1364 |
I <- isSnp(object) |
| 1340 | 1365 |
counter <- 1 ##state counter |
| 1341 |
- for(CT in 0:3){
|
|
| 1366 |
+## for(CT in 0:3){
|
|
| 1367 |
+## sds <- sqrt(tau2A[I]*(CT==0) + sig2A[I]*(CT > 0)) |
|
| 1368 |
+## means <- suppressWarnings(log2(nuA[I]+CT*phiA[I])) |
|
| 1369 |
+## tmp <- dnorm(lT, mean=means, sd=sds) |
|
| 1370 |
+## emit[, , counter] <- tmp |
|
| 1371 |
+## counter <- counter+1 |
|
| 1372 |
+## } |
|
| 1373 |
+## mostLikelyState <- apply(emit, c(1, 2), function(x) order(x, decreasing=TRUE)[1]) |
|
| 1374 |
+ counter <- 1 |
|
| 1375 |
+ for(CT in c(0,1,2,2.5)){
|
|
| 1342 | 1376 |
sds <- sqrt(tau2A[I]*(CT==0) + sig2A[I]*(CT > 0)) |
| 1343 | 1377 |
means <- suppressWarnings(log2(nuA[I]+CT*phiA[I])) |
| 1344 | 1378 |
tmp <- dnorm(lT, mean=means, sd=sds) |
| ... | ... |
@@ -1346,6 +1380,7 @@ biasAdjNP <- function(object, cnOptions, tmp.objects){
|
| 1346 | 1380 |
counter <- counter+1 |
| 1347 | 1381 |
} |
| 1348 | 1382 |
mostLikelyState <- apply(emit, c(1, 2), function(x) order(x, decreasing=TRUE)[1]) |
| 1383 |
+ |
|
| 1349 | 1384 |
if(CHR == 23){
|
| 1350 | 1385 |
## the state index for male on chromosome 23 is 2 |
| 1351 | 1386 |
## add 1 so that the state index is 3 for 'normal' state |
| ... | ... |
@@ -1401,29 +1436,37 @@ getParams <- function(object, batch){
|
| 1401 | 1436 |
} |
| 1402 | 1437 |
|
| 1403 | 1438 |
|
| 1439 |
+## Constrain nu and phi to positive values |
|
| 1404 | 1440 |
thresholdModelParams <- function(object, cnOptions){
|
| 1405 | 1441 |
MIN.NU <- cnOptions$MIN.NU |
| 1406 | 1442 |
MIN.PHI <- cnOptions$MIN.PHI |
| 1407 | 1443 |
batch <- unique(object$batch) |
| 1408 | 1444 |
nuA <- getParam(object, "nuA", batch) |
| 1409 | 1445 |
nuA[nuA < MIN.NU] <- MIN.NU |
| 1446 |
+ object <- pr(object, "nuA", batch, nuA) |
|
| 1410 | 1447 |
nuB <- getParam(object, "nuB", batch) |
| 1411 |
- nuB[nuB < MIN.NU] <- MIN.NU |
|
| 1448 |
+ if(!all(is.na(nuB))){
|
|
| 1449 |
+ nuB[nuB < MIN.NU] <- MIN.NU |
|
| 1450 |
+ object <- pr(object, "nuB", batch, nuB) |
|
| 1451 |
+ } |
|
| 1412 | 1452 |
phiA <- getParam(object, "phiA", batch) |
| 1413 | 1453 |
phiA[phiA < MIN.PHI] <- MIN.PHI |
| 1454 |
+ object <- pr(object, "phiA", batch, phiA) |
|
| 1414 | 1455 |
phiB <- getParam(object, "phiB", batch) |
| 1415 |
- phiB[phiB < MIN.PHI] <- MIN.PHI |
|
| 1416 |
- phiAX <- as.numeric(getParam(object, "phiAX", batch)) |
|
| 1417 |
- phiAX[phiAX < MIN.PHI] <- MIN.PHI |
|
| 1456 |
+ if(!all(is.na(phiB))){
|
|
| 1457 |
+ phiB[phiB < MIN.PHI] <- MIN.PHI |
|
| 1458 |
+ object <- pr(object, "phiB", batch, phiB) |
|
| 1459 |
+ } |
|
| 1460 |
+ phiAX <- as.numeric(getParam(object, "phiAX", batch)) |
|
| 1461 |
+ if(!all(is.na(phiAX))){
|
|
| 1462 |
+ phiAX[phiAX < MIN.PHI] <- MIN.PHI |
|
| 1463 |
+ object <- pr(object, "phiAX", batch, phiAX) |
|
| 1464 |
+ } |
|
| 1418 | 1465 |
phiBX <- as.numeric(getParam(object, "phiBX", batch)) |
| 1419 |
- phiBX[phiBX < MIN.PHI] <- MIN.PHI |
|
| 1420 |
- |
|
| 1421 |
- object <- pr(object, "nuA", batch, nuA) |
|
| 1422 |
- object <- pr(object, "nuB", batch, nuB) |
|
| 1423 |
- object <- pr(object, "phiA", batch, phiA) |
|
| 1424 |
- object <- pr(object, "phiB", batch, phiB) |
|
| 1425 |
- object <- pr(object, "phiAX", batch, phiAX) |
|
| 1426 |
- object <- pr(object, "phiBX", batch, phiBX) |
|
| 1466 |
+ if(!all(is.na(phiBX))){
|
|
| 1467 |
+ phiBX[phiBX < MIN.PHI] <- MIN.PHI |
|
| 1468 |
+ object <- pr(object, "phiBX", batch, phiBX) |
|
| 1469 |
+ } |
|
| 1427 | 1470 |
return(object) |
| 1428 | 1471 |
} |
| 1429 | 1472 |
|
| ... | ... |
@@ -1463,6 +1506,10 @@ computeCopynumber.CNSet <- function(object, cnOptions){
|
| 1463 | 1506 |
tmp.objects <- instantiateObjects(object.batch, |
| 1464 | 1507 |
cnOptions) |
| 1465 | 1508 |
bias.adj <- cnOptions$bias.adj |
| 1509 |
+ if(bias.adj & ncol(object) <= 15){
|
|
| 1510 |
+ warning(paste("bias.adj is TRUE, but too few samples to perform this step"))
|
|
| 1511 |
+ cnOptions$bias.adj <- bias.adj <- FALSE |
|
| 1512 |
+ } |
|
| 1466 | 1513 |
if(bias.adj){
|
| 1467 | 1514 |
if(verbose) message("Dropping samples with low posterior prob. of normal copy number (samples dropped is locus-specific)")
|
| 1468 | 1515 |
tmp.objects <- biasAdjNP(object.batch, cnOptions, tmp.objects) |
| ... | ... |
@@ -1477,7 +1524,15 @@ computeCopynumber.CNSet <- function(object, cnOptions){
|
| 1477 | 1524 |
tmp.objects <- oneBatch(object.batch, |
| 1478 | 1525 |
cnOptions=cnOptions, |
| 1479 | 1526 |
tmp.objects=tmp.objects) |
| 1527 |
+ ##coefs calls nuphiAllele. |
|
| 1480 | 1528 |
object.batch <- coefs(object.batch, cnOptions, tmp.objects) |
| 1529 |
+ ##nuA=getParam(object.batch, "nuA", PLATE) |
|
| 1530 |
+ THR.NU.PHI <- cnOptions$THR.NU.PHI |
|
| 1531 |
+ if(THR.NU.PHI){
|
|
| 1532 |
+ verbose <- cnOptions$verbose |
|
| 1533 |
+ if(verbose) message("Thresholding nu and phi")
|
|
| 1534 |
+ object.batch <- thresholdModelParams(object.batch, cnOptions) |
|
| 1535 |
+ } |
|
| 1481 | 1536 |
if(verbose) message("\nAllele specific copy number")
|
| 1482 | 1537 |
object.batch <- polymorphic(object.batch, cnOptions, tmp.objects) |
| 1483 | 1538 |
if(any(!isSnp(object))){ ## there are nonpolymorphic probes
|
| ... | ... |
@@ -133,17 +133,6 @@ ellipse.CNSet <- function(x, copynumber, batch, ...){
|
| 133 | 133 |
corrA.BB <- getParam(x, "corrA.BB", batch) |
| 134 | 134 |
corrB.AA <- getParam(x, "corrB.AA", batch) |
| 135 | 135 |
corr <- getParam(x, "corr", batch) |
| 136 |
-## nuA <- as.numeric(fData(x)[, match(paste("nuA", batch, sep="_"), fvarLabels(x))])
|
|
| 137 |
-## nuB <- as.numeric(fData(x)[, match(paste("nuB", batch, sep="_"), fvarLabels(x))])
|
|
| 138 |
-## phiA <- as.numeric(fData(x)[, match(paste("phiA", batch, sep="_"), fvarLabels(x))])
|
|
| 139 |
-## phiB <- as.numeric(fData(x)[, match(paste("phiB", batch, sep="_"), fvarLabels(x))])
|
|
| 140 |
-## tau2A <- as.numeric(fData(x)[, match(paste("tau2A", batch, sep="_"), fvarLabels(x))])
|
|
| 141 |
-## tau2B <- as.numeric(fData(x)[, match(paste("tau2B", batch, sep="_"), fvarLabels(x))])
|
|
| 142 |
-## sig2A <- as.numeric(fData(x)[, match(paste("sig2A", batch, sep="_"), fvarLabels(x))])
|
|
| 143 |
-## sig2B <- as.numeric(fData(x)[, match(paste("sig2B", batch, sep="_"), fvarLabels(x))])
|
|
| 144 |
-## corrA.BB <- as.numeric(fData(x)[, match(paste("corrA.BB", batch, sep="_"), fvarLabels(x))])
|
|
| 145 |
-## corrB.AA <- as.numeric(fData(x)[, match(paste("corrB.AA", batch, sep="_"), fvarLabels(x))])
|
|
| 146 |
-## corr <- as.numeric(fData(x)[, match(paste("corr", batch, sep="_"), fvarLabels(x))])
|
|
| 147 | 136 |
for(CN in copynumber){
|
| 148 | 137 |
for(CA in 0:CN){
|
| 149 | 138 |
CB <- CN-CA |
| 150 | 139 |
new file mode 100644 |
| ... | ... |
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