git-svn-id: file:///home/git/hedgehog.fhcrc.org/bioconductor/trunk/madman/Rpacks/OncoSimulR@108872 bc3139a8-67e5-0310-9ffc-ced21a209358
Ramon Diaz-Uriarte authored on 27/09/2015 12:39:23
| ... | ... |
@@ -1,8 +1,8 @@ |
| 1 | 1 |
Package: OncoSimulR |
| 2 | 2 |
Type: Package |
| 3 | 3 |
Title: Forward Genetic Simulation of Cancer Progresion with Epistasis |
| 4 |
-Version: 1.99.6 |
|
| 5 |
-Date: 2015-09-26 |
|
| 4 |
+Version: 1.99.7 |
|
| 5 |
+Date: 2015-09-27 |
|
| 6 | 6 |
Author: Ramon Diaz-Uriarte. |
| 7 | 7 |
Maintainer: Ramon Diaz-Uriarte <rdiaz02@gmail.com> |
| 8 | 8 |
Description: Functions for forward population genetic simulation in |
| ... | ... |
@@ -56,9 +56,10 @@ oncoSimulSample <- function(Nindiv, |
| 56 | 56 |
## well, obviously they are errors |
| 57 | 57 |
## errorHitWallTime = TRUE, |
| 58 | 58 |
## errorHitMaxTries = TRUE, |
| 59 |
- verbosity = 1, |
|
| 60 | 59 |
typeSample = "whole", |
| 61 | 60 |
thresholdWhole = 0.5, |
| 61 |
+ initMutant = NULL, |
|
| 62 |
+ verbosity = 1, |
|
| 62 | 63 |
seed = "auto"){
|
| 63 | 64 |
## No longer using mclapply, because of the way we use the limit on |
| 64 | 65 |
## the number of tries. |
| ... | ... |
@@ -174,6 +175,7 @@ oncoSimulSample <- function(Nindiv, |
| 174 | 175 |
errorHitWallTime = TRUE, |
| 175 | 176 |
errorHitMaxTries = TRUE, |
| 176 | 177 |
seed = seed, |
| 178 |
+ initMutant = initMutant, |
|
| 177 | 179 |
keepPhylog = keepPhylog) |
| 178 | 180 |
|
| 179 | 181 |
if(tmp$other$UnrecoverExcept) {
|
| ... | ... |
@@ -211,8 +213,10 @@ oncoSimulSample <- function(Nindiv, |
| 211 | 213 |
} |
| 212 | 214 |
return(list( |
| 213 | 215 |
popSummary = summary(pop), |
| 214 |
- popSample = samplePop(pop, typeSample = typeSample, |
|
| 215 |
- thresholdWhole = thresholdWhole, geneNames = geneNames), |
|
| 216 |
+ popSample = samplePop(pop, timeSample = "last", |
|
| 217 |
+ typeSample = typeSample, |
|
| 218 |
+ thresholdWhole = thresholdWhole, |
|
| 219 |
+ geneNames = geneNames), |
|
| 216 | 220 |
attemptsUsed = attemptsUsed, |
| 217 | 221 |
probCancer = Nindiv/attemptsUsed, |
| 218 | 222 |
HittedMaxTries = FALSE, |
| ... | ... |
@@ -294,6 +298,7 @@ oncoSimulPop <- function(Nindiv, |
| 294 | 298 |
max.num.tries = 500, |
| 295 | 299 |
errorHitWallTime = TRUE, |
| 296 | 300 |
errorHitMaxTries = TRUE, |
| 301 |
+ initMutant = NULL, |
|
| 297 | 302 |
verbosity = 0, |
| 298 | 303 |
mc.cores = detectCores(), |
| 299 | 304 |
seed = "auto") {
|
| ... | ... |
@@ -328,7 +333,8 @@ oncoSimulPop <- function(Nindiv, |
| 328 | 333 |
errorHitWallTime = errorHitWallTime, |
| 329 | 334 |
errorHitMaxTries = errorHitMaxTries, |
| 330 | 335 |
verbosity = verbosity, |
| 331 |
- seed = seed, keepPhylog = keepPhylog |
|
| 336 |
+ seed = seed, keepPhylog = keepPhylog, |
|
| 337 |
+ initMutant = initMutant |
|
| 332 | 338 |
), |
| 333 | 339 |
mc.cores = mc.cores |
| 334 | 340 |
) |
| ... | ... |
@@ -895,7 +901,7 @@ get.mut.vector <- function(x, timeSample, typeSample, |
| 895 | 901 |
if(typeSample %in% c("wholeTumor", "whole")) {
|
| 896 | 902 |
popSize <- x$PerSampleStats[the.time, 1] |
| 897 | 903 |
return( as.numeric((tcrossprod(pop, |
| 898 |
- x$Genotypes)/popSize) > thresholdWhole) ) |
|
| 904 |
+ x$Genotypes)/popSize) >= thresholdWhole) ) |
|
| 899 | 905 |
} else if (typeSample %in% c("singleCell", "single")) {
|
| 900 | 906 |
|
| 901 | 907 |
return(x$Genotypes[, sample(seq_along(pop), 1, prob = pop)]) |
| ... | ... |
@@ -51,7 +51,9 @@ oncoSimulPop(Nindiv, fp, model = "Exp", numPassengers = 30, mu = 1e-6, |
| 51 | 51 |
max.num.tries = 500, |
| 52 | 52 |
errorHitWallTime = TRUE, |
| 53 | 53 |
errorHitMaxTries = TRUE, |
| 54 |
- verbosity = 0, mc.cores = detectCores(), |
|
| 54 |
+ initMutant = NULL, |
|
| 55 |
+ verbosity = 0, |
|
| 56 |
+ mc.cores = detectCores(), |
|
| 55 | 57 |
seed = "auto") |
| 56 | 58 |
|
| 57 | 59 |
|
| ... | ... |
@@ -90,9 +92,10 @@ oncoSimulSample(Nindiv, |
| 90 | 92 |
max.memory = 2000, |
| 91 | 93 |
max.wall.time.total = 600, |
| 92 | 94 |
max.num.tries.total = 500 * Nindiv, |
| 93 |
- verbosity = 1, |
|
| 94 | 95 |
typeSample = "whole", |
| 95 | 96 |
thresholdWhole = 0.5, |
| 97 |
+ initMutant = NULL, |
|
| 98 |
+ verbosity = 1, |
|
| 96 | 99 |
seed = "auto") |
| 97 | 100 |
|
| 98 | 101 |
|
| ... | ... |
@@ -102,6 +105,7 @@ oncoSimulSample(Nindiv, |
| 102 | 105 |
|
| 103 | 106 |
\item{Nindiv}{Number of individuals or number of different
|
| 104 | 107 |
trajectories to simulate.} |
| 108 |
+ |
|
| 105 | 109 |
\item{fp}{
|
| 106 | 110 |
|
| 107 | 111 |
Either a poset that specifies the order restrictions (see |
| ... | ... |
@@ -372,15 +376,14 @@ to be detected. For \code{oncoSimulSample} this can be a vector.
|
| 372 | 376 |
you set it to "auto", then if you are using v.1, the behavior is the |
| 373 | 377 |
same as if you set it to NULL (a seed will be generated in R and |
| 374 | 378 |
passed to C++) but if you are using v.2, a random seed will be |
| 375 |
- produced in C++. %% using the randutils code from M.E.O'Neill. |
|
| 376 |
- If you need |
|
| 377 |
- reproducibility, either pass a value or set it to NULL (setting it to |
|
| 378 |
- NULL will make the C++ seed reproducible if you use the same seed in R |
|
| 379 |
- via \code{set.seed}). However, even using the same value of
|
|
| 379 |
+ produced in C++. %% using the randutils code from M.E.O'Neill. If you |
|
| 380 |
+ need reproducibility, either pass a value or set it to NULL (setting |
|
| 381 |
+ it to NULL will make the C++ seed reproducible if you use the same |
|
| 382 |
+ seed in R via \code{set.seed}). However, even using the same value of
|
|
| 380 | 383 |
\code{seed} is unlikely to give the exact same results between
|
| 381 |
- platforms and compilers. Note that the defaults are not |
|
| 382 |
- the same in \code{oncoSimulIndiv}, \code{oncoSimulPop} and
|
|
| 383 |
- \code{oncoSimulSample}. }
|
|
| 384 |
+ platforms and compilers. Moreover, note that the defaults for |
|
| 385 |
+ \code{seed} are not the same in \code{oncoSimulIndiv},
|
|
| 386 |
+ \code{oncoSimulPop} and \code{oncoSimulSample}. }
|
|
| 384 | 387 |
|
| 385 | 388 |
|
| 386 | 389 |
|
| ... | ... |
@@ -32,7 +32,7 @@ samplePop(x, timeSample = "last", typeSample = "whole", |
| 32 | 32 |
in the simulation between the time when the first driver appeared |
| 33 | 33 |
and the final time period. "unif" means that it is almost sure that |
| 34 | 34 |
different individuals will be sampled at different times. "last" |
| 35 |
- does not guarantee that different individuals will be sample at the |
|
| 35 |
+ does not guarantee that different individuals will be sampled at the |
|
| 36 | 36 |
same time unit, only that all will be sampled in the last time unit |
| 37 | 37 |
of their simulation. |
| 38 | 38 |
} |
| ... | ... |
@@ -18,7 +18,8 @@ test_that("initMutant crashes",
|
| 18 | 18 |
initSize = 1000, |
| 19 | 19 |
keepPhylog = TRUE |
| 20 | 20 |
, initMutant = c("b, a") ## also "a" and "b" separate
|
| 21 |
- )) |
|
| 21 |
+ ), |
|
| 22 |
+ "genes not in the fitness table") |
|
| 22 | 23 |
expect_error(oncoSimulIndiv(o3, model = "McFL", |
| 23 | 24 |
mu = 5e-5, finalTime = 500, |
| 24 | 25 |
detectionDrivers = 3, |
| ... | ... |
@@ -26,7 +27,8 @@ test_that("initMutant crashes",
|
| 26 | 27 |
initSize = 1000, |
| 27 | 28 |
keepPhylog = TRUE |
| 28 | 29 |
, initMutant = c("b", "a") ## also "a" and "b" separate
|
| 29 |
- )) |
|
| 30 |
+ ), |
|
| 31 |
+ "genes not in the fitness table") |
|
| 30 | 32 |
expect_error(oncoSimulIndiv(o3, model = "McFL", |
| 31 | 33 |
mu = 5e-5, finalTime = 500, |
| 32 | 34 |
detectionDrivers = 3, |
| ... | ... |
@@ -34,7 +36,8 @@ test_that("initMutant crashes",
|
| 34 | 36 |
initSize = 1000, |
| 35 | 37 |
keepPhylog = TRUE |
| 36 | 38 |
, initMutant = c("1", "2") ## also "a" and "b" separate
|
| 37 |
- )) |
|
| 39 |
+ ), |
|
| 40 |
+ "genes not in the fitness table") |
|
| 38 | 41 |
}) |
| 39 | 42 |
|
| 40 | 43 |
|
| ... | ... |
@@ -160,3 +163,186 @@ test_that("initMutant non lexicog order",
|
| 160 | 163 |
expect_true( "m, d_u" %in% cn ) |
| 161 | 164 |
expect_true( "m, d, f_u" %in% cn ) |
| 162 | 165 |
}) |
| 166 |
+ |
|
| 167 |
+ |
|
| 168 |
+test_that("initMutant with oncoSimulSample", {
|
|
| 169 |
+ o3init <- allFitnessEffects(orderEffects = c( |
|
| 170 |
+ "M > D > F" = 0.99, |
|
| 171 |
+ "D > M > F" = 0.2, |
|
| 172 |
+ "D > M" = 0.1, |
|
| 173 |
+ "M > D" = 0.9), |
|
| 174 |
+ noIntGenes = c("u" = 0.01,
|
|
| 175 |
+ "v" = 0.01, |
|
| 176 |
+ "w" = 0.001, |
|
| 177 |
+ "x" = 0.0001, |
|
| 178 |
+ "y" = -0.0001, |
|
| 179 |
+ "z" = -0.001), |
|
| 180 |
+ geneToModule = |
|
| 181 |
+ c("Root" = "Root",
|
|
| 182 |
+ "M" = "m", |
|
| 183 |
+ "F" = "f", |
|
| 184 |
+ "D" = "d") ) |
|
| 185 |
+ ossI <- oncoSimulSample(4, |
|
| 186 |
+ o3init, model = "Exp", |
|
| 187 |
+ mu = 5e-5, finalTime = 500, |
|
| 188 |
+ detectionDrivers = 2, |
|
| 189 |
+ onlyCancer = TRUE, |
|
| 190 |
+ initSize = 10, |
|
| 191 |
+ initMutant = c("z > d"),
|
|
| 192 |
+ thresholdWhole = 1 ## check presence of initMutant |
|
| 193 |
+ ) |
|
| 194 |
+ ssp <- ossI$popSample |
|
| 195 |
+ expect_equal(ssp[, c("d", "z")],
|
|
| 196 |
+ matrix(1, nrow = 4, ncol = 2, |
|
| 197 |
+ dimnames = list(NULL, c("d", "z"))))
|
|
| 198 |
+ expect_false(sum(ssp) == prod(dim(ssp))) ## we don't just have all of |
|
| 199 |
+ ## them, which would turn the |
|
| 200 |
+ ## previous into irrelevant |
|
| 201 |
+ expect_equal(grep("d",
|
|
| 202 |
+ as.character(ossI$popSummary$OccurringDrivers)), 1:4) |
|
| 203 |
+}) |
|
| 204 |
+ |
|
| 205 |
+ |
|
| 206 |
+test_that("initMutant with oncoSimulSample, 2", {
|
|
| 207 |
+ o3init <- allFitnessEffects(orderEffects = c( |
|
| 208 |
+ "M > D > F" = 0.99, |
|
| 209 |
+ "D > M > F" = 0.2, |
|
| 210 |
+ "D > M" = 0.1, |
|
| 211 |
+ "M > D" = 0.9, |
|
| 212 |
+ "M > A" = 0.25), |
|
| 213 |
+ noIntGenes = c("u" = 0.01,
|
|
| 214 |
+ "v" = 0.01, |
|
| 215 |
+ "w" = 0.001, |
|
| 216 |
+ "x" = 0.0001, |
|
| 217 |
+ "y" = -0.0001, |
|
| 218 |
+ "z" = -0.001), |
|
| 219 |
+ geneToModule = |
|
| 220 |
+ c("Root" = "Root",
|
|
| 221 |
+ "A" = "a", |
|
| 222 |
+ "M" = "m", |
|
| 223 |
+ "F" = "f", |
|
| 224 |
+ "D" = "d") ) |
|
| 225 |
+ ossI <- oncoSimulSample(4, |
|
| 226 |
+ o3init, model = "Exp", |
|
| 227 |
+ mu = 5e-5, finalTime = 500, |
|
| 228 |
+ detectionDrivers = 3, |
|
| 229 |
+ onlyCancer = TRUE, |
|
| 230 |
+ initSize = 10, |
|
| 231 |
+ initMutant = c("z > a"),
|
|
| 232 |
+ thresholdWhole = 1 ## check presence of initMutant |
|
| 233 |
+ ) |
|
| 234 |
+ ssp <- ossI$popSample |
|
| 235 |
+ expect_equal(ssp[, c("a", "z")],
|
|
| 236 |
+ matrix(1, nrow = 4, ncol = 2, |
|
| 237 |
+ dimnames = list(NULL, c("a", "z"))))
|
|
| 238 |
+ expect_false(sum(ssp) == prod(dim(ssp))) ## we don't just have all of |
|
| 239 |
+ ## them, which would turn the |
|
| 240 |
+ ## previous into irrelevant |
|
| 241 |
+ expect_equal(grep("a",
|
|
| 242 |
+ as.character(ossI$popSummary$OccurringDrivers)), 1:4) |
|
| 243 |
+}) |
|
| 244 |
+ |
|
| 245 |
+ |
|
| 246 |
+test_that("initMutant with oncoSimulPop", {
|
|
| 247 |
+ o3init <- allFitnessEffects(orderEffects = c( |
|
| 248 |
+ "M > D > F" = 0.99, |
|
| 249 |
+ "D > M > F" = 0.2, |
|
| 250 |
+ "D > M" = 0.1, |
|
| 251 |
+ "M > D" = 0.9), |
|
| 252 |
+ noIntGenes = c("u" = 0.01,
|
|
| 253 |
+ "v" = 0.01, |
|
| 254 |
+ "w" = 0.001, |
|
| 255 |
+ "x" = 0.0001, |
|
| 256 |
+ "y" = -0.0001, |
|
| 257 |
+ "z" = -0.001), |
|
| 258 |
+ geneToModule = |
|
| 259 |
+ c("Root" = "Root",
|
|
| 260 |
+ "M" = "m", |
|
| 261 |
+ "F" = "f", |
|
| 262 |
+ "D" = "d") ) |
|
| 263 |
+ ospI <- oncoSimulPop(4, |
|
| 264 |
+ o3init, model = "Exp", |
|
| 265 |
+ mu = 5e-5, finalTime = 1000, |
|
| 266 |
+ detectionDrivers = 3, |
|
| 267 |
+ onlyCancer = TRUE, |
|
| 268 |
+ keepPhylog = TRUE, |
|
| 269 |
+ initSize = 10, |
|
| 270 |
+ initMutant = c("d > m > y"),
|
|
| 271 |
+ mc.cores = 2 |
|
| 272 |
+ ) |
|
| 273 |
+ genepos <- match(c("d", "m", "y"), ospI[[1]]$geneNames)
|
|
| 274 |
+ expect_true( all( |
|
| 275 |
+ unlist(lapply(ospI, |
|
| 276 |
+ function(x) x$Genotypes[genepos, , drop = FALSE])) == 1)) |
|
| 277 |
+ ## make sure not all 1, by error, which would render previous useless |
|
| 278 |
+ expect_false( all( |
|
| 279 |
+ unlist(lapply(ospI, |
|
| 280 |
+ function(x) x$Genotypes)) == 1)) |
|
| 281 |
+ expect_true(all(unlist(lapply(ospI, |
|
| 282 |
+ function(x) ( |
|
| 283 |
+ lapply(x$GenotypesWDistinctOrderEff, |
|
| 284 |
+ function(z) genepos %in% z)))))) |
|
| 285 |
+ ## Like before, check no silly things |
|
| 286 |
+ allgenepos <- seq_along(ospI[[1]]$geneNames) |
|
| 287 |
+ expect_false(all(unlist(lapply(ospI, |
|
| 288 |
+ function(x) ( |
|
| 289 |
+ lapply(x$GenotypesWDistinctOrderEff, |
|
| 290 |
+ function(z) allgenepos %in% z)))))) |
|
| 291 |
+ expect_true(all( |
|
| 292 |
+ lapply(ospI, |
|
| 293 |
+ function(x) |
|
| 294 |
+ as.character(x$other$PhylogDF[1, 1])) == "d, m_y")) |
|
| 295 |
+}) |
|
| 296 |
+ |
|
| 297 |
+ |
|
| 298 |
+ |
|
| 299 |
+test_that("initMutant with oncoSimulPop, 2", {
|
|
| 300 |
+ o3init <- allFitnessEffects(orderEffects = c( |
|
| 301 |
+ "M > D > F" = 0.99, |
|
| 302 |
+ "D > M > F" = 0.2, |
|
| 303 |
+ "D > M" = 0.1, |
|
| 304 |
+ "M > D" = 0.9), |
|
| 305 |
+ noIntGenes = c("u" = 0.01,
|
|
| 306 |
+ "v" = 0.01, |
|
| 307 |
+ "w" = 0.001, |
|
| 308 |
+ "x" = 0.0001, |
|
| 309 |
+ "y" = -0.0001, |
|
| 310 |
+ "z" = -0.001), |
|
| 311 |
+ geneToModule = |
|
| 312 |
+ c("Root" = "Root",
|
|
| 313 |
+ "M" = "m", |
|
| 314 |
+ "F" = "f", |
|
| 315 |
+ "D" = "d") ) |
|
| 316 |
+ ospI <- oncoSimulPop(4, |
|
| 317 |
+ o3init, model = "Exp", |
|
| 318 |
+ mu = 5e-5, finalTime = 70, |
|
| 319 |
+ detectionDrivers = 4, ## yes, reach end |
|
| 320 |
+ onlyCancer = FALSE, |
|
| 321 |
+ keepPhylog = TRUE, |
|
| 322 |
+ initSize = 10, |
|
| 323 |
+ initMutant = c("m > v > d"),
|
|
| 324 |
+ mc.cores = 2 |
|
| 325 |
+ ) |
|
| 326 |
+ genepos <- match(c("d", "m", "v"), ospI[[1]]$geneNames)
|
|
| 327 |
+ expect_true( all( |
|
| 328 |
+ unlist(lapply(ospI, |
|
| 329 |
+ function(x) x$Genotypes[genepos, , drop = FALSE])) == 1)) |
|
| 330 |
+ ## make sure not all 1, by error, which would render previous useless |
|
| 331 |
+ expect_false( all( |
|
| 332 |
+ unlist(lapply(ospI, |
|
| 333 |
+ function(x) x$Genotypes)) == 1)) |
|
| 334 |
+ expect_true(all(unlist(lapply(ospI, |
|
| 335 |
+ function(x) ( |
|
| 336 |
+ lapply(x$GenotypesWDistinctOrderEff, |
|
| 337 |
+ function(z) genepos %in% z)))))) |
|
| 338 |
+ ## Like before, check no silly things |
|
| 339 |
+ allgenepos <- seq_along(ospI[[1]]$geneNames) |
|
| 340 |
+ expect_false(all(unlist(lapply(ospI, |
|
| 341 |
+ function(x) ( |
|
| 342 |
+ lapply(x$GenotypesWDistinctOrderEff, |
|
| 343 |
+ function(z) allgenepos %in% z)))))) |
|
| 344 |
+ expect_true(all( |
|
| 345 |
+ lapply(ospI, |
|
| 346 |
+ function(x) |
|
| 347 |
+ as.character(x$other$PhylogDF[1, 1])) == "m, d_v")) |
|
| 348 |
+}) |
| ... | ... |
@@ -3323,21 +3323,65 @@ o3init <- allFitnessEffects(orderEffects = c( |
| 3323 | 3323 |
"D > M > F" = 0.2, |
| 3324 | 3324 |
"D > M" = 0.1, |
| 3325 | 3325 |
"M > D" = 0.9), |
| 3326 |
- noIntGenes = c("u" = 0.01, "z" = 0.01),
|
|
| 3326 |
+ noIntGenes = c("u" = 0.01,
|
|
| 3327 |
+ "v" = 0.01, |
|
| 3328 |
+ "w" = 0.001, |
|
| 3329 |
+ "x" = 0.0001, |
|
| 3330 |
+ "y" = -0.0001, |
|
| 3331 |
+ "z" = -0.001), |
|
| 3327 | 3332 |
geneToModule = |
| 3328 | 3333 |
c("Root" = "Root",
|
| 3329 | 3334 |
"M" = "m", |
| 3330 | 3335 |
"F" = "f", |
| 3331 | 3336 |
"D" = "d") ) |
| 3332 |
-tmpI <- oncoSimulIndiv(o3init, model = "McFL", |
|
| 3337 |
+ |
|
| 3338 |
+oneI <- oncoSimulIndiv(o3init, model = "McFL", |
|
| 3333 | 3339 |
mu = 5e-5, finalTime = 500, |
| 3334 | 3340 |
detectionDrivers = 3, |
| 3335 | 3341 |
onlyCancer = FALSE, |
| 3336 | 3342 |
initSize = 1000, |
| 3337 | 3343 |
keepPhylog = TRUE, |
| 3338 | 3344 |
initMutant = c("m > u > d")
|
| 3339 |
- ) |
|
| 3340 |
-plotClonePhylog(tmpI, N = 0) |
|
| 3345 |
+ ) |
|
| 3346 |
+plotClonePhylog(oneI, N = 0) |
|
| 3347 |
+ |
|
| 3348 |
+ |
|
| 3349 |
+## |
|
| 3350 |
+ospI <- oncoSimulPop(4, |
|
| 3351 |
+ o3init, model = "Exp", |
|
| 3352 |
+ mu = 5e-5, finalTime = 500, |
|
| 3353 |
+ detectionDrivers = 3, |
|
| 3354 |
+ onlyCancer = TRUE, |
|
| 3355 |
+ initSize = 10, |
|
| 3356 |
+ keepPhylog = TRUE, |
|
| 3357 |
+ initMutant = c("d > m > z"),
|
|
| 3358 |
+ mc.cores = 2 |
|
| 3359 |
+ ) |
|
| 3360 |
+ |
|
| 3361 |
+op <- par(mar = rep(0, 4), mfrow = c(2, 2)) |
|
| 3362 |
+plotClonePhylog(ospI[[1]]) |
|
| 3363 |
+plotClonePhylog(ospI[[2]]) |
|
| 3364 |
+plotClonePhylog(ospI[[3]]) |
|
| 3365 |
+plotClonePhylog(ospI[[4]]) |
|
| 3366 |
+par(op) |
|
| 3367 |
+ |
|
| 3368 |
+ |
|
| 3369 |
+ossI <- oncoSimulSample(4, |
|
| 3370 |
+ o3init, model = "Exp", |
|
| 3371 |
+ mu = 5e-5, finalTime = 500, |
|
| 3372 |
+ detectionDrivers = 2, |
|
| 3373 |
+ onlyCancer = TRUE, |
|
| 3374 |
+ initSize = 10, |
|
| 3375 |
+ initMutant = c("z > d"),
|
|
| 3376 |
+ thresholdWhole = 1 ## check presence of initMutant |
|
| 3377 |
+ ) |
|
| 3378 |
+ |
|
| 3379 |
+## No phylogeny is kept with oncoSimulSample, but look at the |
|
| 3380 |
+## OcurringDrivers and the sample |
|
| 3381 |
+ |
|
| 3382 |
+ossI$popSample |
|
| 3383 |
+ossI$popSummary[, "OccurringDrivers", drop = FALSE] |
|
| 3384 |
+ |
|
| 3341 | 3385 |
|
| 3342 | 3386 |
@ |
| 3343 | 3387 |
|
| ... | ... |
@@ -1,15 +1,15 @@ |
| 1 | 1 |
\usepackage[% |
| 2 |
- shash={5ea2efc},
|
|
| 3 |
- lhash={5ea2efc59f87434290924e8cd341fac5f5ee67ae},
|
|
| 2 |
+ shash={ea5bee4},
|
|
| 3 |
+ lhash={ea5bee4855766a04a04786475d269790a28c8373},
|
|
| 4 | 4 |
authname={ramon diaz-uriarte (at Bufo)},
|
| 5 | 5 |
authemail={rdiaz02@gmail.com},
|
| 6 |
- authsdate={2015-09-26},
|
|
| 7 |
- authidate={2015-09-26 14:52:30 +0200},
|
|
| 8 |
- authudate={1443271950},
|
|
| 6 |
+ authsdate={2015-09-27},
|
|
| 7 |
+ authidate={2015-09-27 14:25:22 +0200},
|
|
| 8 |
+ authudate={1443356722},
|
|
| 9 | 9 |
commname={ramon diaz-uriarte (at Bufo)},
|
| 10 | 10 |
commemail={rdiaz02@gmail.com},
|
| 11 |
- commsdate={2015-09-26},
|
|
| 12 |
- commidate={2015-09-26 14:52:30 +0200},
|
|
| 13 |
- commudate={1443271950},
|
|
| 11 |
+ commsdate={2015-09-27},
|
|
| 12 |
+ commidate={2015-09-27 14:25:22 +0200},
|
|
| 13 |
+ commudate={1443356722},
|
|
| 14 | 14 |
refnames={ (HEAD -> master)}
|
| 15 | 15 |
]{gitsetinfo}
|
| 16 | 16 |
\ No newline at end of file |