options(java.parameters = "-Xmx4000M")
library(SELEX)
library(SelexGLM)
library(grid)
workDir = "./cache/"
selex.config(workingDir=workDir, maxThreadNumber=4)
### LOCAL PATHS NEED TO BE RE-DEFINED TO RUN OFF OF MY COMPUTER
##################################################################
selexDir = "/Users/gabriella/Columbia/SELEX/"
rawdataDir = "/Users/gabriella/Columbia/rawdata/Mann/HM/"
# CLUSTER VERSIONS ARE COMMENTED OUT
#selexDir = "/vega/hblab/users/gdm2120/SELEX/SELEX/"
#rawdataDir = "/vega/hblab/projects/selex/rawdata/Mann/hm/"
##################################################################
saveDir = "gabriella/SelexGLMtest/NullNset/"
dir.create(file.path(selexDir, saveDir), showWarnings = FALSE, recursive = TRUE)
shapeTable = read.table(paste(selexDir, "gabriella/ShapeParamData/ShapeTableOrthogonal.txt", sep = ""), sep = "\t",
stringsAsFactors = FALSE)
ST = shapeTable[,c(1, 14:19)]
colnames(ST) = c("Sequence", "MGW", "ProT", "HelTA",
"HelTB", "RollA", "RollB")
selex.defineSample('r0',
paste(rawdataDir, "exp6/mplex1.0b.mplex2.0b.fastq.gz", sep = ""),
'm1r0',
0, 16, 'TGG', 'CCAGCTG')
selex.defineSample('r0',
paste(rawdataDir, "exp6/mplex1.0b.mplex2.0b.fastq.gz", sep = ""),
'm2r0',
0, 16, 'TGG', 'CCACGTC')
selex.defineSample('Ubx4a.R2',
paste(rawdataDir, "exp4/exdUbxiva.exdAntp.L.2.fastq.gz", sep = ""),
'HM.Ubx4a.Exd',
2, 16, 'TGG', 'CCAGCTG')
selex.defineSample('Ubx4a.R3',
paste(rawdataDir,"exp4/exdUbxiva.exdAntp.L.3.fastq.gz", sep = ""),
'HM.Ubx4a.Exd',
3, 16, 'TGG', 'CCAGCTG')
r0.train = selex.sample(seqName = 'r0', sampleName='m1r0', round = 0)
r0.test = selex.sample(seqName = 'r0', sampleName='m2r0', round = 0)
dataSample = selex.sample(seqName = 'Ubx4a.R2', sampleName = 'HM.Ubx4a.Exd', round = 2)
# MARKOV MODEL BUILT
kmax = selex.kmax(sample = r0.test)
# Train Markov model on Hm 16bp library Round 0 data
mm = selex.mm(sample = r0.train, order = NA, crossValidationSample =r0.test, Kmax = kmax, mmMethod = "TRANSITION")
mmscores = selex.mmSummary(sample = r0.train)
ido = which(mmscores$R==max(mmscores$R))
mm.order = mmscores$Order[ido]
libLen = as.numeric(as.character(selex.getAttributes(dataSample)$VariableRegionLength))
# For the sake of previous analysis on the Hox data used in this example, I will use kLen = 12 as my k-mer length, even though kLen identified through the information gain analysis has kLen = 13.
kLen = 12
#data.probeCounts = getProbeCounts(dataSample, markovModel = mm)
#save(data.probeCounts, file = paste(selexDir, saveDir, "/data.probeCounts.RData", sep = ""))
load(file = paste(selexDir, saveDir, "/data.probeCounts.RData", sep = ""))
#data.kmerTable = getKmerCountAffinities(dataSample, k = kLen, minCount = 100, markovModel = mm)
#save(data.kmerTable, file = paste(selexDir, saveDir, "/data.kmerTable.RData", sep = ""))
load(file = paste(selexDir, saveDir, "/data.kmerTable.RData", sep = ""))
DummyModelTest = model(varRegLen = libLen,
leftFixedSeq = "GTTCAGAGTTCTACAGTCCGACGATCTGG",
rightFixedSeq ="CCAGCTGTCGTATGCCGTCTTCTGCTTG",
consensusSeq = "NTGAYNNAYNNN",
affinityType = "AffinitySym",
leftFixedSeqOverlap = 5,
minAffinity = 0.00,
missingValueSuppression = 1,
minSeedValue = .01,
upFootprintExtend = 4,
confidenceLevel = .95,
verbose = FALSE,
includeShape = TRUE,
shapeTable = ST,
shapeParamsUsed = list(c("MGW", "HelT", "Roll", "ProT")),
rounds = list(c(2)),
rcSymmetric = FALSE)
# Add seed model
seedMat = seedTable2psam(DummyModelTest, data.kmerTable)
# Inputs about library are data specific
ModelTest = model(name = "HM-Ubx4a-Exd R2 Shape Model",
varRegLen = libLen,
leftFixedSeq = "GTTCAGAGTTCTACAGTCCGACGATCTGG",
rightFixedSeq ="CCAGCTGTCGTATGCCGTCTTCTGCTTG",
consensusSeq = "NTGAYNNAYNNN",
affinityType = "AffinitySym",
leftFixedSeqOverlap = 5,
minAffinity = 0.00,
missingValueSuppression = 1,
minSeedValue = .01,
upFootprintExtend = 4,
confidenceLevel = .95,
verbose = FALSE,
includeShape = TRUE,
shapeTable = ST,
shapeParamsUsed = list(c("MGW", "HelT", "Roll", "ProT")),
rounds = list(c(2)),
rcSymmetric = FALSE,
N.set = c(0),
N.values = seedMat,
useFixedValuesOffset.N = FALSE)
getFeatureDesign(ModelTest)
## Feature design for object of class 'model'
##
## seedLen: 12
## upFootprintExtend: 4
## downFootprintExtend: 4
## rcSymmetric: FALSE
##
## Slot "N":
## N.upFootprintExtend: 0
## N.downFootprintExtend: 0
## N.set: 0
## Number of previous iterations: 0
##
## Slot "Intercept":
## Number of Views per Strand of DNA: 7
## Number of Rounds: 1 (2)
## Number of previous iterations: 0
##
## Slot "Shape":
## ShapeParamsUsed: HelT MGW ProT Roll
## Shape.upFootprintExtend: 4
## Shape.downFootprintExtend: 4
## Shape.set: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## Number of previous iterations: 0
print(getValues(getN(ModelTest)))
## 1 2 3 4 5 6 7 8 9 10
## N.A 0 0 0 0 0.0000000 -0.8340377 -0.6171102 0.000000 -1.360965 -1.476628
## N.C 0 0 0 0 -0.8162560 -1.8500362 -3.1650820 -2.675131 -1.992603 -2.448111
## N.G 0 0 0 0 -0.2525938 -2.1521858 0.0000000 -2.618543 -1.264517 -2.484039
## N.T 0 0 0 0 -0.4154319 0.0000000 -1.3143951 -2.908717 0.000000 0.000000
## 11 12 13 14 15 16 17 18
## N.A -1.118790 0.000000 -2.022527 -0.86831649 0.0000000 -0.7152829 0 0
## N.C -2.174582 -3.392451 -1.355055 -1.05294403 -1.6266289 0.0000000 0 0
## N.G -1.362605 -2.603949 -1.716115 -0.02638645 -0.0963874 -0.3890593 0 0
## N.T 0.000000 -3.561304 0.000000 0.00000000 -1.0818102 -0.2918482 0 0
## 19 20
## N.A 0 0
## N.C 0 0
## N.G 0 0
## N.T 0 0
plot(ModelTest@features@N, Ntitle = "HM-Ubx4a-Exd R2 Shape\n Nucleotide Seed", ddG = TRUE)
Next we score the probes using topModelMatch
sample1 = sample(nrow(data.probeCounts), 1000000)
data = data.probeCounts[sample1, ]
#data = data.probeCounts
data = topModelMatch(data, ModelTest)
# Uses aligned probes to build design matrix
data = addDesignMatrix(data, ModelTest)
if (nrow(data) > 0) {
designMatrixSummary = getDesignMatrix(ModelTest, data)
print("Round summary: ")
print (designMatrixSummary$Round)
print("Mono-nucleotide summary: ")
print (designMatrixSummary$N)
print("View/strand orientation summary: ")
print (designMatrixSummary$Intercept)
# # Constructs regression expression with independent features using design matrix
regressionFormula = updatedRegressionFormula(data, ModelTest)
print("Regression Formula: ")
print (regressionFormula)
fit = glm(regressionFormula,
data=data,
family = poisson(link="log"))
summary(fit)
ModelTest = addNewBetas(ModelTest, data, fit)
# # Nucleotide Features after first round of fitting
summary(ModelTest)
vPheight = verticalPlot_height(ModelTest)
pM <- plot(ModelTest, plotTitle = "HM-Ubx4a-Exd R2 Shape Fit", Nplot.ddG = TRUE, verticalPlots = TRUE)
ggplot2::ggsave(pM, file = paste(selexDir, saveDir, "/modelPlot.pdf", sep = ""), height = vPheight, width = 6)
ggplot2::ggsave(pM, file = paste(selexDir, saveDir, "/modelPlot.",1, ".pdf", sep = ""), height = vPheight, width = 6)
}
## No nucleotides included in fit.
## [1] "Round summary: "
## 2 Total
## Round 792538 792538
## [1] "Mono-nucleotide summary: "
## <0 x 0 matrix>
## [1] "View/strand orientation summary: "
## View.1 View.2 View.3 View.4 View.5 View.6 View.7 StrandTotal
## Strand.F 49760 81720 75140 68274 68439 68928 81440 493701
## Strand.R 36638 49779 47374 36435 37887 41171 49553 298837
## [1] "Regression Formula: "
## [1] "ObservedCount ~ offset(logProb)+Shape.HelTA1+Shape.HelTB1+Shape.MGW1+Shape.ProT1+Shape.RollA1+Shape.RollB1+Shape.HelTA2+Shape.HelTB2+Shape.MGW2+Shape.ProT2+Shape.RollA2+Shape.RollB2+Shape.HelTA3+Shape.HelTB3+Shape.MGW3+Shape.ProT3+Shape.RollA3+Shape.RollB3+Shape.HelTA4+Shape.HelTB4+Shape.MGW4+Shape.ProT4+Shape.RollA4+Shape.RollB4+Shape.HelTA5+Shape.HelTB5+Shape.MGW5+Shape.ProT5+Shape.RollA5+Shape.RollB5+Shape.HelTA6+Shape.HelTB6+Shape.MGW6+Shape.ProT6+Shape.RollA6+Shape.RollB6+Shape.HelTA7+Shape.HelTB7+Shape.MGW7+Shape.ProT7+Shape.RollA7+Shape.RollB7+Shape.HelTA8+Shape.HelTB8+Shape.MGW8+Shape.ProT8+Shape.RollA8+Shape.RollB8+Shape.HelTA9+Shape.HelTB9+Shape.MGW9+Shape.ProT9+Shape.RollA9+Shape.RollB9+Shape.HelTA10+Shape.HelTB10+Shape.MGW10+Shape.ProT10+Shape.RollA10+Shape.RollB10+Shape.HelTA11+Shape.HelTB11+Shape.MGW11+Shape.ProT11+Shape.RollA11+Shape.RollB11+Shape.HelTA12+Shape.HelTB12+Shape.MGW12+Shape.ProT12+Shape.RollA12+Shape.RollB12+Shape.HelTA13+Shape.HelTB13+Shape.MGW13+Shape.ProT13+Shape.RollA13+Shape.RollB13+Shape.HelTA14+Shape.HelTB14+Shape.MGW14+Shape.ProT14+Shape.RollA14+Shape.RollB14+Shape.HelTA15+Shape.HelTB15+Shape.MGW15+Shape.ProT15+Shape.RollA15+Shape.RollB15+Shape.HelTA16+Shape.HelTB16+Shape.MGW16+Shape.ProT16+Shape.RollA16+Shape.RollB16+Shape.HelTA17+Shape.HelTB17+Shape.MGW17+Shape.ProT17+Shape.RollA17+Shape.RollB17+Shape.HelTA18+Shape.HelTB18+Shape.MGW18+Shape.ProT18+Shape.RollA18+Shape.RollB18+Shape.HelTA19+Shape.HelTB19+Shape.MGW19+Shape.ProT19+Shape.RollA19+Shape.RollB19+Shape.HelTA20+Shape.HelTB20+Shape.MGW20+Shape.ProT20+Shape.RollA20+Shape.RollB20"
## No nucleotides included in fit.
## An object of class 'model'
##
## Slot "name": HM-Ubx4a-Exd R2 Shape Model
## Slot "varRegLen": 16
## Slot "leftFixedSeq": GTTCAGAGTTCTACAGTCCGACGATCTGG
## Slot "rightFixedSeq": CCAGCTGTCGTATGCCGTCTTCTGCTTG
## Slot "leftFixedSeqOverlap": 5
## Slot "rightFixedSeqOverlap": 5
## Slot "confidenceLevel": 0.95
## Slot "minAffinity": 0
## Slot "missingValueSuppression": 1
## Slot "minSeedValue": 0.01
## Slot "seedLen": 12
## Slot "consensusSeq": [ACGT]TGA[CT][ACGT][ACGT]A[CT][ACGT][ACGT][ACGT]
## Slot "upFootprintExtend": 4
## Slot "downFootprintExtend": 4
## Slot "fpLen": 20
##
## Fits a model of footprint length 20 for mono-nucleotide and shape features (shape = HelT, MGW, ProT, Roll) with 7 view(s) per strand of DNA and 1 round(s) of data (round = 2) without reverse complement symmetry.
##
## Slot "regressionFormula": ObservedCount ~ offset(logProb)+Round.2+Shape.HelTA1+Shape.HelTB1+Shape.MGW1+Shape.ProT1+Shape.RollA1+Shape.RollB1+Shape.HelTA2+Shape.HelTB2+Shape.MGW2+Shape.ProT2+Shape.RollA2+Shape.RollB2+Shape.HelTA3+Shape.HelTB3+Shape.MGW3+Shape.ProT3+Shape.RollA3+Shape.RollB3+Shape.HelTA4+Shape.HelTB4+Shape.MGW4+Shape.ProT4+Shape.RollA4+Shape.RollB4+Shape.HelTA5+Shape.HelTB5+Shape.MGW5+Shape.ProT5+Shape.RollA5+Shape.RollB5+Shape.HelTA6+Shape.HelTB6+Shape.MGW6+Shape.ProT6+Shape.RollA6+Shape.RollB6+Shape.HelTA7+Shape.HelTB7+Shape.MGW7+Shape.ProT7+Shape.RollA7+Shape.RollB7+Shape.HelTA8+Shape.HelTB8+Shape.MGW8+Shape.ProT8+Shape.RollA8+Shape.RollB8+Shape.HelTA9+Shape.HelTB9+Shape.MGW9+Shape.ProT9+Shape.RollA9+Shape.RollB9+Shape.HelTA10+Shape.HelTB10+Shape.MGW10+Shape.ProT10+Shape.RollA10+Shape.RollB10+Shape.HelTA11+Shape.HelTB11+Shape.MGW11+Shape.ProT11+Shape.RollA11+Shape.RollB11+Shape.HelTA12+Shape.HelTB12+Shape.MGW12+Shape.ProT12+Shape.RollA12+Shape.RollB12+Shape.HelTA13+Shape.HelTB13+Shape.MGW13+Shape.ProT13+Shape.RollA13+Shape.RollB13+Shape.HelTA14+Shape.HelTB14+Shape.MGW14+Shape.ProT14+Shape.RollA14+Shape.RollB14+Shape.HelTA15+Shape.HelTB15+Shape.MGW15+Shape.ProT15+Shape.RollA15+Shape.RollB15+Shape.HelTA16+Shape.HelTB16+Shape.MGW16+Shape.ProT16+Shape.RollA16+Shape.RollB16+Shape.HelTA17+Shape.HelTB17+Shape.MGW17+Shape.ProT17+Shape.RollA17+Shape.RollB17+Shape.HelTA18+Shape.HelTB18+Shape.MGW18+Shape.ProT18+Shape.RollA18+Shape.RollB18+Shape.HelTA19+Shape.HelTB19+Shape.MGW19+Shape.ProT19+Shape.RollA19+Shape.RollB19+Shape.HelTA20+Shape.HelTB20+Shape.MGW20+Shape.ProT20+Shape.RollA20+Shape.RollB20
##
## Slot "shapeParamsUsed[[1]]": HelT MGW ProT Roll
##
## Includes the following feature sub-classes:
## An object of class 'N'
## Fits 1 nucleotides for a feature model of length 20.
## Nucleotide beta values:
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## N.A 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.C 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.G 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.T 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
## Nucleotide beta errors:
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## N.A 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.C 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.G 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.T 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
##
## An object of class 'Intercept'
## Fits intercept(s) for 1 round(s) (round = 2).
## Intercept beta values:
## Round.2:
## [1] 13.06023
##
## Intercept beta errors:
## Round.2:
## [1] 0.0168602
##
##
##
## An object of class 'Shape'
## Fits 120 shape coefficients for 6 kinds of shape parameter(s) (shape = HelT, MGW, ProT, Roll) for a feature model of length 20.
## Shape beta values:
## 1 2 3 4 5
## Shape.HelTA -0.03213169 0.007566734 -0.03403011 -0.046426487 -0.06039012
## Shape.HelTB -0.02293470 0.016285407 0.01245720 0.072361914 -0.04263033
## Shape.MGW -0.18104786 -0.214850829 -0.23294283 -0.200238983 -0.01904571
## Shape.ProT 0.02265717 -0.004921504 0.01463848 -0.003539122 -0.01162015
## Shape.RollA -0.01209981 0.015107093 0.01803699 0.011069969 -0.03517938
## Shape.RollB 0.02633576 0.024623872 0.01992907 0.061737036 -0.03401991
## 6 7 8 9 10
## Shape.HelTA 0.244758220 0.35370755 -0.550574609 -1.2351624 -2.0684354
## Shape.HelTB -0.228008812 -0.23222373 0.927338730 1.5495694 -0.8401631
## Shape.MGW -0.147302458 -0.03393116 -2.035411927 1.4474389 -0.9602375
## Shape.ProT 0.074470448 0.15805637 0.004540317 -0.1392345 -0.3171513
## Shape.RollA 0.197353085 0.13061650 0.048350670 -1.1570448 -0.5460803
## Shape.RollB -0.004007246 -0.39388989 1.278284904 0.4165572 0.4826933
## 11 12 13 14 15
## Shape.HelTA -0.8062143 -0.393163884 -0.239374298 0.08237441 0.13816179
## Shape.HelTB -0.8063984 -0.318595758 0.036598162 -0.32720029 -0.12721371
## Shape.MGW -2.3328125 1.882200902 1.242187734 0.02621601 -0.41279524
## Shape.ProT -0.8438939 -0.269945266 0.077742253 -0.19552138 0.09196883
## Shape.RollA -0.4220921 -0.118412474 -0.150121587 -0.07364690 0.06545442
## Shape.RollB 0.3093489 0.001824568 -0.002530948 -0.11326018 0.03471493
## 16 17 18 19
## Shape.HelTA 0.07804540 0.030053613 0.016513164 -0.005730738
## Shape.HelTB -0.08868946 -0.075009052 -0.023206329 -0.026162796
## Shape.MGW 0.29845425 -0.113303863 0.005741774 -0.135074528
## Shape.ProT -0.03322840 -0.001867282 -0.004811656 0.003843030
## Shape.RollA 0.01808486 0.053653276 0.005253835 0.043843103
## Shape.RollB -0.07097933 -0.026371548 -0.036783736 -0.064045023
## 20
## Shape.HelTA 0.0111321602
## Shape.HelTB -0.0009187715
## Shape.MGW -0.1719388949
## Shape.ProT 0.0206734482
## Shape.RollA 0.0650153081
## Shape.RollB -0.0134425652
##
## Shape beta errors:
## 1 2 3 4
## Shape.HelTA 0.0009790527 0.0019025485 0.0017457059 0.0016764458
## Shape.HelTB 0.0020700227 0.0019282281 0.0017134281 0.0022847346
## Shape.MGW 0.0043162073 0.0046090142 0.0042137805 0.0049314205
## Shape.ProT 0.0005406453 0.0005255629 0.0005107163 0.0005258964
## Shape.RollA 0.0006232436 0.0012630603 0.0011324846 0.0010904212
## Shape.RollB 0.0013548316 0.0011594730 0.0010678312 0.0011071623
## 5 6 7 8 9
## Shape.HelTA 0.002340948 0.002133858 0.003234755 0.006960329 0.013631055
## Shape.HelTB 0.002189548 0.002765692 0.005524655 0.013096787 0.010709147
## Shape.MGW 0.005236629 0.004832134 0.009064814 0.021093978 0.027667004
## Shape.ProT 0.000779140 0.001261402 0.001197024 0.003414486 0.004640425
## Shape.RollA 0.001055678 0.001620312 0.001211837 0.003224533 0.005212795
## Shape.RollB 0.001550774 0.001183127 0.003005021 0.005783745 0.007948613
## 10 11 12 13 14
## Shape.HelTA 0.007334446 0.015715809 0.012482259 0.005362969 0.0027974886
## Shape.HelTB 0.016427711 0.013723550 0.008872356 0.002705727 0.0019315176
## Shape.MGW 0.040455991 0.040071001 0.028143998 0.008604131 0.0049015470
## Shape.ProT 0.005341574 0.005797835 0.004545172 0.001579127 0.0007628626
## Shape.RollA 0.008491315 0.006724114 0.004721404 0.002989634 0.0011480864
## Shape.RollB 0.006457200 0.004038077 0.004835257 0.001107969 0.0009434987
## 15 16 17 18
## Shape.HelTA 0.001921438 0.0023185684 0.0018704554 0.0017876381
## Shape.HelTB 0.002168604 0.0018512088 0.0016905047 0.0018795426
## Shape.MGW 0.004903397 0.0048667051 0.0046862585 0.0044891415
## Shape.ProT 0.000544890 0.0004932381 0.0004967262 0.0005270896
## Shape.RollA 0.001013125 0.0012243288 0.0010530801 0.0011041244
## Shape.RollB 0.001218460 0.0010711591 0.0011100396 0.0012047307
## 19 20
## Shape.HelTA 0.0020448699 0.0021412102
## Shape.HelTB 0.0019955391 0.0011233292
## Shape.MGW 0.0048640830 0.0047730039
## Shape.ProT 0.0005590609 0.0005715216
## Shape.RollA 0.0012555034 0.0014892060
## Shape.RollB 0.0013913199 0.0007345422
data = data.probeCounts[sample1, ]
#data = data.probeCounts
data.nrow = nrow(data)
data = topModelMatch(data, ModelTest)
data = addDesignMatrix(data, ModelTest)
if (nrow(data) > 0) {
designMatrixSummary.v2 = getDesignMatrix(ModelTest, data)
if ((all(designMatrixSummary.v2$N == designMatrixSummary$N)) & (all(designMatrixSummary.v2$Round == designMatrixSummary$Round)) & (all(designMatrixSummary.v2$Intercept == designMatrixSummary$Intercept))) {
print ("Stability Reached")
}
}
## No nucleotides included in fit.
for (i in 2:20) {
if (nrow(data) == 0) {
break
} else if ((all(designMatrixSummary.v2$N == designMatrixSummary$N)) & (all(designMatrixSummary.v2$Round == designMatrixSummary$Round)) & (all(designMatrixSummary.v2$Intercept == designMatrixSummary$Intercept))) {
break
}
data.nrow = nrow(data)
print (paste("i =",i))
designMatrixSummary = getDesignMatrix(ModelTest, data)
print("Round summary: ")
print (designMatrixSummary$Round)
print("Mono-nucleotide summary: ")
print (designMatrixSummary$N)
print("View/strand orientation summary: ")
print (designMatrixSummary$Intercept)
# # Constructs regression expression with independent features using design matrix
regressionFormula = updatedRegressionFormula(data, ModelTest)
print("Regression Formula: ")
print (regressionFormula)
fit = glm(regressionFormula,
data=data,
family = poisson(link="log"))
summary(fit)
ModelTest = addNewBetas(ModelTest, data, fit)
# # Nucleotide Features after first round of fitting
summary(ModelTest)
pM <- plot(ModelTest, plotTitle = "HM-Ubx4a-Exd R2 Shape Fit", Nplot.ddG = TRUE, verticalPlots = TRUE)
ggplot2::ggsave(pM, file = paste(selexDir, saveDir, "/modelPlot.pdf", sep = ""), height = vPheight, width = 6)
ggplot2::ggsave(pM, file = paste(selexDir, saveDir, "/modelPlot.",i, ".pdf", sep = ""), height = vPheight, width = 6)
data = topModelMatch(data, ModelTest)
data = addDesignMatrix(data, ModelTest)
print(paste("Number of Observations in Design Matrix: ",nrow(data), sep = ""))
if (nrow(data) > 0) {
designMatrixSummary.v2 = getDesignMatrix(ModelTest, data)
if ((all(designMatrixSummary.v2$N == designMatrixSummary$N)) & (all(designMatrixSummary.v2$Round == designMatrixSummary$Round)) & (all(designMatrixSummary.v2$Intercept == designMatrixSummary$Intercept))) {
print (paste("Stability Reached after ", i, " iterations.", sep = ""))
break
}
} else {
print (paste("Algorithm failed to converge: No probes meet the confidence level requirement (Confidence Level:", ModelTest@confidenceLevel, ")", sep = ""))
}
}
## [1] "i = 2"
## No nucleotides included in fit.
## [1] "Round summary: "
## 2 Total
## Round 263359 263359
## [1] "Mono-nucleotide summary: "
## <0 x 0 matrix>
## [1] "View/strand orientation summary: "
## View.1 View.2 View.3 View.4 View.5 View.6 View.7 StrandTotal
## Strand.F 16870 22985 21282 16985 18793 18738 22410 138063
## Strand.R 15572 17500 17770 14917 16757 21051 21729 125296
## [1] "Regression Formula: "
## [1] "ObservedCount ~ offset(logProb)+Shape.HelTA1+Shape.HelTB1+Shape.MGW1+Shape.ProT1+Shape.RollA1+Shape.RollB1+Shape.HelTA2+Shape.HelTB2+Shape.MGW2+Shape.ProT2+Shape.RollA2+Shape.RollB2+Shape.HelTA3+Shape.HelTB3+Shape.MGW3+Shape.ProT3+Shape.RollA3+Shape.RollB3+Shape.HelTA4+Shape.HelTB4+Shape.MGW4+Shape.ProT4+Shape.RollA4+Shape.RollB4+Shape.HelTA5+Shape.HelTB5+Shape.MGW5+Shape.ProT5+Shape.RollA5+Shape.RollB5+Shape.HelTA6+Shape.HelTB6+Shape.MGW6+Shape.ProT6+Shape.RollA6+Shape.RollB6+Shape.HelTA7+Shape.HelTB7+Shape.MGW7+Shape.ProT7+Shape.RollA7+Shape.RollB7+Shape.HelTA8+Shape.HelTB8+Shape.MGW8+Shape.ProT8+Shape.RollA8+Shape.RollB8+Shape.HelTA9+Shape.HelTB9+Shape.MGW9+Shape.ProT9+Shape.RollA9+Shape.RollB9+Shape.HelTA10+Shape.HelTB10+Shape.MGW10+Shape.ProT10+Shape.RollA10+Shape.RollB10+Shape.HelTA11+Shape.HelTB11+Shape.MGW11+Shape.ProT11+Shape.RollA11+Shape.RollB11+Shape.HelTA12+Shape.HelTB12+Shape.MGW12+Shape.ProT12+Shape.RollA12+Shape.RollB12+Shape.HelTA13+Shape.HelTB13+Shape.MGW13+Shape.ProT13+Shape.RollA13+Shape.RollB13+Shape.HelTA14+Shape.HelTB14+Shape.MGW14+Shape.ProT14+Shape.RollA14+Shape.RollB14+Shape.HelTA15+Shape.HelTB15+Shape.MGW15+Shape.ProT15+Shape.RollA15+Shape.RollB15+Shape.HelTA16+Shape.HelTB16+Shape.MGW16+Shape.ProT16+Shape.RollA16+Shape.RollB16+Shape.HelTA17+Shape.HelTB17+Shape.MGW17+Shape.ProT17+Shape.RollA17+Shape.RollB17+Shape.HelTA18+Shape.HelTB18+Shape.MGW18+Shape.ProT18+Shape.RollA18+Shape.RollB18+Shape.HelTA19+Shape.HelTB19+Shape.MGW19+Shape.ProT19+Shape.RollA19+Shape.RollB19+Shape.HelTA20+Shape.HelTB20+Shape.MGW20+Shape.ProT20+Shape.RollA20+Shape.RollB20"
## No nucleotides included in fit.
## An object of class 'model'
##
## Slot "name": HM-Ubx4a-Exd R2 Shape Model
## Slot "varRegLen": 16
## Slot "leftFixedSeq": GTTCAGAGTTCTACAGTCCGACGATCTGG
## Slot "rightFixedSeq": CCAGCTGTCGTATGCCGTCTTCTGCTTG
## Slot "leftFixedSeqOverlap": 5
## Slot "rightFixedSeqOverlap": 5
## Slot "confidenceLevel": 0.95
## Slot "minAffinity": 0
## Slot "missingValueSuppression": 1
## Slot "minSeedValue": 0.01
## Slot "seedLen": 12
## Slot "consensusSeq": [ACGT]TGA[CT][ACGT][ACGT]A[CT][ACGT][ACGT][ACGT]
## Slot "upFootprintExtend": 4
## Slot "downFootprintExtend": 4
## Slot "fpLen": 20
##
## Fits a model of footprint length 20 for mono-nucleotide and shape features (shape = HelT, MGW, ProT, Roll) with 7 view(s) per strand of DNA and 1 round(s) of data (round = 2) without reverse complement symmetry.
##
## Slot "regressionFormula": ObservedCount ~ offset(logProb)+Round.2+Shape.HelTA1+Shape.HelTB1+Shape.MGW1+Shape.ProT1+Shape.RollA1+Shape.RollB1+Shape.HelTA2+Shape.HelTB2+Shape.MGW2+Shape.ProT2+Shape.RollA2+Shape.RollB2+Shape.HelTA3+Shape.HelTB3+Shape.MGW3+Shape.ProT3+Shape.RollA3+Shape.RollB3+Shape.HelTA4+Shape.HelTB4+Shape.MGW4+Shape.ProT4+Shape.RollA4+Shape.RollB4+Shape.HelTA5+Shape.HelTB5+Shape.MGW5+Shape.ProT5+Shape.RollA5+Shape.RollB5+Shape.HelTA6+Shape.HelTB6+Shape.MGW6+Shape.ProT6+Shape.RollA6+Shape.RollB6+Shape.HelTA7+Shape.HelTB7+Shape.MGW7+Shape.ProT7+Shape.RollA7+Shape.RollB7+Shape.HelTA8+Shape.HelTB8+Shape.MGW8+Shape.ProT8+Shape.RollA8+Shape.RollB8+Shape.HelTA9+Shape.HelTB9+Shape.MGW9+Shape.ProT9+Shape.RollA9+Shape.RollB9+Shape.HelTA10+Shape.HelTB10+Shape.MGW10+Shape.ProT10+Shape.RollA10+Shape.RollB10+Shape.HelTA11+Shape.HelTB11+Shape.MGW11+Shape.ProT11+Shape.RollA11+Shape.RollB11+Shape.HelTA12+Shape.HelTB12+Shape.MGW12+Shape.ProT12+Shape.RollA12+Shape.RollB12+Shape.HelTA13+Shape.HelTB13+Shape.MGW13+Shape.ProT13+Shape.RollA13+Shape.RollB13+Shape.HelTA14+Shape.HelTB14+Shape.MGW14+Shape.ProT14+Shape.RollA14+Shape.RollB14+Shape.HelTA15+Shape.HelTB15+Shape.MGW15+Shape.ProT15+Shape.RollA15+Shape.RollB15+Shape.HelTA16+Shape.HelTB16+Shape.MGW16+Shape.ProT16+Shape.RollA16+Shape.RollB16+Shape.HelTA17+Shape.HelTB17+Shape.MGW17+Shape.ProT17+Shape.RollA17+Shape.RollB17+Shape.HelTA18+Shape.HelTB18+Shape.MGW18+Shape.ProT18+Shape.RollA18+Shape.RollB18+Shape.HelTA19+Shape.HelTB19+Shape.MGW19+Shape.ProT19+Shape.RollA19+Shape.RollB19+Shape.HelTA20+Shape.HelTB20+Shape.MGW20+Shape.ProT20+Shape.RollA20+Shape.RollB20
##
## Slot "shapeParamsUsed[[1]]": HelT MGW ProT Roll
##
## Includes the following feature sub-classes:
## An object of class 'N'
## Fits 1 nucleotides for a feature model of length 20.
## Nucleotide beta values:
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## N.A 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.C 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.G 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.T 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
## Nucleotide beta errors:
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## N.A 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.C 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.G 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.T 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
##
## An object of class 'Intercept'
## Fits intercept(s) for 1 round(s) (round = 2).
## Intercept beta values:
## Round.2:
## [1] 12.76886
##
## Intercept beta errors:
## Round.2:
## [1] 0.03116927
##
##
##
## An object of class 'Shape'
## Fits 120 shape coefficients for 6 kinds of shape parameter(s) (shape = HelT, MGW, ProT, Roll) for a feature model of length 20.
## Shape beta values:
## 1 2 3 4
## Shape.HelTA -0.036411404 -0.010233133 -0.040286084 -0.0450877395
## Shape.HelTB -0.005696447 0.024412728 0.008111593 0.0524442305
## Shape.MGW -0.193506422 -0.220605019 -0.203981323 -0.2101902851
## Shape.ProT 0.021853587 -0.006064284 0.016824436 -0.0108335416
## Shape.RollA -0.010382248 0.002146366 0.011619105 0.0004576441
## Shape.RollB 0.036433463 0.029339874 0.030167717 0.0646414176
## 5 6 7 8 9
## Shape.HelTA -0.07559339 0.27451940 0.11599695 -1.20947888 -0.31698554
## Shape.HelTB -0.09475673 -0.20732892 -0.10836355 -1.16642807 -0.09098958
## Shape.MGW 0.02231218 -0.05476925 -0.87437170 -1.57889735 1.42736540
## Shape.ProT -0.02892237 0.06491849 0.06976166 -0.47457280 -0.37013298
## Shape.RollA -0.06805138 0.16851766 0.09913961 -0.03843852 -0.45552229
## Shape.RollB -0.03692524 0.05259263 -0.17152537 0.30775352 0.01045572
## 10 11 12 13 14
## Shape.HelTA -0.246732356 -0.4087110 0.06201330 -0.313019743 -0.06285077
## Shape.HelTB 0.001335277 -0.8947546 -0.21538223 0.123010561 -0.43336767
## Shape.MGW -3.166683945 -1.9155758 0.73231049 1.858105562 -0.06557738
## Shape.ProT 0.069904511 -0.3081586 -0.07700509 -0.052086857 -0.19946564
## Shape.RollA 0.031752639 -0.0714215 0.12437230 -0.289594699 -0.06708812
## Shape.RollB 0.555408512 0.1575331 0.05318778 0.007870967 -0.15162511
## 15 16 17 18 19
## Shape.HelTA 0.21022875 0.09790595 0.023568267 0.015674713 -0.016889001
## Shape.HelTB -0.14274330 -0.09675400 -0.073603607 -0.009216756 -0.027962356
## Shape.MGW -0.25033772 0.19581511 -0.121656585 0.024123009 -0.134716550
## Shape.ProT 0.06895883 -0.02619448 -0.001344503 -0.002484433 0.004679428
## Shape.RollA 0.07983036 0.03530842 0.038475679 -0.002368629 0.040448811
## Shape.RollB 0.01227838 -0.05810371 -0.015284036 -0.031054380 -0.055166399
## 20
## Shape.HelTA 0.015429875
## Shape.HelTB -0.004942770
## Shape.MGW -0.194050018
## Shape.ProT 0.023722082
## Shape.RollA 0.057763978
## Shape.RollB -0.006113503
##
## Shape beta errors:
## 1 2 3 4 5
## Shape.HelTA 0.0012515272 0.0024619914 0.002241270 0.0023004204 0.003119425
## Shape.HelTB 0.0026540491 0.0024659673 0.002317226 0.0030391805 0.003053710
## Shape.MGW 0.0055597017 0.0058382937 0.005524098 0.0062904845 0.007048680
## Shape.ProT 0.0006895719 0.0006756929 0.000659689 0.0006904463 0.001075447
## Shape.RollA 0.0008064727 0.0015926888 0.001479564 0.0013957799 0.001434039
## Shape.RollB 0.0017252733 0.0015095473 0.001397158 0.0014824167 0.002135426
## 6 7 8 9 10
## Shape.HelTA 0.003019229 0.005059144 0.009592051 0.017367935 0.008804131
## Shape.HelTB 0.003784798 0.007198635 0.016342399 0.016138762 0.021454522
## Shape.MGW 0.006545368 0.012956007 0.029951491 0.032281978 0.042325772
## Shape.ProT 0.001841360 0.001565977 0.004546738 0.007582019 0.004125389
## Shape.RollA 0.002229936 0.001886759 0.004731737 0.006672021 0.008565051
## Shape.RollB 0.001679704 0.004194146 0.005722096 0.008722937 0.008042647
## 11 12 13 14 15
## Shape.HelTA 0.018323548 0.014904370 0.006900926 0.003776254 0.0025497347
## Shape.HelTB 0.016386804 0.008616398 0.003655170 0.002600893 0.0028937794
## Shape.MGW 0.039461544 0.028625394 0.010514716 0.006204770 0.0064943019
## Shape.ProT 0.004741065 0.004192529 0.001943930 0.001002192 0.0007207032
## Shape.RollA 0.007038334 0.004969246 0.003756787 0.001485886 0.0013818932
## Shape.RollB 0.004937456 0.004594441 0.001454851 0.001241162 0.0016230370
## 16 17 18 19
## Shape.HelTA 0.0031052676 0.0024115536 0.0022745193 0.0025202615
## Shape.HelTB 0.0023938035 0.0021549149 0.0023195748 0.0024408038
## Shape.MGW 0.0062273893 0.0058795263 0.0056766796 0.0060800751
## Shape.ProT 0.0006272193 0.0006188501 0.0006550363 0.0006910134
## Shape.RollA 0.0016399050 0.0013566694 0.0014175064 0.0015723884
## Shape.RollB 0.0013653436 0.0014057334 0.0015055396 0.0017288925
## 20
## Shape.HelTA 0.0026198069
## Shape.HelTB 0.0013966607
## Shape.MGW 0.0059116458
## Shape.ProT 0.0007082487
## Shape.RollA 0.0018447575
## Shape.RollB 0.0009104661
##
## [1] "Number of Observations in Design Matrix: 193409"
## No nucleotides included in fit.
## [1] "i = 3"
## No nucleotides included in fit.
## [1] "Round summary: "
## 2 Total
## Round 193409 193409
## [1] "Mono-nucleotide summary: "
## <0 x 0 matrix>
## [1] "View/strand orientation summary: "
## View.1 View.2 View.3 View.4 View.5 View.6 View.7 StrandTotal
## Strand.F 13628 19463 17570 13545 14852 13773 15896 108727
## Strand.R 11450 13283 12915 10144 11567 12620 12703 84682
## [1] "Regression Formula: "
## [1] "ObservedCount ~ offset(logProb)+Shape.HelTA1+Shape.HelTB1+Shape.MGW1+Shape.ProT1+Shape.RollA1+Shape.RollB1+Shape.HelTA2+Shape.HelTB2+Shape.MGW2+Shape.ProT2+Shape.RollA2+Shape.RollB2+Shape.HelTA3+Shape.HelTB3+Shape.MGW3+Shape.ProT3+Shape.RollA3+Shape.RollB3+Shape.HelTA4+Shape.HelTB4+Shape.MGW4+Shape.ProT4+Shape.RollA4+Shape.RollB4+Shape.HelTA5+Shape.HelTB5+Shape.MGW5+Shape.ProT5+Shape.RollA5+Shape.RollB5+Shape.HelTA6+Shape.HelTB6+Shape.MGW6+Shape.ProT6+Shape.RollA6+Shape.RollB6+Shape.HelTA7+Shape.HelTB7+Shape.MGW7+Shape.ProT7+Shape.RollA7+Shape.RollB7+Shape.HelTA8+Shape.HelTB8+Shape.MGW8+Shape.ProT8+Shape.RollA8+Shape.RollB8+Shape.HelTA9+Shape.HelTB9+Shape.MGW9+Shape.ProT9+Shape.RollA9+Shape.RollB9+Shape.HelTA10+Shape.HelTB10+Shape.MGW10+Shape.ProT10+Shape.RollA10+Shape.RollB10+Shape.HelTA11+Shape.HelTB11+Shape.MGW11+Shape.ProT11+Shape.RollA11+Shape.RollB11+Shape.HelTA12+Shape.HelTB12+Shape.MGW12+Shape.ProT12+Shape.RollA12+Shape.RollB12+Shape.HelTA13+Shape.HelTB13+Shape.MGW13+Shape.ProT13+Shape.RollA13+Shape.RollB13+Shape.HelTA14+Shape.HelTB14+Shape.MGW14+Shape.ProT14+Shape.RollA14+Shape.RollB14+Shape.HelTA15+Shape.HelTB15+Shape.MGW15+Shape.ProT15+Shape.RollA15+Shape.RollB15+Shape.HelTA16+Shape.HelTB16+Shape.MGW16+Shape.ProT16+Shape.RollA16+Shape.RollB16+Shape.HelTA17+Shape.HelTB17+Shape.MGW17+Shape.ProT17+Shape.RollA17+Shape.RollB17+Shape.HelTA18+Shape.HelTB18+Shape.MGW18+Shape.ProT18+Shape.RollA18+Shape.RollB18+Shape.HelTA19+Shape.HelTB19+Shape.MGW19+Shape.ProT19+Shape.RollA19+Shape.RollB19+Shape.HelTA20+Shape.HelTB20+Shape.MGW20+Shape.ProT20+Shape.RollA20+Shape.RollB20"
## No nucleotides included in fit.
## An object of class 'model'
##
## Slot "name": HM-Ubx4a-Exd R2 Shape Model
## Slot "varRegLen": 16
## Slot "leftFixedSeq": GTTCAGAGTTCTACAGTCCGACGATCTGG
## Slot "rightFixedSeq": CCAGCTGTCGTATGCCGTCTTCTGCTTG
## Slot "leftFixedSeqOverlap": 5
## Slot "rightFixedSeqOverlap": 5
## Slot "confidenceLevel": 0.95
## Slot "minAffinity": 0
## Slot "missingValueSuppression": 1
## Slot "minSeedValue": 0.01
## Slot "seedLen": 12
## Slot "consensusSeq": [ACGT]TGA[CT][ACGT][ACGT]A[CT][ACGT][ACGT][ACGT]
## Slot "upFootprintExtend": 4
## Slot "downFootprintExtend": 4
## Slot "fpLen": 20
##
## Fits a model of footprint length 20 for mono-nucleotide and shape features (shape = HelT, MGW, ProT, Roll) with 7 view(s) per strand of DNA and 1 round(s) of data (round = 2) without reverse complement symmetry.
##
## Slot "regressionFormula": ObservedCount ~ offset(logProb)+Round.2+Shape.HelTA1+Shape.HelTB1+Shape.MGW1+Shape.ProT1+Shape.RollA1+Shape.RollB1+Shape.HelTA2+Shape.HelTB2+Shape.MGW2+Shape.ProT2+Shape.RollA2+Shape.RollB2+Shape.HelTA3+Shape.HelTB3+Shape.MGW3+Shape.ProT3+Shape.RollA3+Shape.RollB3+Shape.HelTA4+Shape.HelTB4+Shape.MGW4+Shape.ProT4+Shape.RollA4+Shape.RollB4+Shape.HelTA5+Shape.HelTB5+Shape.MGW5+Shape.ProT5+Shape.RollA5+Shape.RollB5+Shape.HelTA6+Shape.HelTB6+Shape.MGW6+Shape.ProT6+Shape.RollA6+Shape.RollB6+Shape.HelTA7+Shape.HelTB7+Shape.MGW7+Shape.ProT7+Shape.RollA7+Shape.RollB7+Shape.HelTA8+Shape.HelTB8+Shape.MGW8+Shape.ProT8+Shape.RollA8+Shape.RollB8+Shape.HelTA9+Shape.HelTB9+Shape.MGW9+Shape.ProT9+Shape.RollA9+Shape.RollB9+Shape.HelTA10+Shape.HelTB10+Shape.MGW10+Shape.ProT10+Shape.RollA10+Shape.RollB10+Shape.HelTA11+Shape.HelTB11+Shape.MGW11+Shape.ProT11+Shape.RollA11+Shape.RollB11+Shape.HelTA12+Shape.HelTB12+Shape.MGW12+Shape.ProT12+Shape.RollA12+Shape.RollB12+Shape.HelTA13+Shape.HelTB13+Shape.MGW13+Shape.ProT13+Shape.RollA13+Shape.RollB13+Shape.HelTA14+Shape.HelTB14+Shape.MGW14+Shape.ProT14+Shape.RollA14+Shape.RollB14+Shape.HelTA15+Shape.HelTB15+Shape.MGW15+Shape.ProT15+Shape.RollA15+Shape.RollB15+Shape.HelTA16+Shape.HelTB16+Shape.MGW16+Shape.ProT16+Shape.RollA16+Shape.RollB16+Shape.HelTA17+Shape.HelTB17+Shape.MGW17+Shape.ProT17+Shape.RollA17+Shape.RollB17+Shape.HelTA18+Shape.HelTB18+Shape.MGW18+Shape.ProT18+Shape.RollA18+Shape.RollB18+Shape.HelTA19+Shape.HelTB19+Shape.MGW19+Shape.ProT19+Shape.RollA19+Shape.RollB19+Shape.HelTA20+Shape.HelTB20+Shape.MGW20+Shape.ProT20+Shape.RollA20+Shape.RollB20
##
## Slot "shapeParamsUsed[[1]]": HelT MGW ProT Roll
##
## Includes the following feature sub-classes:
## An object of class 'N'
## Fits 1 nucleotides for a feature model of length 20.
## Nucleotide beta values:
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## N.A 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.C 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.G 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.T 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
## Nucleotide beta errors:
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## N.A 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.C 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.G 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.T 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
##
## An object of class 'Intercept'
## Fits intercept(s) for 1 round(s) (round = 2).
## Intercept beta values:
## Round.2:
## [1] -3.687396
##
## Intercept beta errors:
## Round.2:
## [1] 0.1972141
##
##
##
## An object of class 'Shape'
## Fits 120 shape coefficients for 6 kinds of shape parameter(s) (shape = HelT, MGW, ProT, Roll) for a feature model of length 20.
## Shape beta values:
## 1 2 3 4
## Shape.HelTA -0.03460679 -0.0003561758 -0.036418776 -0.046274178
## Shape.HelTB -0.02470951 0.0069609299 0.005361783 0.070411505
## Shape.MGW -0.17092614 -0.1752161101 -0.202220729 -0.220334188
## Shape.ProT 0.02122648 -0.0115930687 0.015020457 -0.015164678
## Shape.RollA -0.01552598 0.0081241935 0.022448184 0.006680466
## Shape.RollB 0.02458163 0.0100969297 0.018678129 0.062305632
## 5 6 7 8 9
## Shape.HelTA -0.11394270 0.2375587163 0.19437262 -1.7783424 -2.9008702
## Shape.HelTB -0.06623053 -0.2415709003 -0.65215115 -1.5307531 0.6503527
## Shape.MGW 0.03372244 0.0918448059 0.20072682 -4.0368138 -4.4442465
## Shape.ProT -0.02125545 0.0002398673 0.24051915 -0.8508409 -1.1296966
## Shape.RollA -0.06873112 0.1323235496 0.02691624 0.2360307 -0.2778476
## Shape.RollB -0.05318367 0.0119145483 -0.56844885 0.7931579 1.1077416
## 10 11 12 13 14
## Shape.HelTA 0.4034551 -3.7879318 -1.4877797 -0.816927885 -0.10833469
## Shape.HelTB 3.8843979 -0.6945354 -0.5981546 -0.036688275 -0.40815120
## Shape.MGW -9.3989989 -4.6872851 1.1003855 1.812021025 0.01653693
## Shape.ProT 0.5824075 -0.2012984 -0.4565620 -0.169795194 -0.20837515
## Shape.RollA -0.7371922 -0.8862788 -0.2820358 -0.475381708 -0.07663986
## Shape.RollB 3.0319968 1.0748519 0.1458420 0.003858131 -0.16306290
## 15 16 17 18 19
## Shape.HelTA 0.16189075 0.08018288 0.01069106 0.019482273 -0.017389071
## Shape.HelTB -0.11647439 -0.08267403 -0.07779219 -0.005780262 -0.023554397
## Shape.MGW -0.29624422 0.22190351 -0.09467683 0.027549740 -0.145910702
## Shape.ProT 0.06940375 -0.02465600 -0.00361482 -0.002155311 0.003615328
## Shape.RollA 0.06162259 0.00548616 0.02663883 -0.005443421 0.039912430
## Shape.RollB 0.04349019 -0.04567800 -0.01352000 -0.031023215 -0.055119756
## 20
## Shape.HelTA 0.012626861
## Shape.HelTB -0.002409107
## Shape.MGW -0.188007582
## Shape.ProT 0.023239016
## Shape.RollA 0.058449914
## Shape.RollB -0.009021939
##
## Shape beta errors:
## 1 2 3 4
## Shape.HelTA 0.0012819656 0.0025216764 0.0023083531 0.0023399023
## Shape.HelTB 0.0027240169 0.0025496396 0.0023565032 0.0031720147
## Shape.MGW 0.0056932510 0.0060555192 0.0057149580 0.0065311716
## Shape.ProT 0.0007081189 0.0006921736 0.0006755019 0.0007186162
## Shape.RollA 0.0008296101 0.0016439490 0.0015370575 0.0014476284
## Shape.RollB 0.0017752127 0.0015648073 0.0014435132 0.0015442041
## 5 6 7 8 9
## Shape.HelTA 0.003352367 0.003806381 0.006559617 0.020078564 0.03738246
## Shape.HelTB 0.003429644 0.004403754 0.015007714 0.026124051 0.05228603
## Shape.MGW 0.007494667 0.007567427 0.019115431 0.066165732 0.10802922
## Shape.ProT 0.001224013 0.002713762 0.002847428 0.010449067 0.02793661
## Shape.RollA 0.001509233 0.002488963 0.002558438 0.009459464 0.02191367
## Shape.RollB 0.002309901 0.002136700 0.010363610 0.016953614 0.02814447
## 10 11 12 13 14
## Shape.HelTA 0.02369130 0.07203113 0.02706179 0.010986299 0.004173785
## Shape.HelTB 0.08037038 0.02216450 0.02419394 0.004753268 0.002986987
## Shape.MGW 0.12965139 0.09512855 0.06160420 0.015097506 0.006591605
## Shape.ProT 0.01380598 0.01353418 0.01185309 0.003523605 0.001173933
## Shape.RollA 0.03069190 0.01832371 0.01421227 0.005254150 0.001687280
## Shape.RollB 0.03394135 0.01627773 0.01186949 0.001754626 0.001327107
## 15 16 17 18
## Shape.HelTA 0.0029216563 0.0032546330 0.0024669067 0.0022957508
## Shape.HelTB 0.0030271481 0.0024536853 0.0021753777 0.0023649592
## Shape.MGW 0.0068585455 0.0064416224 0.0060518597 0.0057895329
## Shape.ProT 0.0007962717 0.0006500121 0.0006314906 0.0006657716
## Shape.RollA 0.0015104519 0.0017175936 0.0013992796 0.0014425925
## Shape.RollB 0.0017137990 0.0014154880 0.0014368170 0.0015420137
## 19 20
## Shape.HelTA 0.0025706459 0.0026592003
## Shape.HelTB 0.0024796720 0.0014302358
## Shape.MGW 0.0062004944 0.0060326696
## Shape.ProT 0.0007024556 0.0007213918
## Shape.RollA 0.0016054580 0.0018832217
## Shape.RollB 0.0017678335 0.0009337037
##
## [1] "Number of Observations in Design Matrix: 186835"
## No nucleotides included in fit.
## [1] "i = 4"
## No nucleotides included in fit.
## [1] "Round summary: "
## 2 Total
## Round 186835 186835
## [1] "Mono-nucleotide summary: "
## <0 x 0 matrix>
## [1] "View/strand orientation summary: "
## View.1 View.2 View.3 View.4 View.5 View.6 View.7 StrandTotal
## Strand.F 13468 18751 16698 12986 14189 13103 15585 104780
## Strand.R 11284 12915 12422 9753 11147 12107 12427 82055
## [1] "Regression Formula: "
## [1] "ObservedCount ~ offset(logProb)+Shape.HelTA1+Shape.HelTB1+Shape.MGW1+Shape.ProT1+Shape.RollA1+Shape.RollB1+Shape.HelTA2+Shape.HelTB2+Shape.MGW2+Shape.ProT2+Shape.RollA2+Shape.RollB2+Shape.HelTA3+Shape.HelTB3+Shape.MGW3+Shape.ProT3+Shape.RollA3+Shape.RollB3+Shape.HelTA4+Shape.HelTB4+Shape.MGW4+Shape.ProT4+Shape.RollA4+Shape.RollB4+Shape.HelTA5+Shape.HelTB5+Shape.MGW5+Shape.ProT5+Shape.RollA5+Shape.RollB5+Shape.HelTA6+Shape.HelTB6+Shape.MGW6+Shape.ProT6+Shape.RollA6+Shape.RollB6+Shape.HelTA7+Shape.HelTB7+Shape.MGW7+Shape.ProT7+Shape.RollA7+Shape.RollB7+Shape.HelTA8+Shape.HelTB8+Shape.MGW8+Shape.ProT8+Shape.RollA8+Shape.RollB8+Shape.HelTA9+Shape.HelTB9+Shape.MGW9+Shape.ProT9+Shape.RollA9+Shape.RollB9+Shape.HelTA10+Shape.HelTB10+Shape.MGW10+Shape.ProT10+Shape.RollA10+Shape.RollB10+Shape.HelTA11+Shape.HelTB11+Shape.MGW11+Shape.ProT11+Shape.RollA11+Shape.RollB11+Shape.HelTA12+Shape.HelTB12+Shape.MGW12+Shape.ProT12+Shape.RollA12+Shape.RollB12+Shape.HelTA13+Shape.HelTB13+Shape.MGW13+Shape.ProT13+Shape.RollA13+Shape.RollB13+Shape.HelTA14+Shape.HelTB14+Shape.MGW14+Shape.ProT14+Shape.RollA14+Shape.RollB14+Shape.HelTA15+Shape.HelTB15+Shape.MGW15+Shape.ProT15+Shape.RollA15+Shape.RollB15+Shape.HelTA16+Shape.HelTB16+Shape.MGW16+Shape.ProT16+Shape.RollA16+Shape.RollB16+Shape.HelTA17+Shape.HelTB17+Shape.MGW17+Shape.ProT17+Shape.RollA17+Shape.RollB17+Shape.HelTA18+Shape.HelTB18+Shape.MGW18+Shape.ProT18+Shape.RollA18+Shape.RollB18+Shape.HelTA19+Shape.HelTB19+Shape.MGW19+Shape.ProT19+Shape.RollA19+Shape.RollB19+Shape.HelTA20+Shape.HelTB20+Shape.MGW20+Shape.ProT20+Shape.RollA20+Shape.RollB20"
## No nucleotides included in fit.
## An object of class 'model'
##
## Slot "name": HM-Ubx4a-Exd R2 Shape Model
## Slot "varRegLen": 16
## Slot "leftFixedSeq": GTTCAGAGTTCTACAGTCCGACGATCTGG
## Slot "rightFixedSeq": CCAGCTGTCGTATGCCGTCTTCTGCTTG
## Slot "leftFixedSeqOverlap": 5
## Slot "rightFixedSeqOverlap": 5
## Slot "confidenceLevel": 0.95
## Slot "minAffinity": 0
## Slot "missingValueSuppression": 1
## Slot "minSeedValue": 0.01
## Slot "seedLen": 12
## Slot "consensusSeq": [ACGT]TGA[CT][ACGT][ACGT]A[CT][ACGT][ACGT][ACGT]
## Slot "upFootprintExtend": 4
## Slot "downFootprintExtend": 4
## Slot "fpLen": 20
##
## Fits a model of footprint length 20 for mono-nucleotide and shape features (shape = HelT, MGW, ProT, Roll) with 7 view(s) per strand of DNA and 1 round(s) of data (round = 2) without reverse complement symmetry.
##
## Slot "regressionFormula": ObservedCount ~ offset(logProb)+Round.2+Shape.HelTA1+Shape.HelTB1+Shape.MGW1+Shape.ProT1+Shape.RollA1+Shape.RollB1+Shape.HelTA2+Shape.HelTB2+Shape.MGW2+Shape.ProT2+Shape.RollA2+Shape.RollB2+Shape.HelTA3+Shape.HelTB3+Shape.MGW3+Shape.ProT3+Shape.RollA3+Shape.RollB3+Shape.HelTA4+Shape.HelTB4+Shape.MGW4+Shape.ProT4+Shape.RollA4+Shape.RollB4+Shape.HelTA5+Shape.HelTB5+Shape.MGW5+Shape.ProT5+Shape.RollA5+Shape.RollB5+Shape.HelTA6+Shape.HelTB6+Shape.MGW6+Shape.ProT6+Shape.RollA6+Shape.RollB6+Shape.HelTA7+Shape.HelTB7+Shape.MGW7+Shape.ProT7+Shape.RollA7+Shape.RollB7+Shape.HelTA8+Shape.HelTB8+Shape.MGW8+Shape.ProT8+Shape.RollA8+Shape.RollB8+Shape.HelTA9+Shape.HelTB9+Shape.MGW9+Shape.ProT9+Shape.RollA9+Shape.RollB9+Shape.HelTA10+Shape.HelTB10+Shape.MGW10+Shape.ProT10+Shape.RollA10+Shape.RollB10+Shape.HelTA11+Shape.HelTB11+Shape.MGW11+Shape.ProT11+Shape.RollA11+Shape.RollB11+Shape.HelTA12+Shape.HelTB12+Shape.MGW12+Shape.ProT12+Shape.RollA12+Shape.RollB12+Shape.HelTA13+Shape.HelTB13+Shape.MGW13+Shape.ProT13+Shape.RollA13+Shape.RollB13+Shape.HelTA14+Shape.HelTB14+Shape.MGW14+Shape.ProT14+Shape.RollA14+Shape.RollB14+Shape.HelTA15+Shape.HelTB15+Shape.MGW15+Shape.ProT15+Shape.RollA15+Shape.RollB15+Shape.HelTA16+Shape.HelTB16+Shape.MGW16+Shape.ProT16+Shape.RollA16+Shape.RollB16+Shape.HelTA17+Shape.HelTB17+Shape.MGW17+Shape.ProT17+Shape.RollA17+Shape.RollB17+Shape.HelTA18+Shape.HelTB18+Shape.MGW18+Shape.ProT18+Shape.RollA18+Shape.RollB18+Shape.HelTA19+Shape.HelTB19+Shape.MGW19+Shape.ProT19+Shape.RollA19+Shape.RollB19+Shape.HelTA20+Shape.HelTB20+Shape.MGW20+Shape.ProT20+Shape.RollA20+Shape.RollB20
##
## Slot "shapeParamsUsed[[1]]": HelT MGW ProT Roll
##
## Includes the following feature sub-classes:
## An object of class 'N'
## Fits 1 nucleotides for a feature model of length 20.
## Nucleotide beta values:
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## N.A 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.C 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.G 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.T 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
## Nucleotide beta errors:
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## N.A 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.C 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.G 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.T 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
##
## An object of class 'Intercept'
## Fits intercept(s) for 1 round(s) (round = 2).
## Intercept beta values:
## Round.2:
## [1] -6.414526
##
## Intercept beta errors:
## Round.2:
## [1] 0.216099
##
##
##
## An object of class 'Shape'
## Fits 120 shape coefficients for 6 kinds of shape parameter(s) (shape = HelT, MGW, ProT, Roll) for a feature model of length 20.
## Shape beta values:
## 1 2 3 4
## Shape.HelTA -0.03514253 -7.002754e-05 -0.037065117 -0.047470937
## Shape.HelTB -0.02482358 8.889422e-03 0.007123981 0.071659057
## Shape.MGW -0.17644593 -1.766524e-01 -0.202268775 -0.213910953
## Shape.ProT 0.02142373 -1.101217e-02 0.015205034 -0.015976044
## Shape.RollA -0.01497436 7.945374e-03 0.021044132 0.005492719
## Shape.RollB 0.02560216 1.192720e-02 0.019647096 0.062750891
## 5 6 7 8 9
## Shape.HelTA -0.11414508 0.2342302001 0.17699469 -2.1464342 -2.53403755
## Shape.HelTB -0.06413246 -0.2327375303 -0.69538616 -2.1714710 -0.05241424
## Shape.MGW 0.04466575 0.0720116906 0.29161054 -3.9145629 -5.36832137
## Shape.ProT -0.01906239 0.0007721396 0.22680445 -0.9298300 -1.25274958
## Shape.RollA -0.06936702 0.1342133165 0.03472131 0.2068817 0.12847530
## Shape.RollB -0.05461930 0.0125142569 -0.64502178 0.4192283 0.95430579
## 10 11 12 13 14
## Shape.HelTA 0.5716462 -4.0409252 -1.3287313 -0.849917454 -0.11605763
## Shape.HelTB 3.7240420 -1.2108835 -0.7457246 -0.062377602 -0.42155267
## Shape.MGW -10.8708748 -5.6751290 1.3968690 1.794942557 0.02123413
## Shape.ProT 0.3625142 -0.3640632 -0.4779718 -0.180794489 -0.21095584
## Shape.RollA -0.6609773 -1.0265801 -0.3051644 -0.483372301 -0.07993323
## Shape.RollB 3.3584946 1.1292876 0.1450468 0.003038428 -0.16527375
## 15 16 17 18
## Shape.HelTA 0.16958051 0.080392351 0.008974381 0.019291793
## Shape.HelTB -0.11152242 -0.078396753 -0.078821723 -0.006519113
## Shape.MGW -0.28281146 0.203281771 -0.093834842 0.025460474
## Shape.ProT 0.07041932 -0.023105018 -0.002820449 -0.003026015
## Shape.RollA 0.05820192 0.008866403 0.024776856 -0.006045378
## Shape.RollB 0.03951218 -0.041505734 -0.012574245 -0.029936884
## 19 20
## Shape.HelTA -0.017276953 0.011511866
## Shape.HelTB -0.022685255 -0.002167758
## Shape.MGW -0.141709339 -0.190303357
## Shape.ProT 0.003308535 0.023199128
## Shape.RollA 0.038985495 0.057678068
## Shape.RollB -0.054213657 -0.009489285
##
## Shape beta errors:
## 1 2 3 4
## Shape.HelTA 0.0012901254 0.0025408053 0.0023275370 0.0023626427
## Shape.HelTB 0.0027476802 0.0025732914 0.0023832787 0.0032164380
## Shape.MGW 0.0057547787 0.0061396628 0.0057669504 0.0066027926
## Shape.ProT 0.0007166870 0.0006992538 0.0006837819 0.0007274258
## Shape.RollA 0.0008375924 0.0016565314 0.0015534899 0.0014630481
## Shape.RollB 0.0017910226 0.0015902021 0.0014589089 0.0015593231
## 5 6 7 8 9
## Shape.HelTA 0.003400929 0.004067774 0.006778561 0.02268616 0.04411130
## Shape.HelTB 0.003513210 0.004506659 0.017345260 0.03396833 0.04602418
## Shape.MGW 0.007595523 0.007726990 0.020097476 0.08556348 0.10253751
## Shape.ProT 0.001254055 0.002863875 0.003068718 0.01195500 0.02626238
## Shape.RollA 0.001529055 0.002523427 0.002720439 0.01225666 0.02359495
## Shape.RollB 0.002343684 0.002225880 0.012472977 0.02268564 0.02548277
## 10 11 12 13 14
## Shape.HelTA 0.03165574 0.05104078 0.03053066 0.011843917 0.004253126
## Shape.HelTB 0.05168112 0.02619201 0.02506224 0.005083851 0.003058327
## Shape.MGW 0.11522905 0.09148051 0.06640731 0.015435047 0.006641234
## Shape.ProT 0.01838343 0.01085736 0.01247218 0.003603954 0.001204792
## Shape.RollA 0.02874508 0.01875536 0.01489198 0.005351969 0.001717610
## Shape.RollB 0.03545702 0.01578422 0.01178972 0.001799063 0.001358530
## 15 16 17 18
## Shape.HelTA 0.0029852481 0.0033029849 0.0024939940 0.0023280085
## Shape.HelTB 0.0030695051 0.0024861056 0.0022044466 0.0023951672
## Shape.MGW 0.0071270899 0.0065659452 0.0061396989 0.0058626115
## Shape.ProT 0.0008185906 0.0006650136 0.0006405998 0.0006728131
## Shape.RollA 0.0015685185 0.0017770758 0.0014222302 0.0014610313
## Shape.RollB 0.0017744288 0.0014386657 0.0014569342 0.0015608702
## 19 20
## Shape.HelTA 0.0026032450 0.0026865669
## Shape.HelTB 0.0025057700 0.0014423523
## Shape.MGW 0.0062740598 0.0060877157
## Shape.ProT 0.0007099479 0.0007280754
## Shape.RollA 0.0016247764 0.0019040279
## Shape.RollB 0.0017864489 0.0009415427
##
## [1] "Number of Observations in Design Matrix: 186514"
## No nucleotides included in fit.
## [1] "i = 5"
## No nucleotides included in fit.
## [1] "Round summary: "
## 2 Total
## Round 186514 186514
## [1] "Mono-nucleotide summary: "
## <0 x 0 matrix>
## [1] "View/strand orientation summary: "
## View.1 View.2 View.3 View.4 View.5 View.6 View.7 StrandTotal
## Strand.F 13452 18740 16688 12973 14175 13091 15530 104649
## Strand.R 11260 12905 12414 9744 11117 12074 12351 81865
## [1] "Regression Formula: "
## [1] "ObservedCount ~ offset(logProb)+Shape.HelTA1+Shape.HelTB1+Shape.MGW1+Shape.ProT1+Shape.RollA1+Shape.RollB1+Shape.HelTA2+Shape.HelTB2+Shape.MGW2+Shape.ProT2+Shape.RollA2+Shape.RollB2+Shape.HelTA3+Shape.HelTB3+Shape.MGW3+Shape.ProT3+Shape.RollA3+Shape.RollB3+Shape.HelTA4+Shape.HelTB4+Shape.MGW4+Shape.ProT4+Shape.RollA4+Shape.RollB4+Shape.HelTA5+Shape.HelTB5+Shape.MGW5+Shape.ProT5+Shape.RollA5+Shape.RollB5+Shape.HelTA6+Shape.HelTB6+Shape.MGW6+Shape.ProT6+Shape.RollA6+Shape.RollB6+Shape.HelTA7+Shape.HelTB7+Shape.MGW7+Shape.ProT7+Shape.RollA7+Shape.RollB7+Shape.HelTA8+Shape.HelTB8+Shape.MGW8+Shape.ProT8+Shape.RollA8+Shape.RollB8+Shape.HelTA9+Shape.HelTB9+Shape.MGW9+Shape.ProT9+Shape.RollA9+Shape.RollB9+Shape.HelTA10+Shape.HelTB10+Shape.MGW10+Shape.ProT10+Shape.RollA10+Shape.RollB10+Shape.HelTA11+Shape.HelTB11+Shape.MGW11+Shape.ProT11+Shape.RollA11+Shape.RollB11+Shape.HelTA12+Shape.HelTB12+Shape.MGW12+Shape.ProT12+Shape.RollA12+Shape.RollB12+Shape.HelTA13+Shape.HelTB13+Shape.MGW13+Shape.ProT13+Shape.RollA13+Shape.RollB13+Shape.HelTA14+Shape.HelTB14+Shape.MGW14+Shape.ProT14+Shape.RollA14+Shape.RollB14+Shape.HelTA15+Shape.HelTB15+Shape.MGW15+Shape.ProT15+Shape.RollA15+Shape.RollB15+Shape.HelTA16+Shape.HelTB16+Shape.MGW16+Shape.ProT16+Shape.RollA16+Shape.RollB16+Shape.HelTA17+Shape.HelTB17+Shape.MGW17+Shape.ProT17+Shape.RollA17+Shape.RollB17+Shape.HelTA18+Shape.HelTB18+Shape.MGW18+Shape.ProT18+Shape.RollA18+Shape.RollB18+Shape.HelTA19+Shape.HelTB19+Shape.MGW19+Shape.ProT19+Shape.RollA19+Shape.RollB19+Shape.HelTA20+Shape.HelTB20+Shape.MGW20+Shape.ProT20+Shape.RollA20+Shape.RollB20"
## No nucleotides included in fit.
## An object of class 'model'
##
## Slot "name": HM-Ubx4a-Exd R2 Shape Model
## Slot "varRegLen": 16
## Slot "leftFixedSeq": GTTCAGAGTTCTACAGTCCGACGATCTGG
## Slot "rightFixedSeq": CCAGCTGTCGTATGCCGTCTTCTGCTTG
## Slot "leftFixedSeqOverlap": 5
## Slot "rightFixedSeqOverlap": 5
## Slot "confidenceLevel": 0.95
## Slot "minAffinity": 0
## Slot "missingValueSuppression": 1
## Slot "minSeedValue": 0.01
## Slot "seedLen": 12
## Slot "consensusSeq": [ACGT]TGA[CT][ACGT][ACGT]A[CT][ACGT][ACGT][ACGT]
## Slot "upFootprintExtend": 4
## Slot "downFootprintExtend": 4
## Slot "fpLen": 20
##
## Fits a model of footprint length 20 for mono-nucleotide and shape features (shape = HelT, MGW, ProT, Roll) with 7 view(s) per strand of DNA and 1 round(s) of data (round = 2) without reverse complement symmetry.
##
## Slot "regressionFormula": ObservedCount ~ offset(logProb)+Round.2+Shape.HelTA1+Shape.HelTB1+Shape.MGW1+Shape.ProT1+Shape.RollA1+Shape.RollB1+Shape.HelTA2+Shape.HelTB2+Shape.MGW2+Shape.ProT2+Shape.RollA2+Shape.RollB2+Shape.HelTA3+Shape.HelTB3+Shape.MGW3+Shape.ProT3+Shape.RollA3+Shape.RollB3+Shape.HelTA4+Shape.HelTB4+Shape.MGW4+Shape.ProT4+Shape.RollA4+Shape.RollB4+Shape.HelTA5+Shape.HelTB5+Shape.MGW5+Shape.ProT5+Shape.RollA5+Shape.RollB5+Shape.HelTA6+Shape.HelTB6+Shape.MGW6+Shape.ProT6+Shape.RollA6+Shape.RollB6+Shape.HelTA7+Shape.HelTB7+Shape.MGW7+Shape.ProT7+Shape.RollA7+Shape.RollB7+Shape.HelTA8+Shape.HelTB8+Shape.MGW8+Shape.ProT8+Shape.RollA8+Shape.RollB8+Shape.HelTA9+Shape.HelTB9+Shape.MGW9+Shape.ProT9+Shape.RollA9+Shape.RollB9+Shape.HelTA10+Shape.HelTB10+Shape.MGW10+Shape.ProT10+Shape.RollA10+Shape.RollB10+Shape.HelTA11+Shape.HelTB11+Shape.MGW11+Shape.ProT11+Shape.RollA11+Shape.RollB11+Shape.HelTA12+Shape.HelTB12+Shape.MGW12+Shape.ProT12+Shape.RollA12+Shape.RollB12+Shape.HelTA13+Shape.HelTB13+Shape.MGW13+Shape.ProT13+Shape.RollA13+Shape.RollB13+Shape.HelTA14+Shape.HelTB14+Shape.MGW14+Shape.ProT14+Shape.RollA14+Shape.RollB14+Shape.HelTA15+Shape.HelTB15+Shape.MGW15+Shape.ProT15+Shape.RollA15+Shape.RollB15+Shape.HelTA16+Shape.HelTB16+Shape.MGW16+Shape.ProT16+Shape.RollA16+Shape.RollB16+Shape.HelTA17+Shape.HelTB17+Shape.MGW17+Shape.ProT17+Shape.RollA17+Shape.RollB17+Shape.HelTA18+Shape.HelTB18+Shape.MGW18+Shape.ProT18+Shape.RollA18+Shape.RollB18+Shape.HelTA19+Shape.HelTB19+Shape.MGW19+Shape.ProT19+Shape.RollA19+Shape.RollB19+Shape.HelTA20+Shape.HelTB20+Shape.MGW20+Shape.ProT20+Shape.RollA20+Shape.RollB20
##
## Slot "shapeParamsUsed[[1]]": HelT MGW ProT Roll
##
## Includes the following feature sub-classes:
## An object of class 'N'
## Fits 1 nucleotides for a feature model of length 20.
## Nucleotide beta values:
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## N.A 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.C 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.G 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.T 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
## Nucleotide beta errors:
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## N.A 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.C 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.G 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.T 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
##
## An object of class 'Intercept'
## Fits intercept(s) for 1 round(s) (round = 2).
## Intercept beta values:
## Round.2:
## [1] -7.567961
##
## Intercept beta errors:
## Round.2:
## [1] 0.2364171
##
##
##
## An object of class 'Shape'
## Fits 120 shape coefficients for 6 kinds of shape parameter(s) (shape = HelT, MGW, ProT, Roll) for a feature model of length 20.
## Shape beta values:
## 1 2 3 4 5
## Shape.HelTA -0.03493164 -0.000313151 -0.036863686 -0.047952287 -0.11270737
## Shape.HelTB -0.02493753 0.008280751 0.007707976 0.072180587 -0.06350309
## Shape.MGW -0.17633594 -0.176871270 -0.200833020 -0.213298034 0.04236838
## Shape.ProT 0.02144458 -0.011140644 0.015189952 -0.015812281 -0.01930025
## Shape.RollA -0.01510213 0.007643213 0.020751336 0.005682664 -0.06851045
## Shape.RollB 0.02575917 0.012027167 0.019175620 0.062418112 -0.05307172
## 6 7 8 9 10
## Shape.HelTA 0.230863035 0.19105766 -2.1201121 -2.67376173 0.2500858
## Shape.HelTB -0.233364395 -0.75677850 -2.1240455 0.02854875 3.7334982
## Shape.MGW 0.072666735 0.34925418 -3.7763283 -5.21031322 -11.7594094
## Shape.ProT 0.002528018 0.23386886 -0.9588584 -1.39310657 0.2823029
## Shape.RollA 0.132808596 0.03480262 0.2296147 0.16395503 -0.7318202
## Shape.RollB 0.011943858 -0.68516667 0.3845064 0.92584951 3.5479426
## 11 12 13 14 15
## Shape.HelTA -4.2615388 -1.5027591 -0.894235354 -0.11903577 0.16997627
## Shape.HelTB -1.2443689 -0.8750826 -0.071172929 -0.42263630 -0.11006782
## Shape.MGW -5.8010957 1.2728263 1.766975440 0.02424275 -0.28168208
## Shape.ProT -0.4460256 -0.5219288 -0.189443993 -0.20944066 0.06951006
## Shape.RollA -1.1570108 -0.3752985 -0.495330712 -0.07960813 0.05783612
## Shape.RollB 1.2260622 0.1354883 0.003425858 -0.16592088 0.03967002
## 16 17 18 19
## Shape.HelTA 0.079537075 0.008689805 0.020504580 -0.017254152
## Shape.HelTB -0.078305547 -0.079605982 -0.006080504 -0.022816902
## Shape.MGW 0.204509294 -0.093153587 0.024463837 -0.141912796
## Shape.ProT -0.022896526 -0.002927027 -0.002782804 0.003360255
## Shape.RollA 0.008630905 0.024668216 -0.005467677 0.038788003
## Shape.RollB -0.041667928 -0.012983047 -0.029620034 -0.054225810
## 20
## Shape.HelTA 0.011627154
## Shape.HelTB -0.002445607
## Shape.MGW -0.189489031
## Shape.ProT 0.023128546
## Shape.RollA 0.057721278
## Shape.RollB -0.009534001
##
## Shape beta errors:
## 1 2 3 4 5
## Shape.HelTA 0.0012904179 0.0025411932 0.002327731 0.0023628817 0.003402544
## Shape.HelTB 0.0027481288 0.0025736129 0.002383616 0.0032184609 0.003512011
## Shape.MGW 0.0057577887 0.0061417640 0.005771542 0.0066032855 0.007597218
## Shape.ProT 0.0007169016 0.0006993884 0.000683887 0.0007276038 0.001253645
## Shape.RollA 0.0008381499 0.0016577278 0.001553807 0.0014633825 0.001529367
## Shape.RollB 0.0017919116 0.0015902107 0.001459581 0.0015597684 0.002346415
## 6 7 8 9 10
## Shape.HelTA 0.004069030 0.006837530 0.02269478 0.04342647 0.03231118
## Shape.HelTB 0.004507374 0.017552693 0.03287662 0.04696763 0.05733207
## Shape.MGW 0.007719298 0.020332652 0.08603771 0.10410936 0.12170334
## Shape.ProT 0.002863478 0.003078224 0.01194326 0.02736440 0.01914435
## Shape.RollA 0.002524381 0.002699956 0.01209510 0.02355485 0.02936030
## Shape.RollB 0.002230287 0.012608657 0.02341856 0.02640227 0.03800860
## 11 12 13 14 15
## Shape.HelTA 0.05875543 0.03125429 0.012528135 0.004260535 0.0029911960
## Shape.HelTB 0.02815261 0.02712136 0.005212060 0.003066467 0.0030714440
## Shape.MGW 0.09781886 0.06887146 0.015878001 0.006653241 0.0071311511
## Shape.ProT 0.01268255 0.01284084 0.003712761 0.001213791 0.0008212477
## Shape.RollA 0.01999920 0.01544316 0.005439782 0.001722087 0.0015711032
## Shape.RollB 0.01675301 0.01189160 0.001809700 0.001359502 0.0017756258
## 16 17 18 19
## Shape.HelTA 0.0033040909 0.0024940706 0.0023289920 0.0026031905
## Shape.HelTB 0.0024863125 0.0022051686 0.0023951388 0.0025060181
## Shape.MGW 0.0065669583 0.0061410508 0.0058646380 0.0062745722
## Shape.ProT 0.0006656642 0.0006406425 0.0006729824 0.0007099705
## Shape.RollA 0.0017781743 0.0014229777 0.0014614609 0.0016248077
## Shape.RollB 0.0014393092 0.0014572362 0.0015610870 0.0017866509
## 20
## Shape.HelTA 0.0026867715
## Shape.HelTB 0.0014423217
## Shape.MGW 0.0060885592
## Shape.ProT 0.0007281485
## Shape.RollA 0.0019042613
## Shape.RollB 0.0009416636
##
## [1] "Number of Observations in Design Matrix: 186395"
## No nucleotides included in fit.
## [1] "i = 6"
## No nucleotides included in fit.
## [1] "Round summary: "
## 2 Total
## Round 186395 186395
## [1] "Mono-nucleotide summary: "
## <0 x 0 matrix>
## [1] "View/strand orientation summary: "
## View.1 View.2 View.3 View.4 View.5 View.6 View.7 StrandTotal
## Strand.F 13446 18739 16684 12961 14170 13089 15526 104615
## Strand.R 11251 12894 12400 9733 11100 12055 12347 81780
## [1] "Regression Formula: "
## [1] "ObservedCount ~ offset(logProb)+Shape.HelTA1+Shape.HelTB1+Shape.MGW1+Shape.ProT1+Shape.RollA1+Shape.RollB1+Shape.HelTA2+Shape.HelTB2+Shape.MGW2+Shape.ProT2+Shape.RollA2+Shape.RollB2+Shape.HelTA3+Shape.HelTB3+Shape.MGW3+Shape.ProT3+Shape.RollA3+Shape.RollB3+Shape.HelTA4+Shape.HelTB4+Shape.MGW4+Shape.ProT4+Shape.RollA4+Shape.RollB4+Shape.HelTA5+Shape.HelTB5+Shape.MGW5+Shape.ProT5+Shape.RollA5+Shape.RollB5+Shape.HelTA6+Shape.HelTB6+Shape.MGW6+Shape.ProT6+Shape.RollA6+Shape.RollB6+Shape.HelTA7+Shape.HelTB7+Shape.MGW7+Shape.ProT7+Shape.RollA7+Shape.RollB7+Shape.HelTA8+Shape.HelTB8+Shape.MGW8+Shape.ProT8+Shape.RollA8+Shape.RollB8+Shape.HelTA9+Shape.HelTB9+Shape.MGW9+Shape.ProT9+Shape.RollA9+Shape.RollB9+Shape.HelTA10+Shape.HelTB10+Shape.MGW10+Shape.ProT10+Shape.RollA10+Shape.RollB10+Shape.HelTA11+Shape.HelTB11+Shape.MGW11+Shape.ProT11+Shape.RollA11+Shape.RollB11+Shape.HelTA12+Shape.HelTB12+Shape.MGW12+Shape.ProT12+Shape.RollA12+Shape.RollB12+Shape.HelTA13+Shape.HelTB13+Shape.MGW13+Shape.ProT13+Shape.RollA13+Shape.RollB13+Shape.HelTA14+Shape.HelTB14+Shape.MGW14+Shape.ProT14+Shape.RollA14+Shape.RollB14+Shape.HelTA15+Shape.HelTB15+Shape.MGW15+Shape.ProT15+Shape.RollA15+Shape.RollB15+Shape.HelTA16+Shape.HelTB16+Shape.MGW16+Shape.ProT16+Shape.RollA16+Shape.RollB16+Shape.HelTA17+Shape.HelTB17+Shape.MGW17+Shape.ProT17+Shape.RollA17+Shape.RollB17+Shape.HelTA18+Shape.HelTB18+Shape.MGW18+Shape.ProT18+Shape.RollA18+Shape.RollB18+Shape.HelTA19+Shape.HelTB19+Shape.MGW19+Shape.ProT19+Shape.RollA19+Shape.RollB19+Shape.HelTA20+Shape.HelTB20+Shape.MGW20+Shape.ProT20+Shape.RollA20+Shape.RollB20"
## No nucleotides included in fit.
## An object of class 'model'
##
## Slot "name": HM-Ubx4a-Exd R2 Shape Model
## Slot "varRegLen": 16
## Slot "leftFixedSeq": GTTCAGAGTTCTACAGTCCGACGATCTGG
## Slot "rightFixedSeq": CCAGCTGTCGTATGCCGTCTTCTGCTTG
## Slot "leftFixedSeqOverlap": 5
## Slot "rightFixedSeqOverlap": 5
## Slot "confidenceLevel": 0.95
## Slot "minAffinity": 0
## Slot "missingValueSuppression": 1
## Slot "minSeedValue": 0.01
## Slot "seedLen": 12
## Slot "consensusSeq": [ACGT]TGA[CT][ACGT][ACGT]A[CT][ACGT][ACGT][ACGT]
## Slot "upFootprintExtend": 4
## Slot "downFootprintExtend": 4
## Slot "fpLen": 20
##
## Fits a model of footprint length 20 for mono-nucleotide and shape features (shape = HelT, MGW, ProT, Roll) with 7 view(s) per strand of DNA and 1 round(s) of data (round = 2) without reverse complement symmetry.
##
## Slot "regressionFormula": ObservedCount ~ offset(logProb)+Round.2+Shape.HelTA1+Shape.HelTB1+Shape.MGW1+Shape.ProT1+Shape.RollA1+Shape.RollB1+Shape.HelTA2+Shape.HelTB2+Shape.MGW2+Shape.ProT2+Shape.RollA2+Shape.RollB2+Shape.HelTA3+Shape.HelTB3+Shape.MGW3+Shape.ProT3+Shape.RollA3+Shape.RollB3+Shape.HelTA4+Shape.HelTB4+Shape.MGW4+Shape.ProT4+Shape.RollA4+Shape.RollB4+Shape.HelTA5+Shape.HelTB5+Shape.MGW5+Shape.ProT5+Shape.RollA5+Shape.RollB5+Shape.HelTA6+Shape.HelTB6+Shape.MGW6+Shape.ProT6+Shape.RollA6+Shape.RollB6+Shape.HelTA7+Shape.HelTB7+Shape.MGW7+Shape.ProT7+Shape.RollA7+Shape.RollB7+Shape.HelTA8+Shape.HelTB8+Shape.MGW8+Shape.ProT8+Shape.RollA8+Shape.RollB8+Shape.HelTA9+Shape.HelTB9+Shape.MGW9+Shape.ProT9+Shape.RollA9+Shape.RollB9+Shape.HelTA10+Shape.HelTB10+Shape.MGW10+Shape.ProT10+Shape.RollA10+Shape.RollB10+Shape.HelTA11+Shape.HelTB11+Shape.MGW11+Shape.ProT11+Shape.RollA11+Shape.RollB11+Shape.HelTA12+Shape.HelTB12+Shape.MGW12+Shape.ProT12+Shape.RollA12+Shape.RollB12+Shape.HelTA13+Shape.HelTB13+Shape.MGW13+Shape.ProT13+Shape.RollA13+Shape.RollB13+Shape.HelTA14+Shape.HelTB14+Shape.MGW14+Shape.ProT14+Shape.RollA14+Shape.RollB14+Shape.HelTA15+Shape.HelTB15+Shape.MGW15+Shape.ProT15+Shape.RollA15+Shape.RollB15+Shape.HelTA16+Shape.HelTB16+Shape.MGW16+Shape.ProT16+Shape.RollA16+Shape.RollB16+Shape.HelTA17+Shape.HelTB17+Shape.MGW17+Shape.ProT17+Shape.RollA17+Shape.RollB17+Shape.HelTA18+Shape.HelTB18+Shape.MGW18+Shape.ProT18+Shape.RollA18+Shape.RollB18+Shape.HelTA19+Shape.HelTB19+Shape.MGW19+Shape.ProT19+Shape.RollA19+Shape.RollB19+Shape.HelTA20+Shape.HelTB20+Shape.MGW20+Shape.ProT20+Shape.RollA20+Shape.RollB20
##
## Slot "shapeParamsUsed[[1]]": HelT MGW ProT Roll
##
## Includes the following feature sub-classes:
## An object of class 'N'
## Fits 1 nucleotides for a feature model of length 20.
## Nucleotide beta values:
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## N.A 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.C 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.G 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.T 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
## Nucleotide beta errors:
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
## N.A 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.C 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.G 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
## N.T 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
##
##
## An object of class 'Intercept'
## Fits intercept(s) for 1 round(s) (round = 2).
## Intercept beta values:
## Round.2:
## [1] -7.541557
##
## Intercept beta errors:
## Round.2:
## [1] 0.2366986
##
##
##
## An object of class 'Shape'
## Fits 120 shape coefficients for 6 kinds of shape parameter(s) (shape = HelT, MGW, ProT, Roll) for a feature model of length 20.
## Shape beta values:
## 1 2 3 4
## Shape.HelTA -0.03494614 -0.0002858458 -0.036874712 -0.047973406
## Shape.HelTB -0.02497323 0.0082978782 0.007709617 0.072192781
## Shape.MGW -0.17636963 -0.1768896440 -0.200889306 -0.213390013
## Shape.ProT 0.02144583 -0.0111416745 0.015199555 -0.015809899
## Shape.RollA -0.01510816 0.0076515312 0.020763770 0.005698872
## Shape.RollB 0.02576448 0.0120287916 0.019174989 0.062438451
## 5 6 7 8 9
## Shape.HelTA -0.11273455 0.230916169 0.19097270 -2.1192044 -2.67519223
## Shape.HelTB -0.06350719 -0.233441743 -0.75604862 -2.1249142 0.03193451
## Shape.MGW 0.04228424 0.073023708 0.34840222 -3.7691603 -5.21684441
## Shape.ProT -0.01931544 0.002524106 0.23373951 -0.9608939 -1.38838376
## Shape.RollA -0.06852509 0.132706196 0.03475305 0.2294190 0.16372839
## Shape.RollB -0.05304710 0.011953914 -0.68485881 0.3836202 0.92803084
## 10 11 12 13 14
## Shape.HelTA 0.2486267 -4.2605394 -1.5028623 -0.893840770 -0.11910766
## Shape.HelTB 3.7327193 -1.2418756 -0.8736088 -0.070967875 -0.42267205
## Shape.MGW -11.7550423 -5.7975123 1.2703905 1.767915197 0.02412976
## Shape.ProT 0.2818355 -0.4452732 -0.5215629 -0.189416026 -0.20943245
## Shape.RollA -0.7311514 -1.1557369 -0.3746536 -0.495447138 -0.07960380
## Shape.RollB 3.5452741 1.2256531 0.1358505 0.003431654 -0.16592335
## 15 16 17 18
## Shape.HelTA 0.17002016 0.079506457 0.008671689 0.020486470
## Shape.HelTB -0.11002099 -0.078274590 -0.079612463 -0.006100396
## Shape.MGW -0.28162509 0.204403671 -0.093081327 0.024520370
## Shape.ProT 0.06952087 -0.022898347 -0.002923549 -0.002792460
## Shape.RollA 0.05784570 0.008645786 0.024649026 -0.005510700
## Shape.RollB 0.03966669 -0.041648399 -0.012941595 -0.029625199
## 19 20
## Shape.HelTA -0.017264713 0.011655010
## Shape.HelTB -0.022796454 -0.002397539
## Shape.MGW -0.141864046 -0.189494064
## Shape.ProT 0.003366561 0.023133988
## Shape.RollA 0.038787657 0.057764847
## Shape.RollB -0.054288813 -0.009543812
##
## Shape beta errors:
## 1 2 3 4
## Shape.HelTA 0.0012904437 0.0025411659 0.0023278031 0.0023629050
## Shape.HelTB 0.0027481166 0.0025736864 0.0023836341 0.0032185420
## Shape.MGW 0.0057578132 0.0061418147 0.0057716617 0.0066034762
## Shape.ProT 0.0007169086 0.0006993882 0.0006838941 0.0007276278
## Shape.RollA 0.0008381538 0.0016577432 0.0015538217 0.0014634149
## Shape.RollB 0.0017919141 0.0015902244 0.0014595944 0.0015598389
## 5 6 7 8 9
## Shape.HelTA 0.003402726 0.004069520 0.006838818 0.02270425 0.04340862
## Shape.HelTB 0.003512116 0.004507452 0.017577759 0.03287827 0.04704082
## Shape.MGW 0.007597325 0.007719953 0.020347701 0.08611614 0.10409299
## Shape.ProT 0.001253684 0.002863818 0.003078540 0.01195084 0.02742478
## Shape.RollA 0.001529370 0.002524445 0.002699252 0.01209997 0.02354705
## Shape.RollB 0.002346365 0.002230507 0.012621921 0.02344182 0.02643658
## 10 11 12 13 14
## Shape.HelTA 0.03232188 0.05878632 0.03125967 0.012527166 0.004260695
## Shape.HelTB 0.05744443 0.02816536 0.02713514 0.005212663 0.003066520
## Shape.MGW 0.12188166 0.09787338 0.06887964 0.015879178 0.006653416
## Shape.ProT 0.01915460 0.01270815 0.01283957 0.003713421 0.001213832
## Shape.RollA 0.02939768 0.02001289 0.01544688 0.005439675 0.001722116
## Shape.RollB 0.03802306 0.01675872 0.01189094 0.001809844 0.001359549
## 15 16 17 18
## Shape.HelTA 0.0029912229 0.0033041291 0.002494114 0.0023290449
## Shape.HelTB 0.0030714924 0.0024863486 0.002205230 0.0023951531
## Shape.MGW 0.0071312794 0.0065670249 0.006141100 0.0058647554
## Shape.ProT 0.0008212806 0.0006656729 0.000640644 0.0006729898
## Shape.RollA 0.0015711378 0.0017781656 0.001422999 0.0014614957
## Shape.RollB 0.0017756163 0.0014393270 0.001457261 0.0015611089
## 19 20
## Shape.HelTA 0.0026032109 0.0026867802
## Shape.HelTB 0.0025060153 0.0014423727
## Shape.MGW 0.0062746862 0.0060886742
## Shape.ProT 0.0007099833 0.0007281730
## Shape.RollA 0.0016248375 0.0019043125
## Shape.RollB 0.0017867165 0.0009416837
##
## [1] "Number of Observations in Design Matrix: 186395"
## No nucleotides included in fit.
## [1] "Stability Reached after 6 iterations."
ModelTest <- finalizeFeatureBetas(ModelTest)
pM <- plot(ModelTest, plotTitle = "HM-Ubx4a-Exd R2 Shape Fit", Nplot.ddG = TRUE, verticalPlots = TRUE)
ggplot2::ggsave(pM, file = paste(selexDir, saveDir, "/modelPlot.pdf", sep = ""), height = vPheight, width = 6)
save(ModelTest, file = paste(selexDir, saveDir, "/model.RData",sep = ""))
saveRDS(ModelTest, file = paste(selexDir, saveDir, "/model.rds",sep = ""))