NanoStringDiff produces very large logFC values - r

Question

I am trying to use NanoStringDiff to identify differentially expressed microRNAs between treatment and control samples, but I am obtaining extraordinarily large values for the fold change (log2FC is 27 for certain genes, but expected to be around 1 by inspection). I think there is an error with my code. I am using the following guide http://www.bioconductor.org/packages/release/bioc/vignettes/NanoStringDiff/inst/doc/NanoStringDiff.pdf
I've included my code below and the data I am using is publicly available on https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE84971 (GSE84971_non-normalized.txt.gz)
I took this data and converted it into an Excel file in the format as specified in the guide which I called "data".
Any help is much appreciated.
source("https://bioconductor.org/biocLite.R")
biocLite()
biocLite("NanoStringDiff")
biocLite("Biobase")
library("BioBase")
library("NanoStringDiff")
designs=data.frame(group=c("Control","Control","Control", "Treatment", "Treatment", "Treatment"))
designs
directory <- "/Users/admin/Desktop"
path <- paste(directory, "data.csv", sep ="/", collapse = NULL)
NanoStringData=createNanoStringSetFromCsv(path,header=TRUE,designs)
pheno=pData(NanoStringData)
group=pheno$group
design.full=model.matrix(~0+group) #create a design (or model) matrix
design.full
contrast=c(-1,1)
NanoStringData=estNormalizationFactors(NanoStringData)
positiveFactor(NanoStringData)
negativeFactor(NanoStringData)
housekeepingFactor(NanoStringData)
result=glm.LRT(NanoStringData,design.full, Beta= ncol(design.full), contrast=contrast)
result$table
I attempted to add the data using dput(NanoString), hopefully this makes my code more self-contained. Below is shown the output.
new("NanoStringSet"
, positiveFactor = numeric(0)
, negativeFactor = numeric(0)
, housekeepingFactor = numeric(0)
, positiveControl = structure(c(51117L, 9153L, 2357L, 749L, 133L, 88L, 30283L, 6423L,
1178L, 444L, 83L, 35L, 46143L, 8040L, 2014L, 554L, 114L, 82L,
48365L, 9338L, 2158L, 603L, 135L, 91L, 52744L, 10177L, 2391L,
786L, 143L, 72L, 70189L, 12069L, 3186L, 693L, 176L, 110L), .Dim = c(6L,
6L), .Dimnames = list(c("POS_A(128)", "POS_B(32)", "POS_C(8)",
"POS_D(2)", "POS_E(0.5)", "POS_F(0.125)"), c("Control.1", "Control.2",
"Control.3", "Treatment.1", "Treatment.2", "Treatment.3")))
, negativeControl = structure(c(52L, 32L, 40L, 14L, 104L, 74L, 28L, 25L, 29L, 11L,
74L, 45L, 31L, 32L, 29L, 13L, 80L, 60L, 61L, 44L, 32L, 5L, 103L,
74L, 56L, 42L, 44L, 15L, 135L, 62L, 55L, 54L, 36L, 12L, 108L,
61L), .Dim = c(6L, 6L), .Dimnames = list(c("NEG_B(0)", "NEG_C(0)",
"NEG_A(0)", "NEG_F(0)", "NEG_E(0)", "NEG_D(0)"), c("Control.1",
"Control.2", "Control.3", "Treatment.1", "Treatment.2", "Treatment.3"
)))
, housekeepingControl = structure(c(825L, 1892L, 1293L, 1496L, 2157L, 1254L, 1081L, 1121L,
914L, 1223L, 2123L, 3912L, 1876L, 2217L, 3363L, 1392L, 1750L,
1626L, 1196L, 1917L, 1378L, 1446L, 1300L, 1077L, 1875L, 2098L,
8006L, 2989L, 4447L, 4930L), .Dim = 5:6, .Dimnames = list(c("Actb|0",
"B2m|0", "Gapdh|0", "Rpl19|0", "Rplp0|0"), c("Control.1", "Control.2",
"Control.3", "Treatment.1", "Treatment.2", "Treatment.3")))
, experimentData = new("MIAME"
, name = ""
, lab = ""
, contact = ""
, title = ""
, abstract = ""
, url = ""
, pubMedIds = ""
, samples = list()
, hybridizations = list()
, normControls = list()
, preprocessing = list()
, other = list()
, .__classVersion__ = new("Versions"
, .Data = list(c(1L, 0L, 0L), c(1L, 1L, 0L))
)
)
, assayData = <environment>
, phenoData = new("AnnotatedDataFrame"
, varMetadata = structure(list(labelDescription = NA_character_), .Names = "labelDescription", row.names = "group", class = "data.frame")
, data = structure(list(group = structure(c(1L, 1L, 1L, 2L, 2L, 2L), .Label = c("Control",
"Treatment"), class = "factor")), .Names = "group", row.names = c("Control.1",
"Control.2", "Control.3", "Treatment.1", "Treatment.2", "Treatment.3"
), class = "data.frame")
, dimLabels = c("sampleNames", "sampleColumns")
, .__classVersion__ = new("Versions"
, .Data = list(c(1L, 1L, 0L))
)
)
, featureData = new("AnnotatedDataFrame"
, varMetadata = structure(list(labelDescription = character(0)), .Names = "labelDescription", row.names = character(0), class = "data.frame")
, data = structure(list(), .Names = character(0), class = "data.frame", row.names = c("hsa-miR-10a-5p|0",
"hsa-miR-1234|0", "hsa-miR-185-5p|0", "hsa-miR-27a-3p", "hsa-miR-34c-3p",
"hsa-miR-1181|0", "hsa-miR-601", "hsa-miR-4454"))
, dimLabels = c("featureNames", "featureColumns")
, .__classVersion__ = new("Versions"
, .Data = list(c(1L, 1L, 0L))
)
)
, annotation = character(0)
, protocolData = new("AnnotatedDataFrame"
, varMetadata = structure(list(labelDescription = character(0)), .Names = "labelDescription", row.names = character(0), class = "data.frame")
, data = structure(list(), .Names = character(0), class = "data.frame", row.names = c("Control.1",
"Control.2", "Control.3", "Treatment.1", "Treatment.2", "Treatment.3"
))
, dimLabels = c("sampleNames", "sampleColumns")
, .__classVersion__ = new("Versions"
, .Data = list(c(1L, 1L, 0L))
)
)
, .__classVersion__ = new("Versions"
, .Data = list(c(3L, 3L, 1L), c(2L, 34L, 0L), c(1L, 3L, 0L), c(1L, 0L,
0L))
)
)
Thanks!