Question: No significant p-values
5.3 years ago by
Guest User • 12k
Guest User • 12k wrote:
Hello, I have constructed the following dataset for analysis using DESeq2: class: DESeqDataSet dim: 57396 10 exptData(0): assays(1): counts rownames(57396): ENSG00000223972 ENSG00000227232 ... ENSG00000210195 ENSG00000210196 rowData metadata column names(0): colnames(10): 1 2 ... 10 11 colData names(1): condition > colData(ddsHTSeq) DataFrame with 10 rows and 1 column condition <factor> 1 na 2 na 3 Resistant 4 na 5 Resistant 6 Resistant 7 na 8 na 10 Sensitive 11 Sensitive I am interested in the differential expression between the drug resistant and sensitive samples ('na' are control samples). I've clustered the samples and plotted a PCA as described in the vignette. However, in each of these plots the samples do not cluster by their drug sensitivity but are distributed across the plot. I don't have any more information about the samples with which to model any potential covariates. I was wondering if there were any pointers as to how I could extract some useful meanings from these data please? As might be expected, when I try a DESeq on these data I get no significant p-values. Thanks in advance, Dave -- output of sessionInfo(): R version 3.1.0 (2014-04-10) Platform: x86_64-unknown-linux-gnu (64-bit) locale:  LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C  LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8  LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8  LC_PAPER=en_US.UTF-8 LC_NAME=C  LC_ADDRESS=C LC_TELEPHONE=C  LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C attached base packages:  parallel stats graphics grDevices utils datasets methods  base other attached packages:  pasilla_0.4.0 matrixStats_0.8.14 gplots_2.13.0  vsn_3.32.0 Biobase_2.24.0 DESeq2_1.4.5  RcppArmadillo_0.4.300.0 Rcpp_0.11.1 GenomicRanges_1.16.3  GenomeInfoDb_1.0.2 IRanges_1.22.7 BiocGenerics_0.10.0 loaded via a namespace (and not attached):  affy_1.42.2 affyio_1.32.0 annotate_1.42.0  AnnotationDbi_1.26.0 BiocInstaller_1.14.2 bitops_1.0-6  caTools_1.17 DBI_0.2-7 DESeq_1.16.0  gdata_2.13.3 genefilter_1.46.1 geneplotter_1.42.0  grid_3.1.0 gtools_3.4.0 KernSmooth_2.23-12  lattice_0.20-29 limma_3.20.4 locfit_1.5-9.1  preprocessCore_1.26.1 RColorBrewer_1.0-5 R.methodsS3_1.6.1  RSQLite_0.11.4 splines_3.1.0 stats4_3.1.0  survival_2.37-7 tcltk_3.1.0 tools_3.1.0  XML_3.98-1.1 xtable_1.7-3 XVector_0.4.0  zlibbioc_1.10.0 -- Sent via the guest posting facility at bioconductor.org.
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