Hi Avinash,

You can use the DESeq() function as you have and it will take care of the
dispersion estimation automatically.

Also, I see you are using v1.0, which is some months behind now. We
recommend, if possible, users always upgrading to the most recent release.

Mike
On Jan 28, 2014 9:56 PM, "Avinash S" <avins.s@gmail.com> wrote:

> Hello,
>
> I'm trying to use DESeq2 for differential expression analysis of RNA-seq
> data containing Control (CR) and two Treatments (HR and SR). One of the
> biological replicate for HR treatment failed leaving me with 2 replicates
> for CR and SR and 1 for HR.
>
> DESeq document described "Working partially without replicates" however,
> that is not in the DESeq2 documentation.
>
> I want to check if I could use the code below to analyze data with no
> biological replicate for one of the treatments.
>
> Also, I appreciate if someone could weigh in on using edgeR with partial
> replicates (by estimating dispersion from house-keeping genes) as an
> option.
>
> Thank you for your time,
> Avinash
>
> Here is the code I used and my sessionInfo().
>
> countsTablePop <- read.delim(filetxt, row.names=1 )
> countTable <-as.data.frame(countsTablePop)
> colData <- DataFrame(condition = factor(c("CR", "CR", "HR", "SR", "SR")))
> dds <- DESeqDataSetFromMatrix(countData = countTable, colData = colData,
> design = ~ condition)
> colData(dds)$condition <- factor(colData(dds)$condition,
> levels=c("CR","HR","SR"))
> design(dds)
> dds <- DESeq(dds)
> res <- results(dds)
> res <- res[order(res$padj),]
>
> #####
>
> > sessionInfo()
> R version 3.0.2 (2013-09-25)
> Platform: x86_64-redhat-linux-gnu (64-bit)
>
> locale:
>  [1] 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
>  [6] LC_MESSAGES=en_US.UTF-8    LC_PAPER=en_US.UTF-8       LC_NAME=C
>            LC_ADDRESS=C               LC_TELEPHONE=C
> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
>
> attached base packages:
>  [1] grid      splines   parallel  stats     graphics  grDevices utils
> datasets  methods   base
>
> other attached packages:
>  [1] VennDiagram_1.6.5       vsn_3.28.0              gplots_2.12.1
>   RColorBrewer_1.0-5      DESeq2_1.0.19
>  [6] RcppArmadillo_0.4.000.2 Rcpp_0.10.6             GenomicRanges_1.13.35
>   XVector_0.1.0           IRanges_1.19.19
> [11] lattice_0.20-23         locfit_1.5-9.1          BiocInstaller_1.10.4
>  limma_3.17.21           topGO_2.12.0
> [16] SparseM_1.03            GO.db_2.9.0             RSQLite_0.11.4
>  DBI_0.2-7               AnnotationDbi_1.23.18
> [21] Biobase_2.21.6          BiocGenerics_0.7.3      graph_1.38.3
>  plyr_1.8                reshape2_1.2.2
> [26] ggplot2_0.9.3.1
>
> loaded via a namespace (and not attached):
>  [1] affy_1.38.1           affyio_1.28.0         annotate_1.38.0
> bitops_1.0-6          caTools_1.16          colorspace_1.2-4
>  [7] dichromat_2.0-0       digest_0.6.4          gdata_2.13.2
>  genefilter_1.42.0     gtable_0.1.2          gtools_3.2.1
> [13] KernSmooth_2.23-10    labeling_0.2          MASS_7.3-29
> munsell_0.4.2         preprocessCore_1.22.0 proto_0.3-10
> [19] scales_0.2.3          stats4_3.0.2          stringr_0.6.2
> survival_2.37-7       tools_3.0.2           XML_3.98-1.1
> [25] xtable_1.7-1          zlibbioc_1.7.0
>
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>
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