I am trying to use CellMix to generate a signature(basis) matrix for whole blood deconvolution based on some inhouse data. I have gene expression data from 16 immune cell types. I had a few questions for you. I would really appreciate your response. 1. I am trying to use Abass method (markerScoreAbbas) for identifying the markerset. When I try to do that based on p.value as statitic, it works fine. But when I try to do the same with t.statistic as the statitic it gives me an error. Following is the r code I am using along with the error message. I have also included the session info along with it. 2. In terms of interpretating the results from the call "markerScore Abbas" I have the following column headers:top,p.value,p.value2,dm2,statistic2,dmM2,fold2,mMfold2,top2,p.value3,dm3,statistic3,dmM3,fold3,mMfold3,top3,p.valuea. Could you please explain what's the difference between top, top2 and top3?Is top indices for one vs rest; top2 for one vs second highest and top3 for one vs. third highest?b. In that case why isn't there a column called fold which would be the fold change that goes with top?c. Are the p-values fdr corrected? Also I got exact same p-values for p.value and p.value3 3. How do I know as to which index in the top columns match to which celltype in f? 4. I finally want to optimize my signature matrix to come up with the minimum number of genes without losing accuracy. Could you please suggest a way of doing that? I don't have cell counts associated with the RNA extracts for the individual samples. I would really appreciate your response and suggestions.Best regards,Sam.> setwd("C:/Users/bandyops/Desktop/WB_Decon_2014/cell_mix")> library("CellMix")Loading required package: pkgmakerLoading required package: registryLoading required package: NMFLoading required package: rngtoolsLoading required package: clusterNMF - BioConductor layer [OK] | Shared memory capabilities [NO: windows] | Cores 7/8Loading required package: csSAMLoading required package: compilerLoading required package: stringrLoading required package: GSEABaseLoading required package: annotateLoading required package: AnnotationDbiLoading required package: graphWarning messages:1: package ‘pkgmaker’ was built under R version 3.0.3 2: package ‘NMF’ was built under R version 3.0.3 3: package ‘rngtools’ was built under R version 3.0.3 4: package ‘cluster’ was built under R version 3.0.3  > imm <- read.table("scaled_rma_normalized_qced.txt", header=T, row.names=1, sep="\t")> imm <- as.matrix(imm)> target <- read.table("target.txt", header=T, row.names=1, sep="\t")> > if (sum(sort(rownames(target)) == sort(colnames(imm))) != length(rownames(target))) {+   stop ("ERROR: target rownames and RMA colnames do not match")+ }> > f <- factor(target$Cells)> scoring_pvalue  <- markerScoreAbbas(imm, f, statistic = "p.value", ntop = 3, log = F, lbase=3)> scoring_tstat <- markerScoreAbbas(imm, f, statistic = "statistic", ntop = 3, log = F, lbase=3)Error in res[, statistic] : subscript out of bounds> traceback()2: cbind(res[, 1L, drop = FALSE], res[, statistic], res[, -1L, drop = FALSE])1: markerScoreAbbas(imm, f, statistic = "statistic", ntop = 3, log = F,        lbase = 3) > sessionInfo()R version 3.0.1 (2013-05-16)Platform: x86_64-w64-mingw32/x64 (64-bit)locale:[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252    LC_MONETARY=English_United States.1252[4] LC_NUMERIC=C                           LC_TIME=English_United States.1252    attached base packages:[1] compiler  parallel  stats     graphics  grDevices utils     datasets  methods   base     other attached packages: [1] CellMix_1.6          GSEABase_1.22.0      graph_1.38.3         annotate_1.38.0      AnnotationDbi_1.22.6 [6] stringr_0.6.2        csSAM_1.2.4          NMF_0.20.5           Biobase_2.20.1       BiocGenerics_0.6.0  [11] cluster_1.15.2       rngtools_1.2.4       pkgmaker_0.20        registry_0.2        loaded via a namespace (and not attached): [1] beeswarm_0.1.6        bibtex_0.3-6          BiocInstaller_1.10.4  codetools_0.2-8       colorspace_1.2-4      [6] corpcor_1.6.6         DBI_0.2-7             dichromat_2.0-0       digest_0.6.4          doParallel_1.0.8     [11] foreach_1.4.2         genefilter_1.42.0     ggplot2_0.9.3.1       grid_3.0.1            gridBase_0.4-7       [16] gtable_0.1.2          gtools_3.4.0          IRanges_1.18.4        iterators_1.0.7       labeling_0.2         [21] limSolve_1.5.5        lpSolve_5.6.7         MASS_7.3-31           matrixStats_0.8.14    munsell_0.4.2        [26] plyr_1.8.1            preprocessCore_1.22.0 proto_0.3-10          quadprog_1.5-5        R.methodsS3_1.6.1    [31] RColorBrewer_1.0-5    Rcpp_0.11.1           reshape2_1.2.2        RSQLite_0.11.4        scales_0.2.3         [36] splines_3.0.1         stats4_3.0.1          survival_2.37-7       tools_3.0.1           XML_3.98-1.1         [41] xtable_1.7-3          		 	   		  
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