Question: maSigPro help- p. vector error
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5.6 years ago by
Guest User12k
Guest User12k wrote:
Hi, So I am doing a single series time course analysis of RNAseq data using maSigPro. My edesign object contains the labels of my samples along with time and replicates. My data object is a cdv spreadsheet of expression values for over 25,000 genes. When I attempt to run p.vector, I get this error: Error in dat[, as.character(rownames(dis))] : subscript out of bounds. I will post the session below. I'm not sure what it isn't happy with. I have researched around but cannot locate a solution. Any help would be greatly appreciated. Loading required package: edgeR Loading required package: limma > library(maSigPro) Loading required package: Biobase Loading required package: BiocGenerics Loading required package: parallel Attaching package: ???BiocGenerics??? The following objects are masked from ???package:parallel???: clusterApply, clusterApplyLB, clusterCall, clusterEvalQ, clusterExport, clusterMap, parApply, parCapply, parLapply, parLapplyLB, parRapply, parSapply, parSapplyLB The following object is masked from ???package:limma???: plotMA The following object is masked from ???package:stats???: xtabs The following objects are masked from ???package:base???: anyDuplicated, append, as.data.frame, as.vector, cbind, colnames, duplicated, eval, evalq, Filter, Find, get, intersect, is.unsorted, lapply, Map, mapply, match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank, rbind, Reduce, rep.int, rownames, sapply, setdiff, sort, table, tapply, union, unique, unlist Welcome to Bioconductor Vignettes contain introductory material; view with 'browseVignettes()'. To cite Bioconductor, see 'citation("Biobase")', and for packages 'citation("pkgname")'. Loading required package: MASS > setwd("Desktop") > edesign=read.delim("SI_edesign.txt") > data=read.csv("SI_normalized_counts.csv") > edesign=read.delim("SI_edesign.txt", rownames=1) Error in read.table(file = file, header = header, sep = sep, quote = quote, : unused argument (rownames = 1) > edesign X Time Replicate Group 1 AI6 0h 0 1 1 2 AJ6 0h 0 1 1 3 Ai8 0h 0 1 1 4 Ai11 0h 0 1 1 5 U25 0h 0 1 1 6 AF2 0h 0 1 1 7 AJ7 6h 6 2 1 8 Ak25 6h 6 2 1 9 Ak4 12h 12 3 1 10 Ak10 12h 12 3 1 11 Z12 24h 24 4 1 12 Z14 24h 24 4 1 13 V43 24h 24 4 1 14 Z18 24h 24 4 1 15 W20 24h 24 4 1 16 S6 24h 24 4 1 17 Y5 96h 96 5 1 18 Y18 96h 96 5 1 19 Y23 96h 96 5 1 20 Y24 96h 96 5 1 21 V40 96h 96 5 1 22 W22 10d 10 6 1 > edesign=read.delim("SI_edesign.txt", row.names=1) > edesign Time Replicate Group AI6 0h 0 1 1 AJ6 0h 0 1 1 Ai8 0h 0 1 1 Ai11 0h 0 1 1 U25 0h 0 1 1 AF2 0h 0 1 1 AJ7 6h 6 2 1 Ak25 6h 6 2 1 Ak4 12h 12 3 1 Ak10 12h 12 3 1 Z12 24h 24 4 1 Z14 24h 24 4 1 V43 24h 24 4 1 Z18 24h 24 4 1 W20 24h 24 4 1 S6 24h 24 4 1 Y5 96h 96 5 1 Y18 96h 96 5 1 Y23 96h 96 5 1 Y24 96h 96 5 1 V40 96h 96 5 1 W22 10d 10 6 1 > head(data) X 1 maker-Contig6333 -snap-gene-0.47-mRNA-1 transcript Name:"Similar to MYH11 Myosin-11 (Gallus gallus)" offset:0 AED:0.15 eAED:0.15 QI:0|0.89|0.82|1|0.71|0.72|40|470| 2 maker-Contig6333-snap-gene-0.51-mRNA-1 transcript Name:"Similar to NDE1 Nuclear distribution protein nudE homolog 1 (Gallus gallus)" offset:46 AED:0.16 eAED:0.16 QI:46|1|1|1|0.42|0.75|8|1603| 3 maker-Contig1111-pred_gff_snap_masked-gene-1.0-mRNA-1 transcript Name:"Similar to APBB2 Amyloid beta A4 precursor protein-binding family B member 2 (Homo sapiens)" offset:0 AED:1.00 eAED:1.00 QI:0|0|0|0|1|1|3|0| 4 maker-Contig3008-pred_gff_snap_masked- gene-0.0-mRNA-1 transcript Name:"Similar to dip2ba Disco-interacting protein 2 homolog B-A (Danio rerio)" offset:0 AED:1.00 eAED:1.00 QI:0|0|0|0|1|1|6|0| 5 maker-Contig11328-pred_gff_augustus_masked- gene-0.0-mRNA-1 transcript Name:"Similar to T-cell receptor alpha chain V region PY14 (Homo sapiens)" offset:0 AED:1.00 eAED:1.00 QI:0|0|0|0|1|1|3|0| 6 maker-Contig947-pred_gff_snap_masked-gene-1.0-mRNA-1 transcript Name:"Similar to Pou4f1 POU domain, class 4, transcription factor 1 (Mus musculus)" offset:0 AED:1.00 eAED:1.00 QI:0|-1|0|0|-1|1|1|0| AI6.0h AJ6.0h Ai8.0h Ai11.0h U25.0h 1 7.831961e+02 2.895929e+02 5.087201e+02 3.375122e+03 5.815714e+02 2 1.893800e+01 1.749886e+01 1.025642e+01 5.328988e+00 1.444428e+01 3 2.071037e+00 2.507320e-01 2.244464e+00 3.811020e+00 1.223929e-01 4 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 5 0.000000e+00 0.000000e+00 3.904084e-03 2.233175e-02 1.647046e-02 6 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 AF2.0h AJ7.6h Ak25.6h Ak4.12h Ak10.12h 1 3.888093e+01 3.103655e+02 9.131026e+01 2.363469e+02 2.093728e+02 2 1.177958e+01 7.809606e+00 2.944269e+00 2.171588e+00 6.813235e-01 3 3.358360e-02 3.360332e+00 2.405789e+00 9.749631e+00 2.208315e+00 4 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 5 1.109405e+00 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 6 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 Z12.24h Z14.24h V43.24h Z18.24h W20.24h 1 3.961911e+02 3.498425e+02 1.266360e+02 1.139859e+03 2.223295e+01 2 1.315224e+01 1.255917e+01 7.757897e+00 2.033740e+01 8.134378e+00 3 2.387005e+00 0.000000e+00 2.613100e+00 3.254617e+00 2.948026e+00 4 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 5 5.122860e-01 0.000000e+00 5.624271e-03 1.023987e-02 0.000000e+00 6 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 S6.24h Y5.96h Y18.96h Y23.96h Y24.96h 1 1.665659e+01 1.092473e+03 6.113765e+02 1.370150e+03 5.331807e+02 2 5.499539e+00 8.262508e+00 1.004341e+01 3.732239e+01 3.228396e+01 3 9.883312e+00 9.040282e+00 5.291639e+00 8.659485e-01 2.833013e+00 4 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 5 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 6 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 V40.96h W22.10d 1 1.047823e+02 6.341251e+01 2 1.535489e+01 3.389437e+00 3 2.056723e-01 4.160000e-17 4 4.160000e-17 4.160000e-17 5 4.032015e+00 4.160000e-17 6 4.160000e-17 4.160000e-17 > data=read.csv("SI_normalized_counts.csv", row.names=1) > head(data) AI6.0h AJ6.0h Ai8.0h Ai11.0h U25.0h 2 7.831961e+02 2.895929e+02 5.087201e+02 3.375122e+03 5.815714e+02 3 1.893800e+01 1.749886e+01 1.025642e+01 5.328988e+00 1.444428e+01 4 2.071037e+00 2.507320e-01 2.244464e+00 3.811020e+00 1.223929e-01 5 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 6 0.000000e+00 0.000000e+00 3.904084e-03 2.233175e-02 1.647046e-02 7 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 AF2.0h AJ7.6h Ak25.6h Ak4.12h Ak10.12h 2 3.888093e+01 3.103655e+02 9.131026e+01 2.363469e+02 2.093728e+02 3 1.177958e+01 7.809606e+00 2.944269e+00 2.171588e+00 6.813235e-01 4 3.358360e-02 3.360332e+00 2.405789e+00 9.749631e+00 2.208315e+00 5 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 6 1.109405e+00 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 7 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 Z12.24h Z14.24h V43.24h Z18.24h W20.24h 2 3.961911e+02 3.498425e+02 1.266360e+02 1.139859e+03 2.223295e+01 3 1.315224e+01 1.255917e+01 7.757897e+00 2.033740e+01 8.134378e+00 4 2.387005e+00 0.000000e+00 2.613100e+00 3.254617e+00 2.948026e+00 5 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 6 5.122860e-01 0.000000e+00 5.624271e-03 1.023987e-02 0.000000e+00 7 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 S6.24h Y5.96h Y18.96h Y23.96h Y24.96h 2 1.665659e+01 1.092473e+03 6.113765e+02 1.370150e+03 5.331807e+02 3 5.499539e+00 8.262508e+00 1.004341e+01 3.732239e+01 3.228396e+01 4 9.883312e+00 9.040282e+00 5.291639e+00 8.659485e-01 2.833013e+00 5 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 6 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 7 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 V40.96h W22.10d 2 1.047823e+02 6.341251e+01 3 1.535489e+01 3.389437e+00 4 2.056723e-01 4.160000e-17 5 4.160000e-17 4.160000e-17 6 4.032015e+00 4.160000e-17 7 4.160000e-17 4.160000e-17 > design=make.design.matrix(edesign, degree=5) > design$groups.vector [1] "Group" "Group" "Group" "Group" "Group" > fit=p.vector(data, design, Q=0.05, MT.adjust="BH", min.obs=0) Error in dat[, as.character(rownames(dis))] : subscript out of bounds > fit=p.vector(data, design, Q=0.05, MT.adjust="BH") Error in dat[, as.character(rownames(dis))] : subscript out of bounds > fit=p.vector(data, design, Q=0.05, MT.adjust="BH", min.obs=3) Error in dat[, as.character(rownames(dis))] : subscript out of bounds > fit=p.vector(data, design, Q=0.05, MT.adjust="BH", min.obs=20) Error in dat[, as.character(rownames(dis))] : subscript out of bounds > dis(data) Error: could not find function "dis" > dim(data) [1] 25385 22 > fit=p.vector(data, design, Q=0.05, MT.adjust="BH", min.obs=22) Error in dat[, as.character(rownames(dis))] : subscript out of bounds > data=as.matrix(data) > head(data) AI6.0h AJ6.0h Ai8.0h Ai11.0h U25.0h 2 7.831961e+02 2.895929e+02 5.087201e+02 3.375122e+03 5.815714e+02 3 1.893800e+01 1.749886e+01 1.025642e+01 5.328988e+00 1.444428e+01 4 2.071037e+00 2.507320e-01 2.244464e+00 3.811020e+00 1.223929e-01 5 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 6 0.000000e+00 0.000000e+00 3.904084e-03 2.233175e-02 1.647046e-02 7 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 AF2.0h AJ7.6h Ak25.6h Ak4.12h Ak10.12h 2 3.888093e+01 3.103655e+02 9.131026e+01 2.363469e+02 2.093728e+02 3 1.177958e+01 7.809606e+00 2.944269e+00 2.171588e+00 6.813235e-01 4 3.358360e-02 3.360332e+00 2.405789e+00 9.749631e+00 2.208315e+00 5 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 6 1.109405e+00 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 7 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 Z12.24h Z14.24h V43.24h Z18.24h W20.24h 2 3.961911e+02 3.498425e+02 1.266360e+02 1.139859e+03 2.223295e+01 3 1.315224e+01 1.255917e+01 7.757897e+00 2.033740e+01 8.134378e+00 4 2.387005e+00 0.000000e+00 2.613100e+00 3.254617e+00 2.948026e+00 5 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 6 5.122860e-01 0.000000e+00 5.624271e-03 1.023987e-02 0.000000e+00 7 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 S6.24h Y5.96h Y18.96h Y23.96h Y24.96h 2 1.665659e+01 1.092473e+03 6.113765e+02 1.370150e+03 5.331807e+02 3 5.499539e+00 8.262508e+00 1.004341e+01 3.732239e+01 3.228396e+01 4 9.883312e+00 9.040282e+00 5.291639e+00 8.659485e-01 2.833013e+00 5 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 6 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 0.000000e+00 7 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 4.160000e-17 V40.96h W22.10d 2 1.047823e+02 6.341251e+01 3 1.535489e+01 3.389437e+00 4 2.056723e-01 4.160000e-17 5 4.160000e-17 4.160000e-17 6 4.032015e+00 4.160000e-17 7 4.160000e-17 4.160000e-17 > fit=p.vector(data, design, Q=0.05, MT.adjust="BH", min.obs=0) Error in dat[, as.character(rownames(dis))] : subscript out of bounds -- output of sessionInfo(): > sessionInfo() R version 3.0.2 (2013-09-25) Platform: x86_64-apple-darwin10.8.0 (64-bit) locale: [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 attached base packages: [1] tcltk parallel stats graphics grDevices utils [7] datasets methods base other attached packages: [1] maSigPro_1.34.0 DynDoc_1.40.0 widgetTools_1.40.0 [4] MASS_7.3-29 Biobase_2.22.0 BiocGenerics_0.8.0 [7] edgeR_3.4.2 limma_3.18.9 loaded via a namespace (and not attached): [1] Mfuzz_2.20.0 tkWidgets_1.40.0 tools_3.0.2 -- Sent via the guest posting facility at bioconductor.org.
rnaseq masigpro a4 • 1.6k views
ADD COMMENTlink modified 3.9 years ago by Mª José Nueda90 • written 5.6 years ago by Guest User12k
Answer: maSigPro help- p. vector error
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gravatar for Mª José Nueda
3.9 years ago by
Spain
Mª José Nueda90 wrote:

Hi!

This error is due to rownames(design) and colnames(data) must be identical vectors and indicate array naming, as it's literaly in the details of p.vector help file.

min.obs is an argument to remove genes with a lot of missing value, genes with less than this number of true numerical values will be excluded from the analysis. If min.obs=0 no gene will be analysed.

MJ

 

ADD COMMENTlink written 3.9 years ago by Mª José Nueda90
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