[BioC] maSigPro help- p. vector error
Audra [guest]
guest at bioconductor.org
Sun Feb 9 23:42:22 CET 2014
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.
More information about the Bioconductor
mailing list