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Error: “pairedData” is not a defined class #1

Closed amab424 closed 8 years ago

amab424 commented 8 years ago

I get the following error when I run MultiRankSeq for paired samples:

data(exampleCounts) data(exampleCountsDiff) result<-MultiRankSeqReport(output="MultiRankSeq1.html",diffResult=exampleCountsDiff,rawCounts=exampleCounts) [1] "The MultiRankSeq report was generated in C:/Users/basudana/Box Sync/R/OvaMetsProject/MultiRankSeq/MultiRankSeq1.html"

Not run:

An example: from counts data to report, paired data

this code may take two minutes, because performing baySeq, DESeq2, and edgeR may be slow.

result<-MultiRankSeqReport(output="MultiRankSeq2.html",rawCounts=exampleCounts,group=c(0,0,0,1,1,1),paired=c(1:3,1:3) ) converting counts to integer mode estimating size factors estimating dispersions gene-wise dispersion estimates mean-dispersion relationship final dispersion estimates fitting model and testing Error in getClass(Class, where = topenv(parent.frame())) : “pairedData” is not a defined class

Can you please help me with that?

thanks

slzhao commented 8 years ago

Hello,

The error was due to the changes in baySeq package. But I can't understand its new document for paired data analysis. I've wrote a email to them and will change it once I get their reply.

Best, Shilin

2016-04-19 12:22 GMT-05:00 amab424 notifications@github.com:

I get the following error when I run MultiRankSeq for paired samples:

data(exampleCounts) data(exampleCountsDiff)

result<-MultiRankSeqReport(output="MultiRankSeq1.html",diffResult=exampleCountsDiff,rawCounts=exampleCounts) [1] "The MultiRankSeq report was generated in C:/Users/basudana/Box Sync/R/OvaMetsProject/MultiRankSeq/MultiRankSeq1.html" Not run:

An example: from counts data to report, paired data

this code may take two minutes, because performing baySeq, DESeq2, and

edgeR may be slow. result<-MultiRankSeqReport(output="MultiRankSeq2.html",rawCounts=exampleCounts,group=c(0,0,0,1,1,1),paired=c(1:3,1:3) ) converting counts to integer mode estimating size factors estimating dispersions gene-wise dispersion estimates mean-dispersion relationship final dispersion estimates fitting model and testing Error in getClass(Class, where = topenv(parent.frame())) : “pairedData” is not a defined class

Can you please help me with that?

thanks

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amab424 commented 8 years ago

If you look at section 2 of the vignette at http://bioconductor.org/packages/devel/bioc/vignettes/baySeq/inst/doc/baySeq_generic.pdf you will find the current procedure for paired data analysis, which is to construct a countData object with a three-dimensional data structure; e.g.

pairCD <- new("countData", data = array(c(pairData[,1:4], pairData[,5:8]), dim = c(nrow(pairData), 4, 2)), replicates = c(1,1,2,2), groups = list(NDE = c(1,1,1,1), DE = c(1,1,2,2)), densityFunction = bbDensity)

Do you think you can update your R code base on that?

Thanks, Ahmed

slzhao commented 8 years ago

Yes. That's where I got confused. It is an example of 4 samples so it sets replicates = c(1,1,2,2). How can I wrote it if I have 5 samples?

2016-04-20 9:40 GMT-05:00 amab424 notifications@github.com:

If you look at section 2 of the vignette at http://bioconductor.org/packages/devel/bioc/vignettes/baySeq/inst/doc/baySeq_generic.pdf you will find the current procedure for paired data analysis, which is to construct a countData object with a three-dimensional data structure; e.g.

pairCD <- new("countData", data = array(c(pairData[,1:4], pairData[,5:8]), dim = c(nrow(pairData), 4, 2)), replicates = c(1,1,2,2), groups = list(NDE = c(1,1,1,1), DE = c(1,1,2,2)), densityFunction = bbDensity)

Do you think you can update your R code base on that?

Thanks, Ahmed

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amab424 commented 8 years ago

I'm assuming you since have paired samples you will only have even numbers like 4,6,8,..

slzhao commented 8 years ago

For example, I have a dataset with 5 patients. They were treated by drug1 and drug2. The 1-5 columns are: Patient1Drug1 Patient2Drug1 Patient3Drug1 Patient4Drug1 Patient5Drug1. The 6-10 columns are: Patient1Drug2 Patient2Drug2 Patient3Drug2 Patient4Drug2 Patient5Drug2.

So this is a paired data, drug 1 and drug 2 are two groups, and each patient is a pair in drug 1 and drug 2.

How should I write replicates and DE?

2016-04-20 16:22 GMT-05:00 amab424 notifications@github.com:

I'm assuming you since have paired samples you will only have even numbers like 4,6,8,..

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slzhao commented 8 years ago

Got reply from baySeq author and just updated the package. Would you please try it again? Thanks!

2016-04-20 16:31 GMT-05:00 zhao shilin zhaoshilin@gmail.com:

For example, I have a dataset with 5 patients. They were treated by drug1 and drug2. The 1-5 columns are: Patient1Drug1 Patient2Drug1 Patient3Drug1 Patient4Drug1 Patient5Drug1. The 6-10 columns are: Patient1Drug2 Patient2Drug2 Patient3Drug2 Patient4Drug2 Patient5Drug2.

So this is a paired data, drug 1 and drug 2 are two groups, and each patient is a pair in drug 1 and drug 2.

How should I write replicates and DE?

2016-04-20 16:22 GMT-05:00 amab424 notifications@github.com:

I'm assuming you since have paired samples you will only have even numbers like 4,6,8,..

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amab424 commented 8 years ago

Hi Shilin,

the code runs to the end but there are errors in the outputs: in the csv file: "1-Likelihood(baySeq)" and "AdjLikelihood(baySeq)" columns are 'NA' for all rows. Also, the Volcano plot for baySeq is not produced and gives the error: ## Error in plot.window(...): need finite 'ylim' values As you would expect based on that, Venn plots don't make sense.

Thanks,

Ahmed

slzhao commented 8 years ago

It works in my R. Here is the sessionInfo in my R, would you please compare with yours? I think it may related with the version of baySeq package.

R version 3.2.3 (2015-12-10)

Platform: x86_64-w64-mingw32/x64 (64-bit)

Running under: Windows 7 x64 (build 7601) Service Pack 1

locale:

[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United

States.1252 LC_MONETARY=English_United States.1252 LC_NUMERIC=C LC_TIME=English_United States.1252

attached base packages:

[1] grid parallel stats4 stats graphics grDevices

utils datasets methods base

other attached packages:

[1] MultiRankSeq_1.2.6 knitr_1.12.3

VennDiagram_1.6.17 futile.logger_1.4.1 baySeq_2.4.1 perm_1.0-0.0 abind_1.4-3

[8] edgeR_3.12.1 limma_3.26.9

DESeq2_1.10.1 RcppArmadillo_0.6.700.3.0 Rcpp_0.12.4 SummarizedExperiment_1.0.2 Biobase_2.30.0

[15] GenomicRanges_1.22.4 GenomeInfoDb_1.6.3

IRanges_2.4.8 S4Vectors_0.8.11 BiocGenerics_0.16.1 devtools_1.10.0

loaded via a namespace (and not attached):

[1] genefilter_1.52.1 locfit_1.5-9.1 splines_3.2.3

lattice_0.20-33 colorspace_1.2-6 survival_2.38-3 XML_3.98-1.4 foreign_0.8-66 withr_1.0.1

[10] DBI_0.3.1 BiocParallel_1.4.3 RColorBrewer_1.1-2

lambda.r_1.1.7 plyr_1.8.3 stringr_1.0.0 zlibbioc_1.16.0 munsell_0.4.3 gtable_0.2.0

[19] evaluate_0.8.3 memoise_1.0.0 latticeExtra_0.6-28

geneplotter_1.48.0 curl_0.9.6 AnnotationDbi_1.32.3 highr_0.5.1 acepack_1.3-3.3 xtable_1.8-2

[28] formatR_1.3 scales_0.4.0 Hmisc_3.17-3

annotate_1.48.0 XVector_0.10.0 gridExtra_2.2.1 ggplot2_2.1.0 digest_0.6.9 stringi_1.0-1

[37] tools_3.2.3 magrittr_1.5 RSQLite_1.0.0

Formula_1.2-1 cluster_2.0.3 futile.options_1.0.0 httr_1.1.0 R6_2.1.2 rpart_4.1-10

[46] nnet_7.3-12 git2r_0.14.0

2016-04-21 13:09 GMT-05:00 amab424 notifications@github.com:

Hi Shilin,

the code runs to the end but there are errors in the outputs: in the csv file: "1-Likelihood(baySeq)" and "AdjLikelihood(baySeq)" columns are 'NA' for all rows. Also, the Volcano plot for baySeq is not produced and gives the error: ## Error in plot.window(...): need finite 'ylim' values As you would expect based on that, Venn plots don't make sense.

Thanks,

Ahmed

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amab424 commented 8 years ago

The code doesn't give me error. I see errors in the CSV file and plots produced. Here's my session info:

sessionInfo() R version 3.2.3 (2015-12-10) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 7 x64 (build 7601) Service Pack 1

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] grid parallel stats4 stats graphics grDevices utils datasets methods base

other attached packages: [1] corrplot_0.76 ggplot2_2.1.0 reshape_0.8.5 MultiRankSeq_1.2.6 knitr_1.12.3
[6] VennDiagram_1.6.17 futile.logger_1.4.1 baySeq_2.5.5 perm_1.0-0.0 abind_1.4-3
[11] DESeq2_1.10.1 RcppArmadillo_0.6.700.3.0 Rcpp_0.12.4 SummarizedExperiment_1.0.2 Biobase_2.30.0
[16] GenomicRanges_1.22.4 GenomeInfoDb_1.6.3 IRanges_2.4.8 S4Vectors_0.8.11 BiocGenerics_0.16.1
[21] edgeR_3.12.1 limma_3.26.9 devtools_1.11.0

loaded via a namespace (and not attached): [1] locfit_1.5-9.1 lattice_0.20-33 digest_0.6.9 R6_2.1.2 plyr_1.8.3 futile.options_1.0.0 acepack_1.3-3.3
[8] RSQLite_1.0.0 evaluate_0.8.3 httr_1.1.0 highr_0.5.1 zlibbioc_1.16.0 curl_0.9.7 annotate_1.48.0
[15] rpart_4.1-10 Matrix_1.2-5 labeling_0.3 splines_3.2.3 BiocParallel_1.4.3 geneplotter_1.48.0 stringr_1.0.0
[22] foreign_0.8-66 munsell_0.4.3 nnet_7.3-12 gridExtra_2.2.1 Hmisc_3.17-3 XML_3.98-1.4 withr_1.0.1
[29] xtable_1.8-2 gtable_0.2.0 DBI_0.3.1 git2r_0.14.0 magrittr_1.5 formatR_1.3 scales_0.4.0
[36] stringi_1.0-1 XVector_0.10.0 genefilter_1.52.1 latticeExtra_0.6-28 Formula_1.2-1 lambda.r_1.1.7 RColorBrewer_1.1-2
[43] tools_3.2.3 survival_2.39-2 AnnotationDbi_1.32.3 colorspace_1.2-6 cluster_2.0.4 memoise_1.0.0

slzhao commented 8 years ago

CSV file and Plot are good in my side. I think here is the issue: baySeq_2.5.5 This is the development version and the author may changed some variable names in it.

2016-04-21 16:36 GMT-05:00 amab424 notifications@github.com:

The code doesn't give me error. I see errors in the CSV file and plots produced. Here's my session info:

sessionInfo() R version 3.2.3 (2015-12-10) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 7 x64 (build 7601) Service Pack 1

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] grid parallel stats4 stats graphics grDevices utils datasets methods base

other attached packages: [1] corrplot_0.76 ggplot2_2.1.0 reshape_0.8.5 MultiRankSeq_1.2.6 knitr_1.12.3

[6] VennDiagram_1.6.17 futile.logger_1.4.1 baySeq_2.5.5 perm_1.0-0.0 abind_1.4-3

[11] DESeq2_1.10.1 RcppArmadillo_0.6.700.3.0 Rcpp_0.12.4 SummarizedExperiment_1.0.2 Biobase_2.30.0

[16] GenomicRanges_1.22.4 GenomeInfoDb_1.6.3 IRanges_2.4.8 S4Vectors_0.8.11 BiocGenerics_0.16.1

[21] edgeR_3.12.1 limma_3.26.9 devtools_1.11.0

loaded via a namespace (and not attached): [1] locfit_1.5-9.1 lattice_0.20-33 digest_0.6.9 R6_2.1.2 plyr_1.8.3 futile.options_1.0.0 acepack_1.3-3.3

[8] RSQLite_1.0.0 evaluate_0.8.3 httr_1.1.0 highr_0.5.1 zlibbioc_1.16.0 curl_0.9.7 annotate_1.48.0

[15] rpart_4.1-10 Matrix_1.2-5 labeling_0.3 splines_3.2.3 BiocParallel_1.4.3 geneplotter_1.48.0 stringr_1.0.0

[22] foreign_0.8-66 munsell_0.4.3 nnet_7.3-12 gridExtra_2.2.1 Hmisc_3.17-3 XML_3.98-1.4 withr_1.0.1

[29] xtable_1.8-2 gtable_0.2.0 DBI_0.3.1 git2r_0.14.0 magrittr_1.5 formatR_1.3 scales_0.4.0

[36] stringi_1.0-1 XVector_0.10.0 genefilter_1.52.1 latticeExtra_0.6-28 Formula_1.2-1 lambda.r_1.1.7 RColorBrewer_1.1-2

[43] tools_3.2.3 survival_2.39-2 AnnotationDbi_1.32.3 colorspace_1.2-6 cluster_2.0.4 memoise_1.0.0

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amab424 commented 8 years ago

I installed the baySeq version you have (2.4.1) and repeated the analysis. I still have the same problem. here are the first few lines of the csv file. you can see the baySeq columns are always NA. DESeq and edger are ok

log2FoldChange(DESeq2)  pValue(DESeq2)  pAdj(DESeq2)    log2FoldChange(edgeR)   pValue(edgeR)   pAdj(edgeR) log2FoldChange(raw) 1-Likelihood(baySeq)    AdjLikelihood(baySeq)   rank(DESeq) rank(edgeR) rank(baySeq)    rankMethod1

ENSG00000264424 -6.172199452 2.58E-67 7.26E-63 -6.731236769 9.77E-53 4.64E-48 -6.315133031 NA NA 1 1 32214 32216 ENSG00000133020 -6.173883395 3.75E-61 5.29E-57 -6.845168415 1.62E-51 3.86E-47 -6.377725492 NA NA 2 2 34005 34009 ENSG00000244094 7.906201931 4.23E-52 3.98E-48 11.84553035 1.09E-37 1.73E-33 Inf NA NA 3 3 8502 8508 ENSG00000089225 -6.489043128 9.56E-49 6.73E-45 -7.591912822 9.48E-37 1.13E-32 -7.361943774 NA NA 4 4 24525 24533 ENSG00000197953 -5.316210994 3.77E-43 2.12E-39 -5.968441372 7.42E-26 2.21E-22 -5.436236665 NA NA 5 16 37673 37694 ENSG00000272736 -5.500100787 1.35E-39 6.34E-36 -6.436560209 7.55E-31 3.28E-27 -5.222971236 NA NA 6 10 3885 3901 ENSG00000182230 4.122119483 1.81E-39 7.30E-36 4.342877681 1.31E-29 4.78E-26 4.4997931 NA NA 7 13 30760 30780

amab424 commented 8 years ago

also, here are my paired information: Samples: The samples labeled by 0 will be taken as reference and compared with samples labeled by 1:

0029-50T 0030-50T 0031-50T 0032-50T 0033-50T 0034-50T 0035-50T 0003-56M 0004-56M 0006-56M 0008-56M 0009-56M 0014-56M 0018-56M

0 0 0 0 0 0 0 1 1 1 1 1 1 1

Pairs (The samples labeled by the same number will be taken as a pair):

0029-50T 0030-50T 0031-50T 0032-50T 0033-50T 0034-50T 0035-50T 0003-56M 0004-56M 0006-56M 0008-56M 0009-56M 0014-56M 0018-56M

1 2 3 4 5 6 7 1 2 3 4 5 6 7

slzhao commented 8 years ago

Updated a new version. Tested it with following code and it worked. Please let me know if it works for you.

set.seed(123) count<-matrix(sample(1:1000,4200,replace = TRUE),ncol=14) row.names(count)<-paste0("Gene",1:300) colnames(count)<-paste0("Sample",1:14) head(count) library(MultiRankSeq) group=rep(c(0,1),each=7) paired=rep(1:7,2) result<-MultiRankSeqReport(output="MultiRankSeq3.html",rawCounts=count,group=group,paired=paired)

2016-04-21 17:18 GMT-05:00 amab424 notifications@github.com:

also, here are my paired information: Samples: The samples labeled by 0 will be taken as reference and compared with samples labeled by 1: 0029-50T 0030-50T 0031-50T 0032-50T 0033-50T 0034-50T 0035-50T 0003-56M 0004-56M 0006-56M 0008-56M 0009-56M 0014-56M 0018-56M 0 0 0 0 0 0 0 1 1 1 1 1 1 1

Pairs (The samples labeled by the same number will be taken as a pair): 0029-50T 0030-50T 0031-50T 0032-50T 0033-50T 0034-50T 0035-50T 0003-56M 0004-56M 0006-56M 0008-56M 0009-56M 0014-56M 0018-56M 1 2 3 4 5 6 7 1 2 3 4 5 6 7

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amab424 commented 8 years ago

Thank you. I think it woks well this time. The only thing that looks weird is the Venn plot for "log2 fold change=>1". It looks weird in both my data and the example you sent. Ahmed Date: Thu, 21 Apr 2016 23:58:39 -0700 From: notifications@github.com To: MultiRankSeq@noreply.github.com CC: amab424@hotmail.com; author@noreply.github.com Subject: Re: [slzhao/MultiRankSeq] Error: “pairedData” is not a defined class (#1)

Updated a new version. Tested it with following code and it worked.

Please let me know if it works for you.

set.seed(123)

count<-matrix(sample(1:1000,4200,replace = TRUE),ncol=14)

row.names(count)<-paste0("Gene",1:300)

colnames(count)<-paste0("Sample",1:14)

head(count)

library(MultiRankSeq)

group=rep(c(0,1),each=7)

paired=rep(1:7,2)

result<-MultiRankSeqReport(output="MultiRankSeq3.html",rawCounts=count,group=group,paired=paired)

2016-04-21 17:18 GMT-05:00 amab424 notifications@github.com:

also, here are my paired information:

Samples: The samples labeled by 0 will be taken as reference and compared

with samples labeled by 1:

0029-50T 0030-50T 0031-50T 0032-50T 0033-50T 0034-50T 0035-50T 0003-56M

0004-56M 0006-56M 0008-56M 0009-56M 0014-56M 0018-56M 0 0 0 0 0 0 0 1 1 1

1 1 1 1

Pairs (The samples labeled by the same number will be taken as a pair):

0029-50T 0030-50T 0031-50T 0032-50T 0033-50T 0034-50T 0035-50T 0003-56M

0004-56M 0006-56M 0008-56M 0009-56M 0014-56M 0018-56M 1 2 3 4 5 6 7 1 2 3

4 5 6 7

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slzhao commented 8 years ago

Did you mean in the venn of "log2 fold change >=1", two circles were covered by edgeR circle? It is normal as their significant genes were all covered by significant genes from edgeR.

2016-04-22 10:41 GMT-05:00 amab424 notifications@github.com:

Thank you. I think it woks well this time. The only thing that looks weird is the Venn plot for "log2 fold change=>1". It looks weird in both my data and the example you sent. Ahmed Date: Thu, 21 Apr 2016 23:58:39 -0700 From: notifications@github.com To: MultiRankSeq@noreply.github.com CC: amab424@hotmail.com; author@noreply.github.com Subject: Re: [slzhao/MultiRankSeq] Error: “pairedData” is not a defined class (#1)

Updated a new version. Tested it with following code and it worked.

Please let me know if it works for you.

set.seed(123)

count<-matrix(sample(1:1000,4200,replace = TRUE),ncol=14)

row.names(count)<-paste0("Gene",1:300)

colnames(count)<-paste0("Sample",1:14)

head(count)

library(MultiRankSeq)

group=rep(c(0,1),each=7)

paired=rep(1:7,2)

result<-MultiRankSeqReport(output="MultiRankSeq3.html",rawCounts=count,group=group,paired=paired)

2016-04-21 17:18 GMT-05:00 amab424 notifications@github.com:

also, here are my paired information:

Samples: The samples labeled by 0 will be taken as reference and compared

with samples labeled by 1:

0029-50T 0030-50T 0031-50T 0032-50T 0033-50T 0034-50T 0035-50T 0003-56M

0004-56M 0006-56M 0008-56M 0009-56M 0014-56M 0018-56M 0 0 0 0 0 0 0 1 1 1

1 1 1 1

Pairs (The samples labeled by the same number will be taken as a pair):

0029-50T 0030-50T 0031-50T 0032-50T 0033-50T 0034-50T 0035-50T 0003-56M

0004-56M 0006-56M 0008-56M 0009-56M 0014-56M 0018-56M 1 2 3 4 5 6 7 1 2 3

4 5 6 7

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amab424 commented 8 years ago

Ok then all is working well. Thank you very much for the effort to make this work. I only have one more question: is there an option within this package to compare only two packages instead of three? e.g. Deseq and edger only?

Thanks Ahmed

On Apr 22, 2016, at 12:01 PM, slzhao notifications@github.com wrote:

Did you mean in the venn of "log2 fold change >=1", two circles were covered by edgeR circle? It is normal as their significant genes were all covered by significant genes from edgeR.

2016-04-22 10:41 GMT-05:00 amab424 notifications@github.com:

Thank you. I think it woks well this time. The only thing that looks weird is the Venn plot for "log2 fold change=>1". It looks weird in both my data and the example you sent. Ahmed Date: Thu, 21 Apr 2016 23:58:39 -0700 From: notifications@github.com To: MultiRankSeq@noreply.github.com CC: amab424@hotmail.com; author@noreply.github.com Subject: Re: [slzhao/MultiRankSeq] Error: “pairedData” is not a defined class (#1)

Updated a new version. Tested it with following code and it worked.

Please let me know if it works for you.

set.seed(123)

count<-matrix(sample(1:1000,4200,replace = TRUE),ncol=14)

row.names(count)<-paste0("Gene",1:300)

colnames(count)<-paste0("Sample",1:14)

head(count)

library(MultiRankSeq)

group=rep(c(0,1),each=7)

paired=rep(1:7,2)

result<-MultiRankSeqReport(output="MultiRankSeq3.html",rawCounts=count,group=group,paired=paired)

2016-04-21 17:18 GMT-05:00 amab424 notifications@github.com:

also, here are my paired information:

Samples: The samples labeled by 0 will be taken as reference and compared

with samples labeled by 1:

0029-50T 0030-50T 0031-50T 0032-50T 0033-50T 0034-50T 0035-50T 0003-56M

0004-56M 0006-56M 0008-56M 0009-56M 0014-56M 0018-56M 0 0 0 0 0 0 0 1 1 1

1 1 1 1

Pairs (The samples labeled by the same number will be taken as a pair):

0029-50T 0030-50T 0031-50T 0032-50T 0033-50T 0034-50T 0035-50T 0003-56M

0004-56M 0006-56M 0008-56M 0009-56M 0014-56M 0018-56M 1 2 3 4 5 6 7 1 2 3

4 5 6 7

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https://github.com/slzhao/MultiRankSeq/issues/1#issuecomment-213137298

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slzhao commented 8 years ago

Good question! I am developing it but there is no option to do it at this time.

Best, Shilin

2016-04-22 11:06 GMT-05:00 amab424 notifications@github.com:

Ok then all is working well. Thank you very much for the effort to make this work. I only have one more question: is there an option within this package to compare only two packages instead of three? e.g. Deseq and edger only?

Thanks Ahmed

On Apr 22, 2016, at 12:01 PM, slzhao notifications@github.com wrote:

Did you mean in the venn of "log2 fold change >=1", two circles were covered by edgeR circle? It is normal as their significant genes were all covered by significant genes from edgeR.

2016-04-22 10:41 GMT-05:00 amab424 notifications@github.com:

Thank you. I think it woks well this time. The only thing that looks weird is the Venn plot for "log2 fold change=>1". It looks weird in both my data and the example you sent. Ahmed Date: Thu, 21 Apr 2016 23:58:39 -0700 From: notifications@github.com To: MultiRankSeq@noreply.github.com CC: amab424@hotmail.com; author@noreply.github.com Subject: Re: [slzhao/MultiRankSeq] Error: “pairedData” is not a defined class (#1)

Updated a new version. Tested it with following code and it worked.

Please let me know if it works for you.

set.seed(123)

count<-matrix(sample(1:1000,4200,replace = TRUE),ncol=14)

row.names(count)<-paste0("Gene",1:300)

colnames(count)<-paste0("Sample",1:14)

head(count)

library(MultiRankSeq)

group=rep(c(0,1),each=7)

paired=rep(1:7,2)

result<-MultiRankSeqReport(output="MultiRankSeq3.html",rawCounts=count,group=group,paired=paired)

2016-04-21 17:18 GMT-05:00 amab424 notifications@github.com:

also, here are my paired information:

Samples: The samples labeled by 0 will be taken as reference and compared

with samples labeled by 1:

0029-50T 0030-50T 0031-50T 0032-50T 0033-50T 0034-50T 0035-50T 0003-56M

0004-56M 0006-56M 0008-56M 0009-56M 0014-56M 0018-56M 0 0 0 0 0 0 0 1 1 1

1 1 1 1

Pairs (The samples labeled by the same number will be taken as a pair):

0029-50T 0030-50T 0031-50T 0032-50T 0033-50T 0034-50T 0035-50T 0003-56M

0004-56M 0006-56M 0008-56M 0009-56M 0014-56M 0018-56M 1 2 3 4 5 6 7 1 2 3

4 5 6 7

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