MeDIPS: warning when using "ttest" settings in MEDIPS.meth
2
0
Entering edit mode
stb • 0
@stb-11175
Last seen 7.4 years ago

Hi, 

I'm currently working with my MeDIP-seq data using MEDIPS in R. I have 18 IP samples (no Input) in 3 groups with PE50. For mapping, I have used bwa for Illumina with default settings in Galaxy.

Arguments for creating MEDIPS SET: 

BSgenome <- 'BSgenome.Mmusculus.UCSC.mm9'

uniq <- 1e-3

ws <- 500

chr.select <- c("chr1","chr2","chr3","chr4","chr5","chr6","chr7","chr8","chr9","chr10", "chr11", "chr12", "chr13", "chr14", "chr15", "chr16", "chr17", "chr18", "chr19")

paired = TRUE

 

However, when using MEDIPS.meth to calculate differential coverage between two groups (Control_MeDIP and LPS_MeDIP), I get the following warning: 

> mr.edgeR_Control_LPS <- MEDIPS.meth(MSet1 = Control_MeDIP, MSet2 = LPS_MeDIP, chr = chr.select, p.adj = "BH", diff.method = "ttest", MeDIP = F, CNV = F, minRowSum = 10, diffnorm = "rpkm")

Calculating genomic coordinates...
Creating Granges object for genome wide windows...
Preprocessing MEDIPS SET 1 in MSet1...
Preprocessing MEDIPS SET 2 in MSet1...
Preprocessing MEDIPS SET 3 in MSet1...
Preprocessing MEDIPS SET 4 in MSet1...
Preprocessing MEDIPS SET 5 in MSet1...
Preprocessing MEDIPS SET 6 in MSet1...
Preprocessing MEDIPS SET 1 in MSet2...
Preprocessing MEDIPS SET 2 in MSet2...
Preprocessing MEDIPS SET 3 in MSet2...
Preprocessing MEDIPS SET 4 in MSet2...
Preprocessing MEDIPS SET 5 in MSet2...
Preprocessing MEDIPS SET 6 in MSet2...
Extracting data for chr1 chr2 chr3 chr4 chr5 chr6 chr7 chr8 chr9 chr10 chr11 chr12 chr13 chr14 chr15 chr16 chr17 chr18 chr19 ...
4944695 windows on chr1 chr2 chr3 chr4 chr5 chr6 chr7 chr8 chr9 chr10 chr11 chr12 chr13 chr14 chr15 chr16 chr17 chr18 chr19 
Differential coverage analysis...
Extracting count windows with at least 10  reads...
Calculating score for 573068 windows...
Adjusting p.values for multiple testing...
Please note, log2 ratios are reported as log2(MSet1/MSet2).
Creating results table...
Adding differential coverage results...

Warning messages:
1: In err0^4/(na0 - 1) :
  longer object length is not a multiple of shorter object length
2: In err1^4/(na1 - 1) :
  longer object length is not a multiple of shorter object length
3: In (err0^2 + err1^2)^2/(err0^4/(na0 - 1) + err1^4/(na1 - 1)) :
  longer object length is not a multiple of shorter object length
4: In df[fi] <- (err0^2 + err1^2)^2/(err0^4/(na0 - 1) + err1^4/(na1 -  :
  number of items to replace is not a multiple of replacement length

 

If I increase minRowSum to 30 or change diff.method to "edgeR" I get rid of the warning, but since I have six replicates in each MEDIPS sets I would like to use "ttest", and I would like to decrease minRowSum to below 30. 

Any suggestions why I get this warning, and how I can use "ttest" without having to increase minRowSum to 30? 

Thanks!
 

Stine

Output from sessionInfo():

R version 3.3.1 (2016-06-21)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows >= 8 x64 (build 9200)

locale:
[1] LC_COLLATE=Danish_Denmark.1252  LC_CTYPE=Danish_Denmark.1252    LC_MONETARY=Danish_Denmark.1252 LC_NUMERIC=C                   
[5] LC_TIME=Danish_Denmark.1252    

attached base packages:
[1] stats4    parallel  stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] BSgenome.Mmusculus.UCSC.mm9_1.4.0 MEDIPS_1.23.2                     Rsamtools_1.25.1                  BiocInstaller_1.23.6             
 [5] BSgenome_1.41.2                   rtracklayer_1.33.11               Biostrings_2.41.4                 XVector_0.13.7                   
 [9] GenomicRanges_1.25.93             GenomeInfoDb_1.9.4                IRanges_2.7.12                    S4Vectors_0.11.10                
[13] BiocGenerics_0.19.2              

loaded via a namespace (and not attached):
 [1] AnnotationDbi_1.35.4        DNAcopy_1.47.1              edgeR_3.15.2                zlibbioc_1.19.0            
 [5] GenomicAlignments_1.9.6     BiocParallel_1.7.6          lattice_0.20-33             tools_3.3.1                
 [9] SummarizedExperiment_1.3.81 grid_3.3.1                  Biobase_2.33.0              DBI_0.5                    
[13] gtools_3.5.0                preprocessCore_1.35.0       Matrix_1.2-6                bitops_1.0-6               
[17] biomaRt_2.29.2              RCurl_1.95-4.8              RSQLite_1.0.0               limma_3.29.17              
[21] locfit_1.5-9.1              XML_3.98-1.4 

Output from traceback():

9: q2qnbinom(y, input.mean = input.mean, output.mean = output.mean, 
       dispersion = dispersion)
8: equalizeLibSizes.default(y, group = group, dispersion = disp, 
       lib.size = lib.size)
7: equalizeLibSizes(y, group = group, dispersion = disp, lib.size = lib.size)
6: estimateCommonDisp.default(y$counts, group = group, lib.size = lib.size, 
       tol = tol, rowsum.filter = rowsum.filter, verbose = verbose, 
       ...)
5: estimateCommonDisp(y$counts, group = group, lib.size = lib.size, 
       tol = tol, rowsum.filter = rowsum.filter, verbose = verbose, 
       ...)
4: estimateCommonDisp.DGEList(d)
3: edgeR::estimateCommonDisp(d)
2: MEDIPS.diffMeth(base = base, values = counts.medip, diff.method = "edgeR", 
       nMSets1 = nMSets1, nMSets2 = nMSets2, p.adj = p.adj, n.r.M1 = n.r.M1, 
       n.r.M2 = n.r.M2, MeDIP = MeDIP, minRowSum = minRowSum, diffnorm = diffnorm)
1: MEDIPS.meth(MSet1 = Control_MeDIP, MSet2 = LPS_MeDIP, chr = chr.select, 
       p.adj = "BH", diff.method = "edgeR", MeDIP = F, CNV = F, 
       minRowSum = 30, diffnorm = "none")

 

R medips medip-seq • 2.1k views
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Entering edit mode
Lukas Chavez ▴ 570
@lukas-chavez-5781
Last seen 6.7 years ago
USA/La Jolla/UCSD
Dear Stine, thank you for your reporting the warning in ’ttest’ mode. I am actually puzzled why the “ttest” mode depends on the minRowSum parameter and I cannot immediately reproduce the warning. Do you receive a result table in spite of the warning? If yes, can you figure out if there are specific columns missing? It will help me a lot to figure out at which stage of the workflow the warning comes up- is this after the “Adding differential coverage results…” and the workflow then crashes without returning any result table? All the best, Lukas On 15 Aug 2016, at 16:33, stb [bioc] <noreply@bioconductor.org<mailto:noreply@bioconductor.org>> wrote: Activity on a post you are following on support.bioconductor.org<https: support.bioconductor.org=""/> User stb<https: support.bioconductor.org="" u="" 11175=""/> wrote Question: MeDIPS: warning when using "ttest" settings in MEDIPS.meth<https: support.bioconductor.org="" p="" 86170=""/>: Hi, I'm currently working with my MeDIP-seq data using MEDIPS in R. I have 18 IP samples (no Input) in 3 groups with PE50. For mapping, I have used bwa for Illumina with default settings in Galaxy. Arguments for creating MEDIPS SET: BSgenome <- 'BSgenome.Mmusculus.UCSC.mm9' uniq <- 1e-3 ws <- 500 chr.select <- c("chr1","chr2","chr3","chr4","chr5","chr6","chr7","chr8","chr9","chr10", "chr11", "chr12", "chr13", "chr14", "chr15", "chr16", "chr17", "chr18", "chr19") paired = TRUE However, when using MEDIPS.meth to calculate differential coverage between two groups (Control_MeDIP and LPS_MeDIP), I get the following warning: > mr.edgeR_Control_LPS <- MEDIPS.meth(MSet1 = Control_MeDIP, MSet2 = LPS_MeDIP, chr = chr.select, p.adj = "BH", diff.method = "ttest", MeDIP = F, CNV = F, minRowSum = 10, diffnorm = "rpkm") Calculating genomic coordinates... Creating Granges object for genome wide windows... Preprocessing MEDIPS SET 1 in MSet1... Preprocessing MEDIPS SET 2 in MSet1... Preprocessing MEDIPS SET 3 in MSet1... Preprocessing MEDIPS SET 4 in MSet1... Preprocessing MEDIPS SET 5 in MSet1... Preprocessing MEDIPS SET 6 in MSet1... Preprocessing MEDIPS SET 1 in MSet2... Preprocessing MEDIPS SET 2 in MSet2... Preprocessing MEDIPS SET 3 in MSet2... Preprocessing MEDIPS SET 4 in MSet2... Preprocessing MEDIPS SET 5 in MSet2... Preprocessing MEDIPS SET 6 in MSet2... Extracting data for chr1 chr2 chr3 chr4 chr5 chr6 chr7 chr8 chr9 chr10 chr11 chr12 chr13 chr14 chr15 chr16 chr17 chr18 chr19 ... 4944695 windows on chr1 chr2 chr3 chr4 chr5 chr6 chr7 chr8 chr9 chr10 chr11 chr12 chr13 chr14 chr15 chr16 chr17 chr18 chr19 Differential coverage analysis... Extracting count windows with at least 10 reads... Calculating score for 573068 windows... Adjusting p.values for multiple testing... Please note, log2 ratios are reported as log2(MSet1/MSet2). Creating results table... Adding differential coverage results... Warning messages: 1: In err0^4/(na0 - 1) : longer object length is not a multiple of shorter object length 2: In err1^4/(na1 - 1) : longer object length is not a multiple of shorter object length 3: In (err0^2 + err1^2)^2/(err0^4/(na0 - 1) + err1^4/(na1 - 1)) : longer object length is not a multiple of shorter object length 4: In df[fi] <- (err0^2 + err1^2)^2/(err0^4/(na0 - 1) + err1^4/(na1 - : number of items to replace is not a multiple of replacement length If I increase minRowSum to 30 or change diff.method to "edgeR" I get rid of the warning, but since I have six replicates in each MEDIPS sets I would like to use "ttest", and I would like to decrease minRowSum to below 30. Any suggestions why I get this warning, and how I can use "ttest" without having to increase minRowSum to 30? Thanks! Stine Output from sessionInfo(): R version 3.3.1 (2016-06-21) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows >= 8 x64 (build 9200) locale: [1] LC_COLLATE=Danish_Denmark.1252 LC_CTYPE=Danish_Denmark.1252 LC_MONETARY=Danish_Denmark.1252 LC_NUMERIC=C [5] LC_TIME=Danish_Denmark.1252 attached base packages: [1] stats4 parallel stats graphics grDevices utils datasets methods base other attached packages: [1] BSgenome.Mmusculus.UCSC.mm9_1.4.0 MEDIPS_1.23.2 Rsamtools_1.25.1 BiocInstaller_1.23.6 [5] BSgenome_1.41.2 rtracklayer_1.33.11 Biostrings_2.41.4 XVector_0.13.7 [9] GenomicRanges_1.25.93 GenomeInfoDb_1.9.4 IRanges_2.7.12 S4Vectors_0.11.10 [13] BiocGenerics_0.19.2 loaded via a namespace (and not attached): [1] AnnotationDbi_1.35.4 DNAcopy_1.47.1 edgeR_3.15.2 zlibbioc_1.19.0 [5] GenomicAlignments_1.9.6 BiocParallel_1.7.6 lattice_0.20-33 tools_3.3.1 [9] SummarizedExperiment_1.3.81 grid_3.3.1 Biobase_2.33.0 DBI_0.5 [13] gtools_3.5.0 preprocessCore_1.35.0 Matrix_1.2-6 bitops_1.0-6 [17] biomaRt_2.29.2 RCurl_1.95-4.8 RSQLite_1.0.0 limma_3.29.17 [21] locfit_1.5-9.1 XML_3.98-1.4 Output from traceback(): 9: q2qnbinom(y, input.mean = input.mean, output.mean = output.mean, dispersion = dispersion) 8: equalizeLibSizes.default(y, group = group, dispersion = disp, lib.size = lib.size) 7: equalizeLibSizes(y, group = group, dispersion = disp, lib.size = lib.size) 6: estimateCommonDisp.default(y$counts, group = group, lib.size = lib.size, tol = tol, rowsum.filter = rowsum.filter, verbose = verbose, ...) 5: estimateCommonDisp(y$counts, group = group, lib.size = lib.size, tol = tol, rowsum.filter = rowsum.filter, verbose = verbose, ...) 4: estimateCommonDisp.DGEList(d) 3: edgeR::estimateCommonDisp(d) 2: MEDIPS.diffMeth(base = base, values = counts.medip, diff.method = "edgeR", nMSets1 = nMSets1, nMSets2 = nMSets2, p.adj = p.adj, n.r.M1 = n.r.M1, n.r.M2 = n.r.M2, MeDIP = MeDIP, minRowSum = minRowSum, diffnorm = diffnorm) 1: MEDIPS.meth(MSet1 = Control_MeDIP, MSet2 = LPS_MeDIP, chr = chr.select, p.adj = "BH", diff.method = "edgeR", MeDIP = F, CNV = F, minRowSum = 30, diffnorm = "none") ________________________________ Post tags: R, medips, medip-seq You may reply via email or visit MeDIPS: warning when using "ttest" settings in MEDIPS.meth
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Entering edit mode

Dear Lukas,

Thanks for your reply.

I’ve looked in to it in more details in order to provid the needed information.

The warning comes up after the “Adding differential coverage results…”, and I do get a result table, as I describe in detail here:

If I run the following command:

TEST1

MEDIPS.meth(MSet1 = Control_MeDIP, MSet2 = LPS_MeDIP, chr = chr.select, p.adj = "BH", diff.method = "ttest", MeDIP = F, CNV = F, minRowSum = 10, diffnorm = "rpkm")

I get the warning, but I also get a result table, and all the columns are there – score.log2.ratio, score.p.value, score.adj.p.value and score.

573,068 windows are tested, and the lowest score.p.value is 3.2025e-06 giving a score.adj.p.value of 0.9640.

 

If I instead run:

TEST2

MEDIPS.meth(MSet1 = Control_MeDIP, MSet2 = LPS_MeDIP, chr = chr.select, p.adj = "BH", diff.method = "ttest", MeDIP = F, CNV = F, minRowSum = 30, diffnorm = "rpkm")

I avoid the warning, and get a result table with the same columns as in TEST1.

Only 4603 windows are tested, and the lowest score.p.value is 0.002602 giving a score.adj.p.value of 0.7023.

 

If I then change the method for calculating differential coverage to edgeR instead of ttest, it does not give a warning and result table is made with the columns edgeR.logFC, edgeR.logCPM, edgeR.p.value and edgeR.adj.p.value as expected.:

TEST3:

MEDIPS.meth(MSet1 = Control_MeDIP, MSet2 = LPS_MeDIP, chr = chr.select, p.adj = "BH", diff.method = "edgeR", MeDIP = F, CNV = F, minRowSum = 10, diffnorm = "tmm")

However, I have a few question to this one:

1) 4,549,704 windows are tested here, out of a total number of 4,944,695 observations (window size = 500 bp, mm9 genome). I thought the number of tested windows were decided from the minRowSum value, but here I have the same number, 10, as in TEST1 where only 573,068 windows were tested?

2) The lowest edgeR.p.value in TEST3 is 1.149812e-07 giving an edgeR.adj.p.value of 0.5231. The second lowest edgeR.p.value is 5.577571e-07, but this gives an edgeR.adj.p.value of 1!? Can this be correct?

 

As a note, TEST3 takes much longer to finish than both TEST1 and TEST2, warning or not.

Hope the above information can help clarify why I get the warning. 

Best regards, 

Stine

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Dear Stine, thank you for sending additional information. I have to admit that I have not worked any more with the ttest functionality since we integrated the edgeR package. The difference in the total number of tested windows given the same minRowSum parameter is because it is applied to the counts in case of edgeR and to the rpkm values in case of ttest. I urgently need to update the reported message, please excuse the confusion. For the adjusted p-value there is not much I can comment on, since the two p-values are different and the adjusted p-values are being calculated by the p.adjust() function. I am still puzzled what causes the warning in some cases in ttest mode even though the result table is generated as expected. Can you please check, if the p-values calculated in the ttest settings are the same for a windows tested in both runs (minRowSum=10 and minRowSum=30)? It is expected that the adjusted p-values will be different, but the ‘raw’ p-values should be the same. Thank you and all the best, Lukas On 18 Aug 2016, at 12:09, stb [bioc] <noreply@bioconductor.org<mailto:noreply@bioconductor.org>> wrote: Activity on a post you are following on support.bioconductor.org<https: support.bioconductor.org=""/> User stb<https: support.bioconductor.org="" u="" 11175=""/> wrote Comment: MeDIPS: warning when using "ttest" settings in MEDIPS.meth<https: support.bioconductor.org="" p="" 86170="" #86286="">: Dear Lukas, Thanks for your reply. I’ve looked in to it in more details in order to provid the needed information. The warning comes up after the “Adding differential coverage results…”, and I do get a result table, as I describe in detail here: If I run the following command: TEST1 MEDIPS.meth(MSet1 = Control_MeDIP, MSet2 = LPS_MeDIP, chr = chr.select, p.adj = "BH", diff.method = "ttest", MeDIP = F, CNV = F, minRowSum = 10, diffnorm = "rpkm") I get the warning, but I also get a result table, and all the columns are there – score.log2.ratio, score.p.value, score.adj.p.value and score. 573,068 windows are tested, and the lowest score.p.value is 3.2025e-06 giving a score.adj.p.value of 0.9640. If I instead run: TEST2 MEDIPS.meth(MSet1 = Control_MeDIP, MSet2 = LPS_MeDIP, chr = chr.select, p.adj = "BH", diff.method = "ttest", MeDIP = F, CNV = F, minRowSum = 30, diffnorm = "rpkm") I avoid the warning, and get a result table with the same columns as in TEST1. Only 4603 windows are tested, and the lowest score.p.value is 0.002602 giving a score.adj.p.value of 0.7023. If I then change the method for calculating differential coverage to edgeR instead of ttest, it does not give a warning and result table is made with the columns edgeR.logFC, edgeR.logCPM, edgeR.p.value and edgeR.adj.p.value as expected.: TEST3: MEDIPS.meth(MSet1 = Control_MeDIP, MSet2 = LPS_MeDIP, chr = chr.select, p.adj = "BH", diff.method = "edgeR", MeDIP = F, CNV = F, minRowSum = 10, diffnorm = "tmm") However, I have a few question to this one: 1) 4,549,704 windows are tested here, out of a total number of 4,944,695 observations (window size = 500 bp, mm9 genome). I thought the number of tested windows were decided from the minRowSum value, but here I have the same number, 10, as in TEST1 where only 573,068 windows were tested? 2) The lowest edgeR.p.value in TEST3 is 1.149812e-07 giving an edgeR.adj.p.value of 0.5231. The second lowest edgeR.p.value is 5.577571e-07, but this gives an edgeR.adj.p.value of 1!? Can this be correct? As a note, TEST3 takes much longer to finish than both TEST1 and TEST2, warning or not. Hope the above information can help clarify why I get the warning. Best regards, Stine ________________________________ Post tags: R, medips, medip-seq You may reply via email or visit C: MeDIPS: warning when using "ttest" settings in MEDIPS.meth
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Dear Lukas, 

I checked the p.values and adjusted p values. As expected the p.values are identical within a window, and the adjusted p values are different using the ttest with different minRowSum.  

It makes sense with the different numbers of windows then. Maybe I can increase the minRowSum when using edgeR to lower the number of tested windows.

As I can conclude, it seems like I can use the result table generated using ttest despite the warning. 

Thanks for your help!

Best regards, 

Stine

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Entering edit mode
stb • 0
@stb-11175
Last seen 7.4 years ago

Dear Lukas, 

We have made a new observation concerning the 'ttest' functionality. 

If I have two groups with 5 and 6 replicates, and then compare the run of MEDIPS.meth with diff.method set to 'ttest' or 'edgeR', with diffnorm set to 'rpkm' and 'tmm', respectively, there is a huge difference in the number of windows included in the score calculation. Moreover, this depends on the minRowSum. The analyzes are with the mm9 reference genome, window size of 500 bp, and the uniq parameter set to 1e-5. 

When minRowSum is set to 1; 4,485,740 and 4,614,550 windows are included for ttest and edgeR, respectively. 

When minRowSum is set to 10; only 383.265 windows are included for ttest, whereas edgeR includes 4,553,980 which makes more sense to me, with the many replicates included. 

Does this have anything to do with the normalization method used, or is there another good explanation?

Thanks. 

Best regards, 

Stine

 

Example of output 

> MEDIPS.meth(MSet1 = Control_MeDIP, MSet2 = Treatment_MeDIP, chr = chr.select, p.adj = "fdr",
+ diff.method = "ttest", MeDIP = F, CNV = F, minRowSum = 10, diffnorm = "rpkm")
Calculating genomic coordinates...
Creating Granges object for genome wide windows...
Preprocessing MEDIPS SET 1 in MSet1...
Preprocessing MEDIPS SET 2 in MSet1...
Preprocessing MEDIPS SET 3 in MSet1...
Preprocessing MEDIPS SET 4 in MSet1...
Preprocessing MEDIPS SET 5 in MSet1...
Preprocessing MEDIPS SET 6 in MSet1...
Preprocessing MEDIPS SET 1 in MSet2...
Preprocessing MEDIPS SET 2 in MSet2...
Preprocessing MEDIPS SET 3 in MSet2...
Preprocessing MEDIPS SET 4 in MSet2...
Preprocessing MEDIPS SET 5 in MSet2...
Extracting data for chr1 chr2 chr3 chr4 chr5 chr6 chr7 chr8 chr9 chr10 chr11 chr12 chr13 chr14 chr15 chr16 chr17 chr18 chr19 ...
4944695 windows on chr1 chr2 chr3 chr4 chr5 chr6 chr7 chr8 chr9 chr10 chr11 chr12 chr13 chr14 chr15 chr16 chr17 chr18 chr19 
Differential coverage analysis...
Extracting count windows with at least 10  reads...
Calculating score for 383265 windows...
Adjusting p.values for multiple testing...
Please note, log2 ratios are reported as log2(MSet1/MSet2).
Creating results table...
Adding differential coverage results...
 

 

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Dear Stine, in case of the ttest, the minRowSum parameter is applied to the rpkm values instead of the counts. All the best, Lukas On 16. Jun 2017, at 15:49, stb [bioc] <noreply@bioconductor.org<mailto:noreply@bioconductor.org>> wrote: Activity on a post you are following on support.bioconductor.org<https: support.bioconductor.org=""/> User stb<https: support.bioconductor.org="" u="" 11175=""/> wrote Answer: MeDIPS: warning when using "ttest" settings in MEDIPS.meth<https: support.bioconductor.org="" p="" 86170="" #97147="">: Dear Lukas, We have made a new observation concerning the 'ttest' functionality. If I have two groups with 5 and 6 replicates, and then compare the run of MEDIPS.meth with diff.method set to 'ttest' or 'edgeR', with diffnorm set to 'rpkm' and 'tmm', respectively, there is a huge difference in the number of windows included in the score calculation. Moreover, this depends on the minRowSum. The analyzes are with the mm9 reference genome, window size of 500 bp, and the uniq parameter set to 1e-5. When minRowSum is set to 1; 4,485,740 and 4,614,550 windows are included for ttest and edgeR, respectively. When minRowSum is set to 10; only 383.265 windows are included for ttest, whereas edgeR includes 4,553,980 which makes more sense to me, with the many replicates included. Does this have anything to do with the normalization method used, or is there another good explanation? Thanks. Best regards, Stine Example of output > MEDIPS.meth(MSet1 = Control_MeDIP, MSet2 = Treatment_MeDIP, chr = chr.select, p.adj = "fdr", + diff.method = "ttest", MeDIP = F, CNV = F, minRowSum = 10, diffnorm = "rpkm") Calculating genomic coordinates... Creating Granges object for genome wide windows... Preprocessing MEDIPS SET 1 in MSet1... Preprocessing MEDIPS SET 2 in MSet1... Preprocessing MEDIPS SET 3 in MSet1... Preprocessing MEDIPS SET 4 in MSet1... Preprocessing MEDIPS SET 5 in MSet1... Preprocessing MEDIPS SET 6 in MSet1... Preprocessing MEDIPS SET 1 in MSet2... Preprocessing MEDIPS SET 2 in MSet2... Preprocessing MEDIPS SET 3 in MSet2... Preprocessing MEDIPS SET 4 in MSet2... Preprocessing MEDIPS SET 5 in MSet2... Extracting data for chr1 chr2 chr3 chr4 chr5 chr6 chr7 chr8 chr9 chr10 chr11 chr12 chr13 chr14 chr15 chr16 chr17 chr18 chr19 ... 4944695 windows on chr1 chr2 chr3 chr4 chr5 chr6 chr7 chr8 chr9 chr10 chr11 chr12 chr13 chr14 chr15 chr16 chr17 chr18 chr19 Differential coverage analysis... Extracting count windows with at least 10 reads... Calculating score for 383265 windows... Adjusting p.values for multiple testing... Please note, log2 ratios are reported as log2(MSet1/MSet2). Creating results table... Adding differential coverage results... ________________________________ Post tags: R, medips, medip-seq You may reply via email or visit A: MeDIPS: warning when using "ttest" settings in MEDIPS.meth
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