User: bioinf

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bioinf0
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Posts by bioinf

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Comment: C: DESeq2 for mulitple tissues under 2 conditions and contrast options
... Thanks Michael. I am aware of that and was just wondering if inside DESeq2 there is some automated way while using contrast. Anyways, thank you so much for answering my queries. :) ...
written 6 months ago by bioinf0
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Comment: C: DESeq2 for mulitple tissues under 2 conditions and contrast options
... Thanks Michael. I think I have been unable to make my query clear. I will explain with an example. Whether I use any of the three below mentioned options, my output is same. head(assay(rld), 5) # For my whole data head(assay(rld_dds4group_deseq), 5) # From my previous posts in ...
written 6 months ago by bioinf0
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Comment: C: DESeq2 for mulitple tissues under 2 conditions and contrast options
... Vignette says: select <- order(rowMeans(counts(dds,normalized=TRUE)) which is for whole data. I am confused on how I can get normalized count dataframe for the samples belong to the group mentioned in the contrast. :(   ...
written 6 months ago by bioinf0
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Comment: C: DESeq2 for mulitple tissues under 2 conditions and contrast options
... Thanks Michael ! I did: res_ACwild <- results(dds4group_deseq, contrast=c("group","Awild","Cwild")) After subset and ordered by padj, I am interested to annotate the list of genes with ensembl and then heatmap, so I wanted to have a normalized dataframe, but it gave me a dataframe including ot ...
written 6 months ago by bioinf0
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Comment: C: DESEq2 for mulitple tissues under 2 conditions
... Michael Love # I tried the following for (1): dds4group <- dds dds4group$group <- factor(paste0(dds4group$tissue, dds4group$condition)) design(dds4group) <- ~ group dds4group_deseq <- DESeq(dds4group) estimating size factors estimating dispersions gene-wise dispersion estimates mean- ...
written 6 months ago by bioinf0
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Comment: C: DESEq2 for mulitple tissues under 2 conditions
...   Thanks Michael Love. I cleaned my data as per your suggestions and ran DESeq2. Its awesome. :-) I did: dds <- DESeqDataSetFromMatrix(countData = cts, colData = coldata, design = ~tissue + condition) dds$condition <- factor(dds$condition, levels = c("wild","mutant")) dds_deseq <- DESeq ...
written 6 months ago by bioinf0
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Comment: C: DESEq2 for mulitple tissues under 2 conditions
... So I can use:   dds$condition <- factor(dds$condition, levels = c("wild","mutant")) How can I keep replicate numbers also during analysis and heatmap so that I can see if there is any variation between replicates? In (iii) I want to compare between different tissue types from mutant. ...
written 7 months ago by bioinf0
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Comment: C: DESEq2 for mulitple tissues under 2 conditions
... @ https://support.bioconductor.org/u/6944/ Yes, you are right WA1 is the replicate 1 of WA. A,B,C,D,E are five different tissues, while 1, 2 and 3 indicate biological replicates. Would you please elaborate more on how I can rearrange coldata to make it better accessible for DESeqDataSetFromMatrix ...
written 7 months ago by bioinf0 • updated 7 months ago by Michael Love18k
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DESeq2 for mulitple tissues under 2 conditions and contrast options
... Hi, I have paired rnaseq data from multiple samples, counted with featureCounts, now planning to use DESeq2 and trying to design it. I have gone through https://support.bioconductor.org/p/67600/.  However, I would like to confirm if my design is correct or not? Here is the sample coldata: ti ...
rnaseq deseq2 featurecounts deseqdatasetfrommatrix written 7 months ago by bioinf0 • updated 6 months ago by Michael Love18k
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Comment: C: CoverageView error (bug?)
... Hi, Did you find any solution? ...
written 12 months ago by bioinf0

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