User: Biologist

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Biologist70
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Posts by Biologist

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Comment: C: Use of batch corrected (removeBatchEffect) read counts for further downstream an
... Hi Aaron, Do you think this approach is right for making a clustering heatmap? library(edgeR) dge <- DGEList(counts=count) dge <- calcNormFactors(dge, method = “TMM”) logCPM <- cpm(dge,log=TRUE,prior.count=5) logCPM_bc <- removeBatchEffect(logCPM,batch=batch) ...
written 9 weeks ago by Biologist70
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Comment: C: edgeR removing batch effect before using expression data for clustering
... Sorry, I got you now. Before your first comment itself I saw the Gordon's comment in that post and thought of asking you whether it is right. Anyways now I got the point, I will use `voom` But If you dont mind could you please help me with the all the syntax I have to use for that. I never did this ...
written 9 weeks ago by Biologist70
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Comment: C: edgeR removing batch effect before using expression data for clustering
... Yes, James. But in this [Remove batch effect in small RNASeq study (SVA or others?)][1] Gordon recommends to do in the above way and then use it for MDS, PCA or heatmaps. So, I did it in that way. Is this wrong? [1]: https://support.bioconductor.org/p/59195/ ...
written 9 weeks ago by Biologist70
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Comment: C: edgeR removing batch effect before using expression data for clustering
... Thanks for the reply. So, after calculating logCPM, then I have to use removeBatchEffect function on that and then scale that for clustering analysis. Is it fine? logCPM <- cpm(y, prior.count=2, log=TRUE) logCPM <- removeBatchEffect(logCPM) logCPM <- t(scale(t(logCPM))) I ...
written 9 weeks ago by Biologist70
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edgeR removing batch effect before using expression data for clustering
... I have gene expression data for 8 samples, 4 controls and 4 FOXCUT OE samples. The raw counts data were in a dataframe `counts`. `coldata` looks like below: Samples Group Experiment Sample1 Control EXP1 Sample2 Control EXP1 Sample3 Co ...
batcheffect clustering edger R removebatcheffect written 10 weeks ago by Biologist70 • updated 10 weeks ago by James W. MacDonald50k
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Comment: C: How to get t-statistic values using edgeR?
... Gordon may I know your answer for my previous comment. thanks ...
written 10 weeks ago by Biologist70
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Comment: C: How to get t-statistic values using edgeR?
... Thanks Gordon. I also gave a try with `camera` now. For `camera` Is the following a right way? pathways.hallmark <- gmtPathways("h.all.v6.2.symbols.gmt") cam <- camera(y, pathways.hallmark, design, contrast=contrast.matrix, inter.gene.cor=0.01) head(cam,5) ...
written 11 weeks ago by Biologist70
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How to get t-statistic values using edgeR?
... Recently, I have seen a post about `fgsea` for gene set enrichment analysis. In this [DESeq results to pathways in 60 Seconds with the fgsea package][1]. In this post they use `stat` values column from `Deseq2` results to rank the genes for gene set enrichment analysis. With `edgeR` I use the foll ...
edger R gsea fgsea t-statistic written 11 weeks ago by Biologist70 • updated 11 weeks ago by Gordon Smyth38k
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Comment: C: EdgeR for differential analysis between two cell lines without replication
... Thank you very much for the reply. ...
written 12 months ago by Biologist70
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Comment: C: EdgeR error for differential analysis between two cell lines
... Hi Gordon, Thank you. I followed the tutorial and did the analysis. I have raw counts data of 72 genes for two cell-lines in dataframe "df". Three columns. First columns has genes and other columns are cell-lines. df <- data.frame(df[,-1], row.names=df[,1]) library(edgeR) y <- DGEList(cou ...
written 12 months ago by Biologist70

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Popular Question 7 months ago, created a question with more than 1,000 views. For Questions about analysis of Human Gene 2.0 ST Array
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Epic Question 7 months ago, created a question with more than 10,000 views. For Heatmap with error message: `x' must be a numeric matrix
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