User: lirongrossmann

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Posts by lirongrossmann

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Different PCA plots using rlog and vsd on the same data set
... Hi All, I have been using Deseq2 to analyze a dataset I have and ran into a problem I am not sure how to solve. I have been using the following code to run deseq2 on my dataset:   dds <-DESeqDataSetFromMatrix(countData = ep,colData = cp,design = ~Risk) dds <- estimateSizeFactors(dds) rld ...
deseq2 pca rlog variancestabilizingtransformation plotpca written 1 day ago by lirongrossmann0 • updated 1 day ago by Michael Love13k
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Comment: C: Selecting genes that best separate between two groups
... Thanks! To be more specific, I am using an expression file which was the output of Kallisto, and the values in the expression matrix are in TPM, not the raw counts. I transformed the expression file to log(TPM+1) and ran limma on it.  Could that explain (at least in part) the source of my problem? ...
written 7 days ago by lirongrossmann0 • updated 7 days ago by Gordon Smyth31k
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Selecting genes that best separate between two groups
... Hi everyone! I'm working on a gene expression file from an RNA seq experiment and try to compare between two groups of samples. I'm pretty new to this world of gene expressions and need some help. I have a strong reason to believe that there should be a biological difference between the two groups ...
clustering genefilter limma tpm ttest written 7 days ago by lirongrossmann0
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Comment: A: Choosing genes for clustering
... Thank you very much! Liron ...
written 10 days ago by lirongrossmann0
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Combined strand specific and unstranded samples
... Hey everybody, I am working with an RNA-seq dataset that combines samples from strand-specific and unstranded technology.  Ideally I would like to use all the samples to be able to detect DE genes between biological groups.  I am trying to deal with the problem at the gene expression level and tre ...
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Choosing genes for clustering
... Dear all,  I am running a differential gene expression between 2 groups and got 124 differentially expressed genes using the limma package.  When I run hierarchal clustering on the dataset using 30 top genes I get pretty clear separation between the 2 groups. When I increase the number of genes to ...
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Comment: C: Limma and batch effect
... Hi! Thanks again for you help. I took your advice of working with the strand-specific dataset, and have two more questions please: 1. In the strand-specific dataset the number of non-responsive  to treatment samples is 9 and the responsive sample is 197. I tried to cluster the dataset to see if t ...
written 12 days ago by lirongrossmann0
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Comment: C: Limma and batch effect
... Thanks! My thought to add the unstranded data was to increase the power of my test, so I will have more samples, but I guess I will lose more if I try to correct for the batch.... ...
written 13 days ago by lirongrossmann0
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Comment: C: Limma and batch effect
... Yep, I ran it again with the topTable(fit, coef=3). I initially took topTable(fit,adjust.method= "BH") which was a mistake. My updated comment is the one I ran the last taking into account the code you provided in your comment. ...
written 13 days ago by lirongrossmann0
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Comment: C: Limma and batch effect
... Thank you for your explanations!! I took into account Aaron's advice and have changed my code to the following: ( I assume Aaron meant topTable?) fit = lmFit(y, design=model.matrix(~batch+fac)) fit = eBayes(fit) topTable(fit,coef=3 ) In my hypothesis, I am testing two biologic groups (refractory ...
written 13 days ago by lirongrossmann0 • updated 13 days ago by Gordon Smyth31k

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