User: aec

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aec40
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3 months, 3 weeks ago
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3 years, 6 months ago
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a**********@cnag.crg.eu

Posts by aec

<prev • 69 results • page 1 of 7 • next >
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Comment: C: edgeR /DESeq2 normalization for differential expression in RNA-seq blood samples
... The RNA-seq samples have already been sequenced (without globin depletion). ...
written 5 months ago by aec40
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edgeR /DESeq2 normalization for differential expression in RNA-seq blood samples
... Dear all, Both DESeq2 and edgeR normalization methods take into account different library sizes and RNA composition between samples, but are they able to account for a high difference of hemoglobin content in human blood samples? In my experiment, a single globin gene consumes between 2% - 50% of t ...
rnaseq normalization edger deseq2 hemoglobin written 5 months ago by aec40 • updated 5 months ago by Ryan C. Thompson7.3k
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Comment: C: time series, block by patient, between and within comparisons limma-voom
... Thanks Aaron, it worked perfectly. Now if I am interested in applying LRT method to detect differential genes between the two time-courses over time, how to set up the model with limma? 5 time-points is enough for using splines? ...
written 9 months ago by aec40
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Comment: C: time series, block by patient, between and within comparisons limma-voom
... Yes, irrespective of the group. ...
written 10 months ago by aec40
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Comment: C: time series, block by patient, between and within comparisons limma-voom
... I have 5 time points per patient, in total 15 patients. These 15 patients can be further divided in two groups for question b) ...
written 10 months ago by aec40
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Comment: C: time series, block by patient, between and within comparisons limma-voom
... sure, I will edit my post. ...
written 10 months ago by aec40
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time series, block by patient, between and within comparisons limma-voom
... Dear all, I have a time course RNA-seq analysis with the following design: 5 time points, 15 patients, 2 types of patients. the questions I would like to answer: a) expression differences across time points irrespective of patient type (t1 vs t2, t1 vs t3, ...) b) expression differences between ...
rna-seq patient limma-voom time series written 10 months ago by aec40 • updated 10 months ago by Aaron Lun24k
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Comment: C: differential expression analysis with big dataset and >500 surrogate variables
... thanks Michael.  ...
written 14 months ago by aec40
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Comment: C: differential expression analysis with big dataset and >500 surrogate variables
... n.sv <- num.sv(dat,mod) n.sv [1] 1   ...
written 14 months ago by aec40
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Comment: C: differential expression analysis with big dataset and >500 surrogate variables
... dds <- estimateSizeFactors(dds) dat <- counts(dds, normalized=TRUE) idx <- rowMeans(dat) > 1 dat <- dat[idx,] mod <- model.matrix(~case, colData(dds)) mod0 <- model.matrix(~1, colData(dds)) n.sv <- num.sv(dat,mod,method="leek") n.sv [1] 589   ...
written 14 months ago by aec40

Latest awards to aec

Popular Question 9 months ago, created a question with more than 1,000 views. For order of covariates for GLM with edgeR
Popular Question 9 months ago, created a question with more than 1,000 views. For How to deal with up to 75% of DE genes in RNA-seq (TMM, edgeR) ?
Popular Question 9 months ago, created a question with more than 1,000 views. For normalization affects drastically limma-voom + sva results
Popular Question 10 months ago, created a question with more than 1,000 views. For order of covariates for GLM with edgeR
Popular Question 2.1 years ago, created a question with more than 1,000 views. For limma - complex design with paired samples, sex and batch effect

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