Questions tagged [edger]

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What is the difference between AnnotationDbi/org.Mm.eg.db and biomaRt/Mus.musculus for converting to gene symbols?

I am interested in the differences between AnnotationDbi/org.Mm.eg.db and biomaRt/Mus.musculus. They yield the same results as seen in the code below. ...
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2 votes
1 answer
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What is the difference between Normalized Expression in EdgeR vs DESeq2?

I am trying to access the normalized expression in both edgeR and DESeq2, yet the results are different. Does anyone know why? How to get normalized expression using edgeR: ...
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62 views

Differential miRNA expression using RPM

I have microRNA (miRNA) expression data in RPM. I would like to do differential gene expression between two groups. How can I do this? I have considered edgeR and DESeq2 in R, but it looks like they ...
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1 answer
207 views

RNASeq analysis using featureCount and EdgeR

I am using a pipeline (bam -> featurecount-> EdgeR) to do some RNASeq analysis of several groups and sub-groups. For example, I have the following dataset with two types (T1 and T2) and T1 has ...
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  • 195
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2 answers
111 views

Determining what RNAseq data is filtered on volcano plot

I am using RNA seq data to analyze genes via a volcano plot comparing differential gene expression of bacteria with and without antibiotic in R. After having created my plot, I am unsure why some of ...
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1 vote
2 answers
42 views

Bulk RNA-Seq Read Length Normalization across different samples

I have 20 samples out of which 14 are 100 bp in length and 6 are 150 bp. Is there a way to normalize the read length for cross-sample differential expression comparison? What would be the best way to ...
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1 vote
1 answer
84 views

Why use "robust" FPKMs?

Both DESeq2 and edgeR have an FPKM/RPKM function that by default uses normalized library sizes ("robust" option in DESeq2). FPKMs have their own issues, but I thought the main benefit was to ...
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1 answer
62 views

the variation between treatments is less than the variation between replicates in RNA-seq data

I have a set of RNA-seq samples from targeting different proteins in a complex with siRNAs. However, the ...
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3 votes
1 answer
1k views

Removing Batch Effect in Heatmaps after Differential Gene Expression Analysis

I'm working on a dataset in which the first replicate of each group is one batch and the second replicate is in a second batch. After checking the PCA plot and ...
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1 vote
0 answers
153 views

Differential Gene Expression with Replicates for some of the samples

[this question has also been posted on Biostars; some additional clarification from there has been copied into this question] I've been asked to analyse a set of samples in which their control sample ...
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38 views

a proper Design Matrix for several drug treatments with both control negative and control positive

I have a dataset of RNA-seq samples for testing different drugs on the presence of another drug. One of my samples is the normal cells with no drugs (control negative) and another is the cells with ...
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1 vote
2 answers
386 views

How to create a list of differentially expressed (DE) genes after normalization with RUVSeq?

I am using edgeR to perform differential expression (DE) analysis on a set of RNA-seq data samples (2 controls; 8 treatments). To correct for batch effects, I am using RUVSeq. I am able to get a list ...
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2 votes
1 answer
176 views

Comparing multiple treatments to multiple other treatments in edgeR for simple effects in a complex experimental design

I am working with a RNA-seq data set in maize that has a relatively complex design. There are two levels of treatment A (nitrogen fertilizer level in the field, high or low), two levels of treatment B ...
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1 answer
390 views

How to incorportate RIN values as covariate in the design matrix?

I have been following the last DESeq2 pipeline to perform an RNAseq analysis with a dataset with low rin samples in the experimental (or treated) and high rin on the control ones. I read a paper in ...
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1 vote
2 answers
36 views

Identify differentially covered genes only between two samples

I have a question about finding differentially covered regions (coverage represents methylation level which goes from 0 to several thousands). I'm using enrichment based method which can be summarized ...
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2 votes
2 answers
216 views

What do these files / annotations mean?

I have no experience in Bioinformatics and I need to understand what the annotations given here mean (I am including the first few lines, please see the link for more): ...
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0 votes
1 answer
124 views

RNA-seq: How to get new expression count after normalization

I've RNA seq, Human, Paired-end data, Sample size is <40. These are aligned using STAR, RSEM processed. With RSEM I've TPM and expected counts, that is two files columns as individual IDs and row ...
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1 answer
200 views

Correlate DEGs from DESeq2, EdgeR and Limma results

I have a lists of DEGs identified by DESeq2, EdgeR and Limma. I would like to correlate the the gene rankings in the lists to decide on a package to use in downstream analysis. I am havig a few ...
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1 answer
93 views

Single sample in group: normal pipeline or Kal's Z test

As stated, which one is better for differential expression analysis? When I say normal pipeline I mean limma-voom, edgeR and DESeq2 pipeline for standard analysis. Kal's z test is mentioned in this ...
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1 vote
0 answers
383 views

What is the formula for Mg values in TMM normalization for RNA Seq data?

I am reading through the paper "A scaling normalization method for differential expression analysis of RNA-seq data" by Mark D Robinson, Alicia Oshlack, available here. In this paper they introduce a ...
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1 vote
0 answers
109 views

Gene ratio as imput in limma

I have a data frame with gene-expression ratio. Is it possible to input this into limma/voom to find signinficannt gene-ratios between groups of samples? my data: ...
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2 votes
1 answer
1k views

Calculating Z-score from logCPM values using edgeR

I have the raw counts for RNA-Seq data. I converted counts data to logCPM using edgeR package. Lets say I have a dataframe A with 15000 genes as rows and 100 ...
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0 votes
1 answer
73 views

Experimental Design for Differential expreression analysis

I have a Normal esophageal Fibroblasts (NOFs) cultured in DMEM media; The same NOF also have been cultured with a tumor sample from a patient named 005 on DMEM media; I have also Cancer Associated ...
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1 vote
1 answer
366 views

Error in quantile.default(x, p = p) in EgdeR calcNormFactors

I am trying to run TMM normalization using rpy2 and when I run calcNormFactors() function: <...
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8 votes
1 answer
1k views

How is prior.count used by edgeR's cpm

edgeR's cpm function has an argument called prior.count. Based on my understanding of the documentation, it is supposed to be adding a fixed number per sample which ...
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  • 183
0 votes
1 answer
1k views

Batch Effects in RNA Seq Sample

I am using the R (using EdgeR) for the RNA Seq analysis, I had few batch effect samples like Control vs treatment. Could anyone tell me the best way to remove the batch effects. I have looked into ...
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1 vote
1 answer
2k views

How to calculate logCPM across all samples?

Using edgeR for differential analysis between Tumor and Normal gave me differential expressed genes with logFC, logCPM, PValue and FDR. From the details of glmTreat function I see that logCPM is ...
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1 vote
2 answers
738 views

What could be the reason for the samples not clustering?

I'm performing RNA-seq analysis. I have used Hisat2 for aligning reads to the genome and stringtie for quantification and extracted read count information directly from the files generated by ...
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2 votes
0 answers
1k views

Which R package to use for differential analysis with TPM values?

I'm using hisat2, stringtie tools for the RNA-Seq analysis. After stringtie using ballgown I get FPKM and TPM values for every gene. I have seen that edgeR, Deseq2 can be used for Counts data. I ...
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10 votes
2 answers
1k views

*very* unbalanced group sizes for DE

I downloaded some publicly available RNA-seq data and want to compare those samples carrying a mutation (~4) against the rest (~800!). I ran both EdgeR and DESeq2, and the first results in an ...
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  • 395
8 votes
1 answer
379 views

When performing differential expression analysis, should genes with low read counts be removed before or after normalization?

I have RNA seq data which I've quantified using Kallisto. I'd like to use tximport to transform the read count data into input for EdgeR, following the R code supplied in the tximport documentation: ...
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9 votes
1 answer
464 views

confidence ellipses for MDS plot in edgeR?

Is it possible to draw e.g. 95% confidence ellipses around samples from the same group on the results from the plotMDS function under edgeR? If so, how?
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