<p>So for context, I have a set of TPM values for multiple genes for different samples, and I need to calculate the differential expression for RNA-seq values. I've been using this website as a guide: <a href="https://raw.githubusercontent.com/ucdavis-bioinformatics-training/2019_March_UCSF_mRNAseq_Workshop/master/differential_expression/DE_Analysis.Rmd" rel="nofollow noreferrer">https://raw.githubusercontent.com/ucdavis-bioinformatics-training/2019_March_UCSF_mRNAseq_Workshop/master/differential_expression/DE_Analysis.Rmd</a>. The overall aim of this calculation is so that I can use PANDA to map TM motifs/combine gene expression data to create networks representing interactions between transcription factors and genes, and GSEA to analyze genes ranked by fold change or differential expression p-value.</p>
<p>So what I need to do is match one male to one female of the same age group (which I already did prior; the number of males outnumbered the number of females so I filtered the number of males so that there would be an equal number, and of the same age distribution). But it seems that I need to derive two factors and create a new variable &quot;group&quot; that combines factor1 and factor2. In this case, it would be the gender I would use as the group factors, right?</p>

CC BY-SA 4.0
2023-06-07T21:39:38.180Z
**My advice is open a separate question on the topic of calculating DEG cut-offs on this site.** I personally cannot  answer the first question (I don't know the project, specifically what the DEG is measuring and how pairwise DEGs are avoided), but I can present the rationale of calculating DEG cut-offs (i.e. different approaches used and why). Again this is the second part of the question and the SE (Stackexchange) approach is one technical request per question. In this instance the answer  is bit complicated (if stats aren't you thing) and is not a one line response in comments.
M__
CC BY-SA 4.0
2023-06-07T21:41:35.340Z
Okay, but do you have a recommendation on the specific number I use as a cutoff?
Feynman
CC BY-SA 4.0
2023-06-08T01:40:27.790Z
Which is..? It wasn’t clear to me if you had a number in mind or you were telling me to just eyeball it.
Feynman
CC BY-SA 4.0
2023-06-08T01:59:01.497Z
And how do you derive this?
Feynman
CC BY-SA 4.0
2023-06-08T06:36:38.750Z
Okay, I did what you asked
Feynman
<differential-expression><tpm>
How do I calculate differential expression for RNA-seq values with the "limma" package and the "ebayes" function?
# How do I calculate differential expression for RNA-seq values with the "limma" package and the "ebayes" function?

(Asked by: username_0 on 2023-06-07)

So for context, I have a set of TPM values for multiple genes for different samples, and I need to calculate the differential expression for RNA-seq values. I've been using this website as a guide: <https://raw.githubusercontent.com/ucdavis-bioinformatics-training/2019_March_UCSF_mRNAseq_Workshop/master/differential_expression/DE_Analysis.Rmd>. The overall aim of this calculation is so that I can use PANDA to map TM motifs/combine gene expression data to create networks representing interactions between transcription factors and genes, and GSEA to analyze genes ranked by fold change or differential expression p-value.

So what I need to do is match one male to one female of the same age group (which I already did prior; the number of males outnumbered the number of females so I filtered the number of males so that there would be an equal number, and of the same age distribution). But it seems that I need to derive two factors and create a new variable "group" that combines factor1 and factor2. In this case, it would be the gender I would use as the group factors, right?

**Tags:** differential-expression, tpm
> **Comments:**
> **username_1**: **My advice is open a separate question on the topic of calculating DEG cut-offs on this site.** I personally cannot  answer the first question (I don't know the project, specifically what the DEG is measuring and how pairwise DEGs are avoided), but I can present the rationale of calculating DEG cut-offs (i.e. different approaches used and why). Again this is the second part of the question and the SE (Stackexchange) approach is one technical request per question. In this instance the answer  is bit complicated (if stats aren't you thing) and is not a one line response in comments.  
> **username_0**: Okay, but do you have a recommendation on the specific number I use as a cutoff?  
> **username_0**: Which is..? It wasn’t clear to me if you had a number in mind or you were telling me to just eyeball it.  
> **username_0**: And how do you derive this?  
> **username_0**: Okay, I did what you asked  

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## 0 answers

