16
votes
Understanding DESeq2 design, contrast and results
The simplest manner is to not use a wald test, but rather an LRT with a reduced model lacking the factor of interest:
...
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12
votes
Accepted
How can I extract normalized read count values from DESeq2 results?
The normalized counts themselves can be accessed with counts(dds, normalized=T).
Now as to what the baseMean actually means, that will depend upon whether an "...
- 19.6k
10
votes
Accepted
Understanding DESeq2 design, contrast and results
It seems that the "combining factors" trick described in part 3.3 of DESeq2 current "vignette" (as of may 2017) under the title "Interaction" is a way to access to the desired contrasts.
It seems ...
- 3,100
8
votes
Trouble using biomaRt to retrieve hgnc symbols from Ensembl transcript ids
You need to specify the number without the version. Instead of "ENSMUST00000178862.1" just "ENSMUST00000178862":
You can do this with one more line:
...
- 4,693
7
votes
differential gene expression complex design no replicates
Mike Love is right. If the response you are looking for is linear in terms of change per minute, the most productive approach is likely to be fitting a linear model. You might get something out of ...
- 3,301
7
votes
Accepted
differential gene expression complex design no replicates
Although it is not recommended to use no replicates, in the edgeR manual they give some advice on how to go on with no replicates design. See page 21 of user guide. You can e.g. estimate a BCV value. ...
- 3,571
7
votes
Accepted
What are the count units in DEseq2?
The counts are "reads" for single-end datasets and "fragments" for paired-end datasets. In other words, they're what featureCounts and htseq-count produce. The "normalized counts" that you'll be able ...
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7
votes
Accepted
What are the ways to process a list of differentially expressed genes?
You originally had asked a very broad question, so I'll try to demonstrate why that is such a hard question to answer. I've done two fairly large differential analysis studies (and a few smaller ones) ...
- 13.8k
7
votes
Accepted
PCA plot shows big difference but not many differentially expressed genes are found
You only have 4 samples total. I think it would be difficult to not have the PCA show big differences between the groups with so few points.
On the other hand, for differential expression, it is hard ...
- 2,169
6
votes
How can I extract normalized read count values from DESeq2 results?
It depends what you mean by “normalised”. As Devon said, the normalized = TRUE argument to the count function gives you ...
- 4,845
6
votes
Accepted
Running differential expression analyses on count matrices with many zeroes
I don't think that the issue is the low counts, but rather the number of features without any real variance (the black dots at the bottom).
So what the heck is the dispersion plot and why does one ...
- 19.6k
6
votes
Accepted
gene-level versus transcript-level analysis
There are a variety of reasons people use gene-level quantitations.
Transcript-level differences are difficult to biologically interpret. Let's be honest, few groups are likely to put in the work ...
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6
votes
Accepted
design formula question
You can't (easily) use a single design, since clone is nested within diabetic status, so you were correct using two separate designs. Your designs are correct.
If you really wanted to use a single ...
- 19.6k
5
votes
Running differential expression analyses on count matrices with many zeroes
Remove low-count features in advance. This is standard for most tools including DESeq2 and edgeR (see section 2.6).
This will keep you from testing a lot of features that cannot be differentially ...
5
votes
Can I model technical replicates in DESeq2?
If they're truly technical replicates, then there's no way to model them using DESeq2*, as you've alluded to with the collapseReplicates function. DESeq2/ Mike Love'...
- 236
5
votes
Can I model technical replicates in DESeq2?
Practically speaking, there's no way to include the technical replicates in that design (in DESeq2 at least). Your concern regarding inflating the power is exactly correct and the only way to combat ...
- 19.6k
5
votes
Accepted
DeSeqDataSet experimental design: column with integer values
Any IDs (e.g. replicate number) don't need to be included in the design formula if it's not a repeated factor in multiple samples.
In this case, you have said that mouse number is related to the ...
- 13.8k
5
votes
Accepted
Salmon tximport
You are right, samples.txt is not generated by Salmon (or any other transcript abundance quantifiers). From documentation, you can find a link to an example of how <...
- 2,676
5
votes
Accepted
LRT or LRT-like test on cyclical (Sleep) data
I think the problem is that you have time as a linear value rather than a factor. While this naively makes sense (after all, you have to go through 3 hours awake ...
- 19.6k
5
votes
Accepted
Install DESeq2 through anaconda
Ultimately my colleague helped me to solve the issue by following the steps:
Created environment: conda create --name myenv
Activated it: ...
- 2,538
5
votes
Why use "robust" FPKMs?
FPKM are inherently experiment specific and can not be used to compare across samples. Let's consider the following two sequencing runs. Let $E1$ and $E2$ be the true, underlying expression in two ...
5
votes
Accepted
Calculating most abundant transcript from RNA-Seq data
Transcript abundance quantification is a tricky topic since a read often could belong to several transcripts, so any "count" is a best guess as to which transcript it actually originates ...
4
votes
Accepted
Highly variable genes analysis by DESeq2
The first method (resSig$log2FoldChange) is for getting the most differentially expressed genes. These are the genes with the biggest differences between specific ...
- 2,169
4
votes
Accepted
plotMA function issue: can not circle genes
It's likely that the fold-change of the topGene is greater than 5. Consequently, the circle is being drawn and the text produced, but they're outside the bounds of ...
- 19.6k
4
votes
Accepted
Error in checkFullRank(modelMatrix) deseq2
See the second example from the vignette, which is exactly your situation. The software cannot differentiate between the batch effects vs. condition effects because the groups are exactly the same.
- 56
4
votes
Accepted
Is it possible to create a DESeqDataSet with a user-provided design matrix?
Provide rank sufficient design to DESeqDataSetFromMatrix and then use your custom model matrix in DESeq. In essence:
...
- 19.6k
4
votes
gene-level versus transcript-level analysis
To add to the list that Devon Ryan outlined (or perhaps to elaborate on point 2?):
Although Salmon/Kallisto/RSEM are the more accurate in their transcript quantification than the methods they ...
- 3,301
4
votes
Installing DESeq2 in Ubuntu
First I installed this libraries:
sudo apt-get install libcurl4-openssl-dev libxml2-dev
I then installed RCurl:
...
- 645
4
votes
Identify differentially covered genes only between two samples
Not really an answer but an extended comment... and most likely something you don't like to hear
I guess by technical replicates, it means taking the same biological sample and making 2 methylation ...
- 1,678
4
votes
Accepted
How to incorportate RIN values as covariate in the design matrix?
In the DESeq2 manual there is a section titled "How can I include a continuous covariate in the design formula?" that deals with your question.
Basically the process is no different from using a ...
- 886
Only top scored, non community-wiki answers of a minimum length are eligible