7
votes
Accepted
Using Seurat to compare mutant vs.wt
Single-cell analysis to compare samples is a long a difficult process. There is very good documentation for 10x Genomics cellranger, the DropSeq Pipeline and the Seurat R package. These tools all have ...
- 873
6
votes
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Seurat with normalized count matrix?
This was addressed by the Seurat developers here:
if you have TPM counts, I suggest you don't use
Seurat::NormalizeData(), since TPM counts are already normalized for
sequencing depth and ...
- 2,169
6
votes
Accepted
6
votes
Accepted
Resolution parameter in Seurat's FindClusters function for larger cell numbers
Assuming you have an informative selection of variable genes from which you have constructed a number of useful PCs, I'd run a number of iterations with ...
- 2,624
6
votes
Accepted
Cells with zero expression of a given gene
This has been debated for a few years now as the "dropout" problem, which is actually a mixture of different issues.
On one hand, you are sequencing a relatively low input at a depth that ...
- 131
5
votes
Accepted
Which are the use cases for the methods for DE in Seurat
You can take a look at the recently published article: Bias, robustness and scalability in single-cell differential expression analysis.
We evaluated 36 approaches using experimental and synthetic ...
- 1,022
5
votes
Accepted
Mapping a list of cells in seurat featureplot
To color the TSNEPlot, you can generate a new column in metadata with the expression levels (High, low, etc). Then use pt.shape to set a shape for each identity.
To show binary expression based on ...
- 574
5
votes
How to set the position of groups in a Seurat object on a FeatureHeatmap plot
I don't think this is possible in Seurat v2, but in v3 you can change the factor levels of the grouping variable to change the plot order:
...
- 674
5
votes
Accepted
How can I obtain the percentage gene expression per identity class in Seurat as further processible numbers (e.g. matrix)?
This can be solved like this:
...
- 537
5
votes
Merging two dataframes in R
For merging dataframes, I find it easiest to use the tidyverse / dplyr functions inner/full/left/right_join. See the "Data Transformation Cheatsheet" on this page. For the merge that @...
- 13.8k
5
votes
Accepted
TCR-seq or scRNA-seq
The 3' gene expression protocol will capture TCR and BCR mRNAs but this may not be very helpful to you. As you already mentioned only the 3' end will be sequenced, which are the constant regions. With ...
- 886
4
votes
Is it possible to identify cells that are expressing two or more genes in Seurat?
The counts stored in the Seurat object are: raw counts ([email protected]), the log + normalized counts (seuratobject@data), and the scaled counts ([email protected]). ...
- 2,624
4
votes
Accepted
Violinplot of gene expression
You want to (1) see the mean for each gene, and also to (2) calculate a ratio of expression levels of two genes, then compare it between clusters.
(1) First, notice that ...
- 2,624
4
votes
Accepted
Percentage distribution of cells in all clusters based on their treatment condition?
Here is a solution using dplyr and ggplot2:
...
- 674
4
votes
Accepted
how to merge more than two sample in Seurat?
You have fed arguments to the MergeSeurat() function that it does not expect. In terms of objects, MergeSeurat() accepts only 2 ...
- 3,947
4
votes
Is it important to filter out poor quality cells before performing an integration analysis on single cell RNA sequencing data?
It is absolutely necessary to remove low quality cells: In the case of CCA (and this applies to other "integration" or "data alignment" methods as well), one would ...
- 3,947
4
votes
Accepted
The biological meaning of the random variables and the responses in Seurat analysis
In the linked article the authors formalize microarray analysis as the study of the joint distributions of $\overrightarrow{X}_i$ and $Y_i$, where $\overrightarrow{X}_i$ is a vector of random ...
- 3,301
3
votes
Seurat Merged objects tSNE - How to paint on original IDs?
Below a few lines of code that accompany BC Wang's answer.
After using MergeSeurat the sample name will be added to meta data under orig.ident. this can then be used to color the tSNE either using ...
- 574
3
votes
How I can test my hypothesises computationally
This is what packages like FateID and Monocle are for, namely taking single-cell RNAseq data and inferring differentiation trajectories from it. Don't try to reinvent the wheel on this, there are a ...
- 19.6k
3
votes
Accepted
How I can reproduce this heat map
In case it is still helpful as the post is rather old, the code below would generate a heatmap with annotations thanks to the ComplexHeatmap package.
But before ...
- 3,947
3
votes
Accepted
Output of Seurat FindAllMarkers parameters
pct.1– The percentage of cells where the gene is detected in the first group
p_val_adj– Adjusted p-value, based on bonferroni ...
- 1,149
3
votes
Manually define clusters in Seurat and determine marker genes
Seurat has functions for adding metadata and setting identities. Get unique cell names:
cell.labels <- seuratobject@ident
Replace column and its name with ...
- 2,624
3
votes
Accepted
Manually define clusters in Seurat and determine marker genes
I think you are looking to FindAllMarkers function from Seurat. As you said, you just have to define your ...
- 1,022
3
votes
Resolution parameter in Seurat's FindClusters function for larger cell numbers
That is a very general recommendation. Depending on your experiment, you can get a very different number of clusters with the same number of cells at the same resolution.
You can actually use a ...
- 2,169
3
votes
Accepted
FeaturePlot from Seurat: change its title
I tried with some data that I have and this is working for me:
...
- 1,022
3
votes
Accepted
about dotplot legend meaning
The expression values for each gene are scaled / standardized by subtracting the genes mean expression and dividing by its standard deviation. A value of -1 would imply it's one standard deviation ...
- 752
3
votes
Accepted
Using external list of PCs for clustering
There is a way to do this, and even better--there is documentation for how to do it! No surprise coming from the Satija Lab. In the vignette they perform multidimensional scaling, but the idea is the ...
- 1,149
3
votes
Changing a wide range of colours to a limited gradient
TSNEPlot()
TSNEPlot() will always treat your variables as discrete. My approach is to manually generate a gradient with unique colors for each factor level and ...
- 1,149
3
votes
Accepted
Changing a wide range of colours to a limited gradient
If you would like to color discrete intervals on a gradient as opposed to having a continuous gradient (like your second plot), use this approach.
It is similar to the approach in the answer I ...
- 1,149
3
votes
How can I obtain the percentage gene expression per identity class in Seurat as further processible numbers (e.g. matrix)?
You can get the table that is used to make the dot plot if you modify the DotPlot function to return it instead of the ggplot, and use the argument do.return=T.
To edit the function, the command is:
...
- 31
Only top scored, non community-wiki answers of a minimum length are eligible