11 votes
Accepted

PCA vs tSNE in single cell RNA-seq

tSNE often offers better visual representation (separation) on such complicated data than PCA. As Micheal pointed out, computing a tSNE embedding over 20.000 gene dimensions is computationally ...
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  • 504
10 votes

determining doublets in single-cell RNA-seq

Expected rates of doublets / duplets / multiplets Fluidigm C1 doublet rate: around 1-5% depending on chip type used. More information: Fluidigm white paper: Redesign of C1 Medium-Cell 96 IFCs ...
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  • 2,584
8 votes
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What is the actual cause of excessive zeroes in single cell RNA-seq data? Is it PCR?

It may be necessary to distinguish between methods that use unique molecular identifiers (UMIs), such as 10X's Chromium, Drop-seq, etc, and non-UMI methods, such as SMRT-seq. At least for UMI-based ...
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  • 561
7 votes

What is the actual cause of excessive zeroes in single cell RNA-seq data? Is it PCR?

The Biostars thread turned out helpful. The most interesting possible cause, not mentioned in the Ian Subery's answer, is that due to bursty nature of transcription, the true distribution of ...
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7 votes

What are doublets in single cell RNA-seq data?

"Doublet" is commonly used to describe a droplet in droplet-based sequencing that has captured atleast 2 cells. 10x states their doublet rate to be 0.8% per 1000 cells: There is a tradeoff between ...
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  • 71
7 votes
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What are doublets in single cell RNA-seq data?

Is doublet a set of cells sequenced as a single cell? Yes. Depending on the method of single cell sequencing it may be more or less likely for groups of cells to be captured and barcoded with the ...
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  • 11.8k
7 votes
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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 ...
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  • 873
7 votes
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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 ...
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  • 2,099
6 votes

How to filter ribosomal RNA from scRNA-seq data

In the paper mentioned, we used the ScaleData function in Seurat to regress out the number of reads, Rn45s abundance, and percent ribosomal gene transcripts. ...
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6 votes
Accepted

validating identified sub-populations of cells in scRNA-seq

A SC3, single-cell consensus clustering, approach could be helpful here. It aims at achieving "high accuracy and robustness by combining multiple clustering solutions through a consensus approach" ...
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  • 481
6 votes
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Are mitochondrial genes to exclude in scRNA-seq such as ribosomal genes?

According to Ilicic et al. (2016), on upregulation of mtRNA in broken cells: There is an extensive literature on the relationship between mtDNA, mitochondrially localized proteins, and cell death [...
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  • 1,733
6 votes
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Specific cell type identification in Single Cell Sequencing

I do not know of such software. However, I believe this effort is a bit misdirected. The purpose of single-cell sequencing is to get a better understanding of cells; their heterogeneity and ...
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  • 2,584
6 votes

VlnPlot problem

I assume you are referring to VlnPlot() of Seurat. The reason that you are getting such a plot is because your distribution is highly skewed, most of your points ...
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  • 3,477
5 votes

Improve scRNA-seq dataset for further analysis

I don't think you can conclude that the dataset is terrible based on that PCA. Depending on the specific protocol, each scRNA-seq dataset is going to be very different. Unlike bulk RNA-seq where all ...
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  • 2,099
5 votes

What is the actual cause of excessive zeroes in single cell RNA-seq data? Is it PCR?

I know of no references for this, but in general, I would say that your reasoning is sound. I would just add that in contrast to what I suspect you have simulated, not all transcripts are equally ...
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  • 3,221
5 votes
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ComBat for batch effects removal on scRNA-seq data

Look at this recent paper that uses ComBat on scRNA-seq data for batch effect removal and states that it "successfully does so". I also suggest that you check out this publication on Distribution ...
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  • 166
5 votes
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Why is ribosomal RNA difficult to remove even with Poly(A) selection?

We've found ribosomal RNA to be less of a problem with sequencing that depends on polyA, which suggests the issue might be in the library preparation, rather than the selection. Many polyA RNA ...
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  • 11.8k
5 votes
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What's a template switching site?

From the page you cited: During first-strand synthesis, upon reaching the 5’ end of the RNA template, the terminal transferase activity of the MMLV reverse transcriptase adds a few additional ...
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  • 1,022
5 votes
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Raw vs Filtered in the output of cellranger count

I'm unsure whether this is the answer you are looking for, but when looking into 10X cellranger documentation for the Matrices Output: Unfiltered gene-barcode matrices: Contains every barcode ...
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5 votes

Script to allow gene set enrichment analysis of 10x genomics data in R

Seruat will give you a list of genes which it thinks are upregulated in a particular cluster. Look at the functions that talk about marker genes - these functions basically do a DE analysis of the ...
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  • 3,221
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: ...
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  • 674
5 votes
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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: ...
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  • 497
5 votes
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How to best detect the "peaks" in RNA-seq data that are not assigned to any gene?

Basically what you're discovering is that there are unannotated expressed features, so your task isn't really finding peaks, but rather finding novel expressed transcripts. For that, you can use ...
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  • 19.2k
5 votes

public multi-modal single-cell data

These tutorials on Seurat multimodal data and the wrapper Seurat data are easy ways to start. The wrapper has some cite-seq data preinstalled making it easy to work with benchmarked data sets If you ...
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5 votes

How do I pull singe cell RNA sequencing data from GEO database?

The simplest would be using a count matrix (at the end of the link you have shared, section "Supplementary file"). For example ...
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  • 3,477
5 votes
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How to reduce the occupied RAM when you are dealing with a very sparse matrix in a single-cell Experiment in R?

Ah, looks like I can't even procrastinate on StackExchange anymore without seeing work-related stuff. Oh well. Anyway, the other answers and comments are way off. scran has supported sparse matrices ...
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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 @...
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  • 11.8k
4 votes
Accepted

10x Genomics Chromium single-cell RNA-seq data analysis options?

Data preparation Cell Ranger uses the Illumina sequencing output (.bcl) files Make fastq files: cellranger mkfastq ==> ...
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  • 2,584
4 votes
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Drawbacks of upper quartile normalization for scRNA-seq data

My primary concern with using the top ~1% or so in upper quantile normalization is that it's going to be prone to the same robustness issues that RPKM/FPKMs run in to. That is, if for whatever ...
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  • 19.2k
4 votes

determining doublets in single-cell RNA-seq

We cannot assume that doublets will produce more UMIs I would caution the assumption that all doublets will have twice the UMI levels of isolated single-cells. Many "doublets" could contain ...
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  • 873

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