5 votes
Accepted

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 ...
Martin's user avatar
  • 166
4 votes

ComBat for batch effects removal on scRNA-seq data

There are competing claims regarding how well ComBat works on scRNA-seq datasets. A recent paper from John Marioni's introduces a mutual nearest neighbors method that seems to outperform ComBat in at ...
Devon Ryan's user avatar
  • 19.6k
4 votes

How should I address batch effects in my experiment?

Yes, though thankfully Your 2018 PreD samples will help you resolve this. Simply add the batch effect to the design (~Batch + Treatment) and DESeq2 (or edgeR or ...
Devon Ryan's user avatar
  • 19.6k
3 votes

TPM or rlog(CPM) for comparing expression?

For comparing the counts of different samples from DESeq2, Michael Love recommends using the variance-stabilized transform. It'd be great if you could provide some specific code examples in your ...
gringer's user avatar
  • 14.1k
3 votes
Accepted

Interpreting this PCA plot for RNA-seq

Yes, you can safely concatenate the technical replicates. Odds are good that these are even the same libraries just sequenced twice, so even labeling them as replicates is a bit of a stretch. As an ...
Devon Ryan's user avatar
  • 19.6k
3 votes
Accepted

Combat for multiplatform batch correction

Usually with microarrays you want to make a case/control comparison, so I am going to assume that. Data from different array platforms is generally difficult to compare: each platform is measuring ...
Jay Moore's user avatar
  • 1,012
3 votes

Batch Effects in RNA Seq Sample

The help page for removeBatchEffect() explicitly states that it should not be used in conjunction with differential expression testing, so don't do that. You ...
Devon Ryan's user avatar
  • 19.6k
3 votes

Order of batch effects removal, data imputation and library size normalization in scRNA-seq data

MAGIC assumes input data has been both library-size normalized, and either log or sqrt transformed prior to imputation (see also: MAGIC tutorial). Additionally, any graph-based methods (MAGIC, PHATE, ...
Scott Gigante's user avatar
2 votes
Accepted

How hard is it to clean and QC gene expression microarray data?

I am not sure how much you know about bioinformatics already, can you use R? For a bioinformatician looking at QC for microarrays should not be a big deal, at least for me it would take maybe a day (...
benn's user avatar
  • 3,571
2 votes

Is it possible to merge scRNAseq data from experiments with different design?

See this paper from the Marioni group, where they propose a method for correcting batch effects between single cell sequencing experiments when each experiment contains different sub-populations: ...
Ian Sudbery's user avatar
  • 3,311
2 votes
Accepted

Is it possible to merge scRNAseq data from experiments with different design?

It’s right there on the cellranger manual: #aggregate results of counts for separate samples cellranger aggr #analyse the combined results cellranger reanalyze ...
Tom Kelly's user avatar
  • 873
2 votes
Accepted

How to get the corrected matrix after SVA batch effect correction

If you want to plot the "corrected" expression, you will need to remove the variation introduced by these surrogate variables. Removing the expression affected can introduce some bias too and it is ...
llrs's user avatar
  • 4,703
2 votes

TPM or rlog(CPM) for comparing expression?

To add to what @gringer, when you do use TPM, the normalization done is for both library size and gene length. When you use rlog, the normalization is done via median normalization (https://www.ncbi....
StupidWolf's user avatar
  • 1,688
2 votes

Comparing differential expression across samples - is batch effect correction needed?

There is no need for batch correction because all your comparisons are within batch. As long as you are making comparisons for each line, and treatment and control for the same line are in the same ...
Gordon Smyth's user avatar
2 votes

Batch correction in differential expression analysis

If both batches contain replicates of both groups (LT and C) then the presented code is what you should do, exactly pointed out in the vignette for the LRT: http://bioconductor.org/packages/release/...
ATpoint's user avatar
  • 1,287
1 vote

Problems in conducting batch effect correction

The ComBat-seq method requires raw counts which can be modelled as a negative binomial. The other methods are typically used with normalized counts transformed to log2 scale. Obviously for any method ...
Boggs Diamond's user avatar
1 vote
Accepted

Can I Incorporate svaseq() into GSEA/GSVA analysis?

Use removeBatchEffects from limma. The input counts should be on log scale, so vst and ...
Corinthus Kackus's user avatar
1 vote

What is the correct order of flooring-normalization-batch correction for microarrays?

The most important thing to do first is batch correction, and it looks like that was done in this instance. The ordering in this case seems reasonable. Normalisation is usually applied to a full ...
gringer's user avatar
  • 14.1k
1 vote
Accepted

(scRNA-seq) I have a dataset with 4 conditions (experiments) should I be anchoring aka integrating data for each comparison when looking for DEGs?

Batch correction/data integration is a tricky subject for scRNA-seq, see a few recent papers for benchmarks: https://www.nature.com/articles/s41592-021-01336-8 and https://genomebiology.biomedcentral....
Chris_Rands's user avatar
  • 3,948
1 vote
Accepted

Assumptions of batch effect removal

You're basically subtracting a constant per-gene per-level. The relevant portion of the code is: ...
Devon Ryan's user avatar
  • 19.6k
1 vote
Accepted

Batch effect correction using a subset of samples - using DE genes

The batch effect is expected to be the same across all samples - therefore you want to estimate its effect across all of the samples. Just add batch as an additional parameter to the linear model (...
Greg's user avatar
  • 301
1 vote

Should one be especially conscious of removing low counts, when applying batch correction?

I don't think this has anything to do with batch correction. The averages of that gene are distinctly different between groups, so it's correct that the gene is statistically significant. But with ...
swbarnes2's user avatar
  • 1,925
1 vote
Accepted

how to solve “dim(X) must have a positive length” at running ComBat function in R

batch = Pheno_LMS$batchId should be batch = Pheno_LMS$BatchId, if you fix that then at least the code you showed works just fine....
Devon Ryan's user avatar
  • 19.6k
1 vote

Interpreting this PCA plot for RNA-seq

Prepping the RNA on different days, or making Illumina libraries on different days, or having different technicians handle different samples; that can lead to batch effects. Running samples on two ...
swbarnes2's user avatar
  • 1,925
1 vote

sva for RNA-Seq data without known phenotype

You can just remove the first component from the dataset by setting the first eigenvalue to 0 in the diagonal matrix and then multiplying the SVD matrices. I am not sure which R code you are using ...
Aedin's user avatar
  • 156
1 vote

Is it possible to merge scRNAseq data from experiments with different design?

Have you tried seurat3? Here is the reference: https://satijalab.org/seurat/v3.0/pancreas_integration_label_transfer.html
Zhi-Ping Feng's user avatar

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