User: Aaron Lun

gravatar for Aaron Lun
Aaron Lun20k
Reputation:
20,130
Status:
Trusted
Location:
Cambridge, United Kingdom
Scholar ID:
Google Scholar Page
Last seen:
6 hours ago
Joined:
3 years, 11 months ago
Email:
a***@wehi.edu.au

I am a research associate in the field of computational biology at the Cancer Research UK Cambridge Institute in the United Kingdom. I am the author and maintainer of the csaw, diffHic, InteractionSet, scrancydar, beachmat, DropletUtils, chipseqDB and simpleSingleCell packages; a co-author and co-maintainer of the scater, SingleCellExperiment and iSEE packages; a co-maintainer of the edgeR package; a co-author of the TENxBrainData package; and an occasional contributor to the limma package.

Posts by Aaron Lun

<prev • 2,232 results • page 2 of 224 • next >
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Answer: A: Limma weights, non-specific interactions
... The main problem here is that it's hard to convert a vague sense of "I don't like these proteins" into a concrete, quantitative weight. You say that you want to downweight the problematic interactors, but by how much? What does it mean to be twice as problematic? How many angels dance on the head of ...
written 14 days ago by Aaron Lun20k
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Comment: C: Batch Effect Correction
... Assuming that condition1 and condition2 are truly identical (i.e., both factors), all I can say is that ComBat performs some moderation on the batch effects, with the aim of stabilizing the batch effect estimates by sharing information across genes. If the moderation is strong, the observed batch ef ...
written 15 days ago by Aaron Lun20k
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Comment: C: time series RNA-seq allowing time offset between individuals
... See Section 9.6.2 of the limma user's guide for an example. ...
written 15 days ago by Aaron Lun20k
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Comment: C: Batch Effect Correction
... Well, for starters, you're using condition1 for ComBat and condition2 for removeBatchEffect. ...
written 16 days ago by Aaron Lun20k
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Answer: A: time series RNA-seq allowing time offset between individuals
... This seems fairly standard. Just use a design with individual and time effects; the usual suspects (edgeR, DEseq2, limma) are all able to deal with this. For example, in edgeR, one might define the design matrix as: design <- model.matrix(~individual + time) ... and then test the effect of the ...
written 16 days ago by Aaron Lun20k
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Answer: A: csaw normalization and library size
... This shouldn't happen if you used the same readParam object in both regionCounts and windowCounts. In fact, that's the primary purpose of having the readParam class in the first place. The only possibility I can think of is if one of the totals is integer and the other is double-precision. You can c ...
written 19 days ago by Aaron Lun20k
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Answer: A: Limma: technical and biological replicates in proteomics data
... Your set-up looks fine to me. To address your specific concerns: Yes, you should put ex and ms in the model. If you don't put in ex, systematic differences between experiments would affect the correlation estimated by duplicateCorrelation, i.e., the correlation wouldn't just capture the fact that ...
written 19 days ago by Aaron Lun20k
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Answer: A: Adjust number of clusters with scran/buildSNNGraph
... Increase the number of neighbours used (k) when running buildSNNGraph. This increases the connectivity of the SNN graph and should reduce the number of clusters (i.e., follow the opposite of the advice given in the comments section here). I am surprised that the default k=10 yields too many clusters ...
written 19 days ago by Aaron Lun20k
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Answer: C: Batch Effect Correction
... Include the batch factor when creating a design matrix to run in edgeR. Not doing so would be incorrect; there is clearly a batch effect in all of your PCA plots. I don't know why you think that the batch effect is "not much" in the PCA plot generated with the top 500 highly variable genes, the batc ...
written 19 days ago by Aaron Lun20k
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Answer: A: Combining groups in a LIMMA design
... I don't know what lmfmain or contrasts.fmain are. Aside from that, your design matrix looks fine. For your ALL contrast, you should divide by two as you're taking the average of the with/without autism groups: ALL = (adult.autism + ped.autism)/2 - (adult.control + ped.control )/2 Otherwise your l ...
written 20 days ago by Aaron Lun20k

Latest awards to Aaron Lun

Scholar 11 weeks ago, created an answer that has been accepted. For A: column nubering plotMDS
Appreciated 11 weeks ago, created a post with more than 5 votes. For A: Is Limma's removeBatchEffect() and log2() commutative?
Scholar 11 weeks ago, created an answer that has been accepted. For A: csaw::combineTests: Error: length(ids) == nrow(tab) is not TRUE
Scholar 11 weeks ago, created an answer that has been accepted. For A: edgeR normalisation factors different between experimental groups
Scholar 11 weeks ago, created an answer that has been accepted. For A: Building contrasts for combined treatment groups to compare to a control
Good Answer 11 weeks ago, created an answer that was upvoted at least 5 times. For A: Is Limma's removeBatchEffect() and log2() commutative?
Appreciated 11 weeks ago, created a post with more than 5 votes. For A: edgeR normalisation factors different between experimental groups
Scholar 11 weeks ago, created an answer that has been accepted. For A: adding a description column to glmTreat output
Teacher 11 weeks ago, created an answer with at least 3 up-votes. For A: Filtering for ATAC-seq
Scholar 11 weeks ago, created an answer that has been accepted. For A: Paired factorial design model in limma
Scholar 11 weeks ago, created an answer that has been accepted. For A: how to calculate the logFC value
Scholar 11 weeks ago, created an answer that has been accepted. For A: Problem with annotating ENSEMBLE IDs to GENE SYMBOL with AnnotationDBI mapIDs
Scholar 11 weeks ago, created an answer that has been accepted. For A: How to extract genes with greatest BCV?
Good Answer 11 weeks ago, created an answer that was upvoted at least 5 times. For A: Continuous variable interaction with Groups in design matrix
Teacher 11 weeks ago, created an answer with at least 3 up-votes. For A: edgeR normalisation factors different between experimental groups
Scholar 11 weeks ago, created an answer that has been accepted. For A: Representvie gene expression value in one condition with several replicates
Teacher 11 weeks ago, created an answer with at least 3 up-votes. For A: Paired factorial design model in limma
Teacher 11 weeks ago, created an answer with at least 3 up-votes. For A: Representvie gene expression value in one condition with several replicates
Teacher 11 weeks ago, created an answer with at least 3 up-votes. For A: Building contrasts for combined treatment groups to compare to a control
Scholar 3 months ago, created an answer that has been accepted. For A: Building contrasts for combined treatment groups to compare to a control
Scholar 3 months ago, created an answer that has been accepted. For A: how to calculate the logFC value
Scholar 3 months ago, created an answer that has been accepted. For A: Representvie gene expression value in one condition with several replicates
Teacher 3 months ago, created an answer with at least 3 up-votes. For A: Filtering for ATAC-seq
Scholar 3 months ago, created an answer that has been accepted. For A: adding a description column to glmTreat output

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