User: Aaron Lun

gravatar for Aaron Lun
Aaron Lun17k
Reputation:
16,870
Status:
Trusted
Location:
Cambridge, United Kingdom
Scholar ID:
Google Scholar Page
Last seen:
8 hours ago
Joined:
3 years, 2 months ago
Email:
a***@wehi.edu.au

I am a research associate working 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 and beachmat packages, a contributor and co-maintainer for the edgeR and SingleCellExperiment packages, and an occasional contributor to the limma and scater packages.

Posts by Aaron Lun

<prev • 1,863 results • page 1 of 187 • next >
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Comment: C: edgeR: Should there be a normalization step for CRISPR screens? How to deal with
... "Library size normalization" refers to the use of the library size only for scaling normalization of each sample. This is equivalent to running edgeR without using calcNormFactors, i.e., normalization factors set to 1. Remember that edgeR uses the effective library sizes (product of the library size ...
written 14 hours ago by Aaron Lun17k
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Answer: A: edgeR: Should there be a normalization step for CRISPR screens? How to deal with
... In lieu of someone more qualified, I'll have a stab at answering your questions. For your first question: TMM normalization in calcNormFactors relies on the assumption that most genes (or guides, or whatever features you're giving it) are not DE between samples. This may not be true for small scree ...
written 16 hours ago by Aaron Lun17k
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Answer: A: Boxplot and Identification of DEG
... For your first question: an FDR of 50% means that we can expect (on average) up to half of your detected DE genes to be false positives. In most situations, I would find this unacceptable. How can anybody be confident in a set of DE genes where half of them are expected to be false positives? Such a ...
written 17 hours ago by Aaron Lun17k
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Answer: A: Time-course group difference analysis with repeated individuals using limma-voom
... Regarding the choice between models: reading your comment indicates that the models share 20490 DE genes, with only 361 and 919 DE genes unique to each model. This suggests that, relatively speaking, there's not much difference between the models to worry about. (It is quite a large number of DE gen ...
written 17 hours ago by Aaron Lun17k
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Comment: C: Design matrix for longitudinal discordant twin analysis with limma
... Having thought about it a bit more (and after getting some dinner!), I realized that you can make it work by just not running duplicateCorrelation at all: group <- paste0(disease, time) # time/condition interactions design <- model.matrix(~0 + group) # ... and go straight to lmFit(). You c ...
written 1 day ago by Aaron Lun17k
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Comment: C: edgeR: Should there be a normalization step for CRISPR screens? How to deal with
... Which case studies are you referring to? These? ...
written 1 day ago by Aaron Lun17k
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Comment: C: Adaptation of DESeq/edgeR model for CRISPR drop-out screen
... The equivalent in edgeR would be to supply GLM offsets via the scaleOffset function, if anyone's interested. ...
written 1 day ago by Aaron Lun17k
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Comment: C: Error while processing BAM file with Picard FixMateInformation
... Having two reads with the same name in the FASTQ file would be very irregular. Illumina sequencers name their reads by the coordinates of the cluster on the flow cell, so having the same read name would imply that you have two different reads from the same location on the flow cell! This is clearly ...
written 1 day ago by Aaron Lun17k
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Answer: A: Design matrix for longitudinal discordant twin analysis with limma
... This is a pretty limited data set and I don't think you will be able to do most of the things you want to do. There's too many factors compared to samples. For your ideal design that accounts for time-specific condition effects, duplicateCorrelation will just spit out NAs. This is not surprising bec ...
written 1 day ago by Aaron Lun17k
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Comment: C: limma. After running a differential expression analysis... Can you get the indiv
... It's hard to tell what you're doing without code, read the posting guide. Looking at ?"EList-class" would probably yield the answers you're looking for. ...
written 3 days ago by Aaron Lun17k

Latest awards to Aaron Lun

Scholar 4 months ago, created an answer that has been accepted. For A: EdgeR -ANOVA-like test vs testing individual contrasts
Scholar 4 months ago, created an answer that has been accepted. For A: Limma Model Design
Teacher 5 months ago, created an answer with at least 3 up-votes. For A: Limma-voom contrast confusion
Scholar 5 months ago, created an answer that has been accepted. For A: Limma Model Design
Commentator 5 months ago, created a comment with at least 3 up-votes. For C: limma: same data in different formats produces different DEG-analysis results
Teacher 5 months ago, created an answer with at least 3 up-votes. For A: Limma-voom contrast confusion
Scholar 5 months ago, created an answer that has been accepted. For A: Limma Model Design
Appreciated 6 months ago, created a post with more than 5 votes. For A: Combining newer/older RNAseq data, batch correcting
Appreciated 6 months ago, created a post with more than 5 votes. For A: Combining newer/older RNAseq data, batch correcting
Teacher 6 months ago, created an answer with at least 3 up-votes. For A: Limma-voom contrast confusion
Appreciated 6 months ago, created a post with more than 5 votes. For A: Combining newer/older RNAseq data, batch correcting
Commentator 6 months ago, created a comment with at least 3 up-votes. For C: Filtering lowly expressed genes in voom-limma analysis
Scholar 6 months ago, created an answer that has been accepted. For A: limma for metabolite data
Teacher 6 months ago, created an answer with at least 3 up-votes. For A: Limma-voom contrast confusion
Scholar 6 months ago, created an answer that has been accepted. For A: limma for metabolite data
Teacher 6 months ago, created an answer with at least 3 up-votes. For A: Limma-voom contrast confusion
Scholar 7 months ago, created an answer that has been accepted. For A: limma for metabolite data
Commentator 7 months ago, created a comment with at least 3 up-votes. For C: Filtering lowly expressed genes in voom-limma analysis
Scholar 7 months ago, created an answer that has been accepted. For A: limma for metabolite data
Scholar 7 months ago, created an answer that has been accepted. For A: limma for metabolite data
Teacher 7 months ago, created an answer with at least 3 up-votes. For A: Limma-voom contrast confusion
Scholar 7 months ago, created an answer that has been accepted. For A: limma for metabolite data
Scholar 7 months ago, created an answer that has been accepted. For A: (batch) corrections of RNA-seq data: integrating LIMMA and SVA
Teacher 7 months ago, created an answer with at least 3 up-votes. For A: Limma-voom contrast confusion
Scholar 7 months ago, created an answer that has been accepted. For A: (batch) corrections of RNA-seq data: integrating LIMMA and SVA

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