User: Aaron Lun

gravatar for Aaron Lun
Aaron Lun16k
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16,120
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Location:
Cambridge, United Kingdom
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Last seen:
15 hours ago
Joined:
3 years 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 • 1,756 results • page 1 of 176 • next >
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Answer: A: Differential ChIP-seq with csaw: How to normalise counts on repetitive regions (
... The multi-mapping reads (or lack thereof) should not affect how TMM normalization behaves. The assumption of TMM normalization on binned counts is that most regions of the genome are not marked, i.e., background, and all background regions are not DB between conditions. The normalization factors are ...
written 2 days ago by Aaron Lun16k
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Answer: A: csaw::combineTests: Error: length(ids) == nrow(tab) is not TRUE
... As the error message suggests, the lengths of the inputs don't match up. You have 14051634 elements in your rowRanges output but only 120695 rows in your results$table. This is most probably caused by the fact that you filtered on abundance at some point in your analysis, but then you kept the unfil ...
written 4 days ago by Aaron Lun16k
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Comment: C: Saving output from glmTreat to a csv file?
... Use names<- or setNames on res$table$PValue. ...
written 4 days ago by Aaron Lun16k
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Answer: A: Saving output from glmTreat to a csv file?
... Try using the write.csv function. library(edgeR) example(glmTreat) res <- topTags(tr, n=Inf) write.csv(file="output.csv", res$table) ...
written 4 days ago by Aaron Lun16k • updated 4 days ago by Gordon Smyth31k
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Comment: C: Why edgeR::aveLogCPM() is simlar to log2(rowMeans(cpm)) instead of rowMeans(cpm(
... If you're fitting a linear model to log-expression values, the independent filter statistic would technically be the mean log-expression across samples. However, I wouldn't worry about it; indeed, the edgeR user's guide describes different filtering strategies altogether. This is because the choice ...
written 8 days ago by Aaron Lun16k
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Answer: A: Why edgeR::aveLogCPM() is simlar to log2(rowMeans(cpm)) instead of rowMeans(cpm(
... No, because the aveLogCPM function is based on the mean for each gene under a negative binomial model, which naturally considers counts on the raw scale. Specifically, the count for each sample i is assumed to be sampled from a negative binomial distribution with mean equal to x*lib_i where lib_i is ...
written 8 days ago by Aaron Lun16k
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Answer: A: bias.data vector must have the same length as DEgenes vector!
... There are a number of errors with your code: Is "Length" really a gene name? I think you missed a header=TRUE when loading these tables. Missing values in R use NA, not "n/a". nullp expects a vector for bias.data, not a data.frame. See ?nullp. (It also expects a string for id, but this seems to ...
written 8 days ago by Aaron Lun16k
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Answer: A: adding genes to edgeR
... Your gene names are already row names for rawCountTable, so there's no need to explicitly assign a data.frame to y$genes to represent this information. It's perfectly fine to leave y$genes empty if you don't have any extra gene-level annotation to add. ...
written 8 days ago by Aaron Lun16k
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Comment: C: Limma for differential expression in a time-course
... Estimate... of what? Of the second coefficient, i.e., the log-fold change between groups? If so, yes, the fit will use information across all samples at all time points to estimate the coefficient. However, the most informative samples will be those in the time intervals that have samples from both ...
written 8 days ago by Aaron Lun16k
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Comment: C: Limma for differential expression in a time-course
... In the additive model, looking at a shift in expression between groups at the first time point is the same as looking at a shift at any time point, because the time effect is the same between groups. So if there's a log-fold change of 2 at the first time point, there will also be a log-fold change o ...
written 9 days ago by Aaron Lun16k

Latest awards to Aaron Lun

Scholar 12 weeks ago, created an answer that has been accepted. For A: EdgeR -ANOVA-like test vs testing individual contrasts
Scholar 12 weeks ago, created an answer that has been accepted. For A: Limma Model Design
Teacher 3 months ago, created an answer with at least 3 up-votes. For A: Limma-voom contrast confusion
Scholar 3 months ago, created an answer that has been accepted. For A: Limma Model Design
Commentator 3 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 3 months ago, created an answer with at least 3 up-votes. For A: Limma-voom contrast confusion
Scholar 3 months ago, created an answer that has been accepted. For A: Limma Model Design
Appreciated 4 months ago, created a post with more than 5 votes. For A: Combining newer/older RNAseq data, batch correcting
Appreciated 4 months ago, created a post with more than 5 votes. For A: Combining newer/older RNAseq data, batch correcting
Teacher 4 months ago, created an answer with at least 3 up-votes. For A: Limma-voom contrast confusion
Appreciated 4 months ago, created a post with more than 5 votes. For A: Combining newer/older RNAseq data, batch correcting
Commentator 4 months ago, created a comment with at least 3 up-votes. For C: Filtering lowly expressed genes in voom-limma analysis
Scholar 4 months ago, created an answer that has been accepted. For A: limma for metabolite data
Teacher 4 months ago, created an answer with at least 3 up-votes. For A: Limma-voom contrast confusion
Scholar 4 months ago, created an answer that has been accepted. For A: limma for metabolite data
Teacher 4 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 for metabolite data
Commentator 5 months ago, created a comment with at least 3 up-votes. For C: Filtering lowly expressed genes in voom-limma analysis
Scholar 5 months ago, created an answer that has been accepted. For A: limma for metabolite data
Scholar 5 months ago, created an answer that has been accepted. For A: limma for metabolite data
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 for metabolite data
Scholar 5 months ago, created an answer that has been accepted. For A: (batch) corrections of RNA-seq data: integrating LIMMA and SVA
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: (batch) corrections of RNA-seq data: integrating LIMMA and SVA

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