Moderator: Michael Love

gravatar for Michael Love
Michael Love13k
Reputation:
12,520
Status:
Trusted
Location:
United States
Website:
http://mikelove.github...
Twitter:
mikelove
Scholar ID:
Google Scholar Page
Last seen:
2 days, 4 hours ago
Joined:
4 years, 4 months ago
Email:
m****************@gmail.com

Michael I. Love, Dr. rer. nat.
Assistant Professor
Departments of Biostatistics and Genetics
University of North Carolina-Chapel Hill

My main Bioconductor involvement is to maintain these software packages

and the RNA-seq gene-level workflow.

Posts by Michael Love

<prev • 2,387 results • page 1 of 239 • next >
0
votes
1
answers
160
views
1
answers
Comment: C: DESeq2 model - How to test case/control time course model when taking account wi
... Good Q for a new post with a DEXSeq tag. ...
written 22 hours ago by Michael Love13k
0
votes
1
answers
160
views
1
answers
Comment: C: DESeq2 model - How to test case/control time course model when taking account wi
... For exon level you definitely need DEXSeq. The model is specifically designed for differential exon usage, controlling for gene expression. Best to read over the DEXSeq paper or vignette. ...
written 1 day ago by Michael Love13k
0
votes
3
answers
70
views
3
answers
Answer: A: Sparsity plot and how that indicates a model fit to negative binomial distributi
... I forgot, I had the image in my email from previously. This looks fine given the sample size of 3 vs 3. It means that for some genes all of the counts are from one sample but this is concentrated for the low to middle count genes, and the NB can accommodate this with higher dispersion values. ...
written 1 day ago by Michael Love13k
0
votes
1
answers
44
views
1
answers
Answer: A: Linear regression in DESeq2
... We have a FAQ about continuous covariates in the DESeq2 vignette. Briefly, yes, you can include them, and this is modeling the log of counts over changes in the covariates. The LFC is the change for each unit in the covariate. You can see this from the formula log(q) = X beta in the vignette and DES ...
written 1 day ago by Michael Love13k • updated 1 day ago by Wolfgang Huber13k
0
votes
3
answers
70
views
3
answers
Answer: A: Sparsity plot and how that indicates a model fit to negative binomial distributi
... Sorry I'm away from WiFi and can't access the PDF, I'll take a look as soon as I can. Generally I was using the plot as a diagnostic for when the majority of genes with high counts have most of the row sum coming from individual samples. ...
written 1 day ago by Michael Love13k • updated 13 hours ago by Wolfgang Huber13k
0
votes
2
answers
56
views
2
answers
Comment: C: Differences in PCA plot - rld versus vsd normalized data (DESeq2)
... Yes you can use removeBatchEffect on the transformed counts by running it on the assay() of a transformed dataset and reassigning to assay(). Note that MDS vs PCA is not causing a difference. MDA with Euclidean distance produces the same plot as PCA. ...
written 1 day ago by Michael Love13k • updated 1 day ago by Wolfgang Huber13k
0
votes
2
answers
56
views
2
answers
Answer: A: Differences in PCA plot - rld versus vsd normalized data (DESeq2)
... I'd recommend blind=FALSE (discussed in vignette) and the VST when there are many samples as here. There is a similar thread to this one that was posted a few days ago. You can find it by clicking the DESeq2 tag on this post. ...
written 1 day ago by Michael Love13k • updated 1 day ago by Wolfgang Huber13k
0
votes
2
answers
66
views
2
answers
Comment: C: DESeq2 - PCAplot differs between rlog and vsd transformation
... I prefer VST when there are many samples. The rlog seemed to outperform (according to our simulations performed in the DESeq2 paper) when there were very large differences in size factor (e.g. spanning an order of magnitude from low to high seq depth). ...
written 1 day ago by Michael Love13k
0
votes
3
answers
86
views
3
answers
Comment: C: DESeq function taking too long
... Methods tend to have large overlap as the sample size grows large. See for example Schurch 2016 or our DESeq2 paper. But limma-voom has a large speed advantage when you have 400+ samples as here. ...
written 2 days ago by Michael Love13k
0
votes
3
answers
86
views
3
answers
Comment: C: DESeq function taking too long
... I was suggesting to subset genes, not samples. You can use an index such as rowSums(counts(dds,normalized=TRUE) >= 10) >= 5) or fill in a reasonable value instead of 5. For me, datasets on the order of 400 can be computed in less than an hour with DESeq() using e.g. 4 cores with parallel=TRUE. ...
written 2 days ago by Michael Love13k

Latest awards to Michael Love

Scholar 5 weeks ago, created an answer that has been accepted. For A: ABOUT TRANSFORMATION OF RNA-SEQ DATA FOR GLMNET COX SURVIVAL ANALYSIS
Scholar 5 weeks ago, created an answer that has been accepted. For A: ABOUT TRANSFORMATION OF RNA-SEQ DATA FOR GLMNET COX SURVIVAL ANALYSIS
Scholar 5 weeks ago, created an answer that has been accepted. For A: ABOUT TRANSFORMATION OF RNA-SEQ DATA FOR GLMNET COX SURVIVAL ANALYSIS
Student 5 weeks ago, asked a question with at least 3 up-votes. For recount counts in the example experiment
Appreciated 7 weeks ago, created a post with more than 5 votes. For A: DESeq2 Model Design
Scholar 8 weeks ago, created an answer that has been accepted. For A: ABOUT TRANSFORMATION OF RNA-SEQ DATA FOR GLMNET COX SURVIVAL ANALYSIS
Student 8 weeks ago, asked a question with at least 3 up-votes. For Updated DESeq2 performance on highly replicated yeast RNA-seq data
Good Answer 9 weeks ago, created an answer that was upvoted at least 5 times. For A: DESeq2 Model Design
Scholar 10 weeks ago, created an answer that has been accepted. For A: ABOUT TRANSFORMATION OF RNA-SEQ DATA FOR GLMNET COX SURVIVAL ANALYSIS
Teacher 10 weeks ago, created an answer with at least 3 up-votes. For A: Is the VST implemented in DESeq useful on time-series cell differentiation datas
Teacher 10 weeks ago, created an answer with at least 3 up-votes. For A: Is the VST implemented in DESeq useful on time-series cell differentiation datas
Scholar 10 weeks ago, created an answer that has been accepted. For A: ABOUT TRANSFORMATION OF RNA-SEQ DATA FOR GLMNET COX SURVIVAL ANALYSIS
Teacher 10 weeks ago, created an answer with at least 3 up-votes. For A: Is the VST implemented in DESeq useful on time-series cell differentiation datas
Teacher 10 weeks ago, created an answer with at least 3 up-votes. For A: Is the VST implemented in DESeq useful on time-series cell differentiation datas
Popular Question 10 weeks ago, created a question with more than 1,000 views. For DESeq2 testing ratio of ratios (RIP-Seq, CLIP-Seq, ribosomal profiling)
Popular Question 11 weeks ago, created a question with more than 1,000 views. For DESeq2 testing ratio of ratios (RIP-Seq, CLIP-Seq, ribosomal profiling)
Appreciated 11 weeks ago, created a post with more than 5 votes. For Updated DESeq2 performance on highly replicated yeast RNA-seq data
Scholar 12 weeks ago, created an answer that has been accepted. For A: ABOUT TRANSFORMATION OF RNA-SEQ DATA FOR GLMNET COX SURVIVAL ANALYSIS
Scholar 3 months ago, created an answer that has been accepted. For A: ABOUT TRANSFORMATION OF RNA-SEQ DATA FOR GLMNET COX SURVIVAL ANALYSIS
Teacher 3 months ago, created an answer with at least 3 up-votes. For A: Is the VST implemented in DESeq useful on time-series cell differentiation datas
Appreciated 3 months ago, created a post with more than 5 votes. For Updated DESeq2 performance on highly replicated yeast RNA-seq data
Scholar 3 months ago, created an answer that has been accepted. For A: ABOUT TRANSFORMATION OF RNA-SEQ DATA FOR GLMNET COX SURVIVAL ANALYSIS
Scholar 3 months ago, created an answer that has been accepted. For A: ABOUT TRANSFORMATION OF RNA-SEQ DATA FOR GLMNET COX SURVIVAL ANALYSIS
Appreciated 4 months ago, created a post with more than 5 votes. For DESeq2 testing ratio of ratios (RIP-Seq, CLIP-Seq, ribosomal profiling)

Help
Access

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 2.2.0
Traffic: 267 users visited in the last hour