## User: rbronste

rbronste60
Reputation:
60
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Location:
@RBronshteyn
Last seen:
3 weeks, 2 days ago
Joined:
1 year, 8 months ago
Email:
r************@gmail.com

#### Posts by rbronste

<prev • 121 results • page 1 of 13 • next >
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... Although I relevel in the following way, the GRanges with results still lists BB as the negative log2FoldChange, wondering what I am doing incorrectly here? Thanks. dds<-DESeqDataSet(se, design= ~batch + treatment) dds$group <- factor(paste0(dds$treatment)) dds$treatment<-relevel(dds$tr ...
written 5 weeks ago by rbronste60 • updated 5 weeks ago by Michael Love19k
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... Thanks! That explains it really nicely. One additional question is whether in ATAC data using DBA_SCORE_READS this consensus means anything like it does with the RNA-seq data where differences in expression of a gene are inferred. Im assuming it simply means smaller or larger open chromatin regions ...
written 6 weeks ago by rbronste60
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... Sure of course, I just mean that baseMean in gene expression data represents to some approximation the transcript abundance however in ChIP or ATAC data merely represents the fragment pileup at a specific site, unless I am incorrect?  ...
written 6 weeks ago by rbronste60
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... Yes this is quite helpful however I guess I am still a bit confused as what baseMean represents in an RNA-seq experiment vs the experiment I am indicating with the code above? The binding matrix in question above is made from ATAC-seq data. Thanks. ...
written 6 weeks ago by rbronste60
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... Yes actually that answers part of it, however an even deeper and perhaps slightly naive question is how the baseMean called by DESeq2 relates to the original counts and how does that change with normalization within DESeq2 - trying to determine if the problem is with the stringency of called peaks b ...
written 6 weeks ago by rbronste60
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... So I am using DiffBind to create a count matrix as summarizedExperiment and then running this through DESeq2 and I was wondering about ways to filter for specific baseMean ranges within this data? My script looks like the following: library("DESeq2") library("ggplot2") library("BiocParallel") libr ...
written 7 weeks ago by rbronste60
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... Currently just using the following setup to look at differences in treatment across all 3 time points I have (30, 180, 360 min) however would like to also break down analysis by time, any suggestions for design would be much appreciated thank you! hyMData<-read.csv("hyM.csv") rownames(hyMData) ...
written 11 weeks ago by rbronste60 • updated 11 weeks ago by Michael Love19k
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... Wondering about the current state of thought on this? Does not have to be a high throughput, just something straightforward to use and uses data from StepOne Plus qPCR machine. Thanks! ...
written 4 months ago by rbronste60 • updated 4 months ago by Gordon Smyth35k
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Comment: C: DESeq2 design subcategories
... Thanks for the tip! The code in the vignette refers to doing this with raw counts and I was more interested in doing this with output of results() such as from: results(dds, contrast=c(1, -1/3, -1/3, -1/3)) With all four possible coefficients plotted. Thanks again! ...
written 7 months ago by rbronste60
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Comment: C: DESeq2 design subcategories
... A bit of a tangential question, but do you have any suggestions on how to effectively visualize results of something like this comparison, basically some kind of 4-way (dimension) graph that shows differential peaks unique to each of the 4 categories? Thanks! ...
written 7 months ago by rbronste60

#### Latest awards to rbronste

Centurion 15 months ago, created 100 posts.
Supporter 15 months ago, voted at least 25 times.

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