User: gil.hornung

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Posts by gil.hornung

<prev • 16 results • page 1 of 2 • next >
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Comment: C: Strong upwards correlation between log fold change and average log expression in
... Thank you Gordon and James for the fast and helpful answers. I used "1+" in my model and it worked fine.   Al the best ,   Gil ...
written 7 days ago by gil.hornung0
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Strong upwards correlation between log fold change and average log expression in MD plot of Limma
... Hi, I am trying to analyse my proteomics data (intensity based label free quantification) using Limma. When I look at the MD plot after limma fit, I see a strong correlation between log-fold-change and average-log-expression. What could cause this odd behaviour and how can I fix it? Thanks, Gil ...
proteomics limma written 9 days ago by gil.hornung0 • updated 9 days ago by Gordon Smyth32k
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Comment: C: Differential ChIP-seq with csaw: How to normalise counts on repetitive regions (
... Thanks Aaron! ...
written 8 weeks ago by gil.hornung0
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Differential ChIP-seq with csaw: How to normalise counts on repetitive regions (telomers)?
... Hi, I am interested in H3K9me2 signal (in S. Pombe), which is abundant on telomeres and centromeres. These regions are notorious for being highly repetitive. I clearly see an effect between treated and control samples in the coverage on telomeres, and I would like to quantify these differences usin ...
chip-seq csaw histone chip-seq written 8 weeks ago by gil.hornung0 • updated 8 weeks ago by Aaron Lun17k
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Comment: C: pre-ranked GSEA within R?
... A faster GSEA is great. Did you implement it in the stable release? I'm using version 1.10.2 and it is still slow. ...
written 16 months ago by gil.hornung0
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Comment: C: "Over-correction" in the size-factors of the DESeq2 package
... Thank you, Michael. I learned from this discussion. Indeed, the experiment was very noisy with large variation in number of reads. I'm just trying to salvage what I can. And, ofcourse, I will treat the results with a cup of salt. ...
written 19 months ago by gil.hornung0
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Comment: C: "Over-correction" in the size-factors of the DESeq2 package
... Thanks Michael. I understand that "correlation to bad is not a desirable property", however I am concerned that one of the assumption behind the DESeq normalization, namely that the expression of most genes is reliable, does not hold in this case. Below is the MA plot. Red line is the size factor ...
written 19 months ago by gil.hornung0
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Comment: C: "Over-correction" in the size-factors of the DESeq2 package
... Hi Michael, To my best understanding (and you are welcome to correct me), the DESeq normalization is in place to control for changes in genes that are take up most of the counts, and can then bias the total number of counts. I am not too concerned about this in this sample, because the most highly ...
written 19 months ago by gil.hornung0
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Comment: C: "Over-correction" in the size-factors of the DESeq2 package
... Wow, fast answer, Michael! Here is what you asked for: > round(quantile(rowMeans(counts(dds)), 0:10/10))    0%   10%   20%   30%   40%   50%   60%   70%   80%   90%  100%      0     7    51    93   146   219   314   461   705  1278 30096  the "regular" size factor of the problematic sample: ...
written 19 months ago by gil.hornung0
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Comment: C: Error when trying to load a gff3 with GenomicFeatures
... Thank you, Mike! ...
written 19 months ago by gil.hornung0

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