User: A

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A0
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Posts by A

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Comment: C: Filtering genes with a minimum number of counts between samples
... Thank you for the reply! I will look into setting a minimum fold change but will also look at defining this using a base r function with the count matrix after DESeq. Thanks once again :) ...
written 10 days ago by A0
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Filtering genes with a minimum number of counts between samples
... Hi all,  I have searched for this high and low with no luck. I was wondering if it is possible (over a time course experiment) to filter genes that have a specific change across the time points.  So for example, I would like to be able to look at genes that change from one time point to another on ...
deseq2 filtering written 11 days ago by A0 • updated 11 days ago by Michael Love16k
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Comment: C: Filtering for genes >100 counts after LRT still showing significant genes with g
... Amazing! Thank you so much for making that crystal clear!    ...
written 12 days ago by A0
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Comment: C: Filtering for genes >100 counts after LRT still showing significant genes with g
... Many thanks!! Just out of interest though, just so I understand the full design itself, would I get the same list of DE genes if my full design is ~Genotype + Time +Genotype:Time and reduced genotype as full design of ~Genotype + Time and reduced genotype?   ...
written 13 days ago by A0
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Comment: C: Filtering for genes >100 counts after LRT still showing significant genes with g
... yep! I apologise, actually that was arbitrary... And I am looking at 1-10 as the filter. The reason I went up to 100 is because when I was filtering any count above 0 (i.e. 10), I was seeing so many 0's in the count matrix after the LRT, so increased it to 100 just to see what happens when I have a ...
written 13 days ago by A0
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Comment: A: Filtering for genes >100 counts after LRT still showing significant genes with g
... Thank you very much!! And yes, I also carried out the following code before running DESeq, where I also add conditions for how many samples should contain this minimum CPM count filter <- rowSums(nc >= 100) >= 2 ddsWT<-ddsWT[filter,] nrow(ddsWT) Thanks again! ...
written 13 days ago by A0
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Filtering for genes >100 counts after LRT still showing significant genes with genes with 0 counts!
... Hi all,  Just wondering if somebody can chime in on a funny problem I am having. I am filtering genes that have a minimum count of 100 to show after an LRT test to look for changes over time. This succesfully removes low count genes in the summary(results), however, when I make a count matrix of si ...
deseq2 lrt cpm lowcountgenes written 13 days ago by A0
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Comment: C: DESeq2 nbinomLRT results interpretation
... Sorry it was confusing...The question was basically, is Full= ~Time+Genotype+Time:Genotype and reduced ~Genotype the same as:  Full= ~Time+Genotype and reduced ~Genotype.   ...
written 16 days ago by A0
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Comment: C: DESeq2 nbinomLRT results interpretation
... Thank you so so much! That explains it perfectly! And thank you for being patient with me and all my questions!   As a quick follow up to your last point:with a full model of time+Genotype+Time:Genotype, is the reduced model of ~Time alone, or ~Genotype alone (Not reduced of Time+ and Genotype tog ...
written 16 days ago by A0
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Comment: C: DESeq2 nbinomLRT results interpretation
... Many thanks! Yes I will be partnering with someone to go through this properly. In the meantime, may I then ask an LRT related question (about the design specifically). I have seen other threads and just one to confirm I understand this.  I am looking for changes in time. I have 4 genotypes. Princi ...
written 17 days ago by A0

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