User: kautilya

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kautilya380
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Posts by kautilya

<prev • 49 results • page 1 of 5 • next >
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Comment: C: Diffbind - Very high proportion of significant peaks
... Thanks for replying!. - *Do you expect the conditions to change the open chromatin landscape quite a bit?* Yes, this is a gene knockout experiment and the gene is part of a nucleosome remodelling complex. - *How are the differential sites divided between the two conditions? Do they mo ...
written 8 months ago by kautilya380
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Comment: C: Diffbind - Very high proportion of significant peaks
... Thanks for the reply! I am new to peak based analysis in general. I chose BAMPE over a specific shift/extsize based on the MACS2 authors recommendation [here][1] The other parameters that I have seen being used for ATAC are `--shift -75/-100 extsize 150/200`. But will these not then result in furth ...
written 8 months ago by kautilya380
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Comment: C: Diffbind - Very high proportion of significant peaks
... Thanks again. Apologies was out of office. - The gene which was knocked out is the part of an nucleosome remodeling complex so i think the large-scale effects can be expected. - The insert sizes of at least 4 of 6 samples shows a clear increase around 170-200 bp and another small one at ~40 ...
written 8 months ago by kautilya380
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Comment: C: Diffbind - Very high proportion of significant peaks
... Thanks for the reply!. The experiment is a gene knockout experiment and the organism here is Mus musculus(using mm10 as reference). There is no input/control. It is comparison of wild type vs the knockout each having 3 replicates. ...
written 8 months ago by kautilya380
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Diffbind - Very high proportion of significant peaks
... I am using **Diffbind** to call differential peaks on an ATAC seq dataset of condition A vs B each having 3 replicates. The total number of peaks post union is - 106700 and of these 33197 **(~30%)** come out as significant even with a stringent FDR cutoff of **0.01**. Is this high proportion of si ...
diffbind deseq2 atac-seq written 8 months ago by kautilya380
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Comment: C: Fold Change In R
... Can you provide some examples of the mean values for which you are getting this error? ...
written 9 months ago by kautilya380
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Comment: C: DESEQ analysis contain rlog formation?
... DEseq2 has a separate [rlog][1] function which you can use to transform your count data. You can supply it a matrix of counts or a deseq2 dataset. The default DESeq function will not give you rlog transformed data. [1]: https://rdrr.io/bioc/DESeq2/man/rlog.html ...
written 9 months ago by kautilya380
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Comment: C: Fold Change In R
... The warning indicates that you have markers which have `avg.t2d AND avg.healthy` as 0. One way of handling this is adding a small pseudo count of eg. 0.0001 to all the mean values. This will ensure that there are no 0's in your data and NANs will be 0 foldch as expected. ...
written 9 months ago by kautilya380
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Comment: C: Fold Change In R
... Use log2 for exploring the fold changes. You could do something like `log2(avg.t2d)-log2(avg.healthy)` ...
written 9 months ago by kautilya380
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Comment: C: Deseq plots interpretation
... Can you be more specific about any particular aspects/plots that you are not understanding? ...
written 10 months ago by kautilya380

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