How to extract overlapping and unique peaks from the Venn Diagram to a csv format in DiffBind?
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Hesh ▴ 10
@hesh-14437
Last seen 4.1 years ago
University of Washington

Hi, 

I have differential binding analysis performed on a set of samples and plotted a Venn diagram (using DiffBind) to look at overlapping and unique diff. bound sites. Now I want to get those peaks in the Venn Diagram as a list for further analysis and to look on IGV. How can I convert these data to a report / csv file ? "bReturnPeaksets" function is removed it seems.

 

Thank you

Hesh

DiffBind plotvenn • 2.1k views
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Rory Stark ★ 5.2k
@rory-stark-5741
Last seen 8 weeks ago
Cambridge, UK

dba.plotVenn() returns the overlapping peaksets "invisibly", so bReturnPeaksets is no longer needed. Simple assign the return value of dba.plotVenn() to a variable and you will have a list of all the overlapping peaksets (as GRanges), as before.

 

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Thank you! 

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I'm having trouble converting the output GRanges file to a CSV file. I did try a couple different methods to convert the GRanges to a CSV or BED file but I keep getting errors. Highly appreciate if you can let me know how to get the output in CSV format. 

Thank you!

 

This is what I tried: 

gr <- GRanges(seqnames = Rle(Venn_2$name),
              ranges = IRanges(Venn_2$start, end=Venn_2$stop),
              strand = Rle(strand(c(rep("*", length(Venn_2$name))))),
              Conc = Venn_2$Conc)
venn_2_df <- data.frame(seqnames=seqnames(gr), 
                        starts=start(gr)-1,
                        ends=end(gr),
                        names=c(rep(".", length(gr))),
                        scores=c(rep(".", length(gr))),
                        strands=strand(gr))
write.table(venn_2_df, file="Venn_c123_th1.bed", quote=F, sep="\t", row.names=F, col.names = F)

 

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Actually you can just call write.csv() on a GRanges object. You will get a column with the strand, which you may not want.

Another way is to convert a GRanges to a data.frame by calling data.frame(myGRanges), then write that out with write.csv() including/deleting the columns you are/aren't interested in.

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