ChiPQC and paired-end data

0

Entering edit mode

Ugo Borello ▴ 340

@ugo-borello-5753

Last seen 5.8 years ago

France

Dear Rory, I have few basic questions about ChiPQC. - Could I use ChiPQC with paired-end data? - I would like to use my mouse blacklist https://sites.google.com/site/anshulkundaje/projects/blacklists MOUSE (mm9): http://www.broadinstitute.org/~anshul/projects/mouse/blacklist/mm9-bla cklist .bed.gz I noticed that the formatting of this mm9-blacklist.bed is different from your blacklist_hg19.bed. For example your file has an header, not mine. Is it correct then to provide only a filename to my blacklist, when calling ChIPQC(), or is it better to import the bed file as Granges object first? - If I understand correctly, while constructing a ChIPQCexperiment object and setting consensus=TRUE, a consensus peak set is generated. This consensus peak set consists of the peaks overlapping at least two of the replicate samples, correct? Is it possible to access this consensus peak set? Thank you for your help and for this very useful tool, Ugo

ChIPQC ChIPQC • 1.8k views

ADD COMMENT • link updated 9.7 years ago by Carroll, Thomas ▴ 20 • written 9.8 years ago by Ugo Borello ▴ 340

0

Entering edit mode

Carroll, Thomas ▴ 20

@carroll-thomas-6672

Last seen 9.6 years ago

Hi Ugo, Sorry for the delay in reply. If you include the maintainers in the post then I will get a quicker notification. I usually supply blacklists as GRanges objects and this is what i have done when using mm9 blacklists myself form Anshul Kudaje's site. ChIPQC expects there to be a header when reading from a file. You could use paired-end data with ChIPQC but for now this would require you to filter your Bam file for only "first read in pair" in order to avoid double counting and biasing the cross-coverage scores plots. This should be pretty straightforward to do using samtools view. In the future we will include paired-end data analysis for ChIPQC. Not sure how Diffbind handles paired end data, perhaps Rory has an idea? To retrieve consensus sets you could take the DBA object from ChIPQCexperiment and work from there using the Diffbind package. dbaobject = ChIPQCexperiment at DBA Then simply follow DiffBind vignette to select a suitable consensus set. best, Tom Thomas Carroll Head of Bioinformatics MRC Clinical Sciences Centre, Faculty of Medicine, Imperial College London,Hammersmith Hospital Campus Du Cane Road,London,W12 0NN

ADD COMMENT • link 9.7 years ago Carroll, Thomas ▴ 20

0

Entering edit mode

Thank you Thomas, > You could use paired-end data with ChIPQC but for now this would require you > to filter your Bam file for only "first read in pair" in order to avoid double > counting and biasing the cross-coverage scores plots. > This should be pretty straightforward to do using samtools view. To be sure I understand you mean: $ samtools view -f 64 > To retrieve consensus sets you could take the DBA object from ChIPQCexperiment > and work from there using the Diffbind package. > > dbaobject = ChIPQCexperiment at DBA Indeed, I finally got my consensus playing with the Diffbind package. I needed to understand how to link properly ChIPQC with Diffbind. Thank you again for your help. Ugo > From: "Carroll, Thomas" <thomas.carroll at="" csc.mrc.ac.uk=""> > Date: Mon, 28 Jul 2014 12:16:15 +0000 > To: "bioconductor at r-project.org" <bioconductor at="" r-project.org=""> > Cc: "ugo.borello at inserm.fr" <ugo.borello at="" inserm.fr=""> > Subject: Re: [BioC] ChiPQC and paired-end data > > Hi Ugo, > > Sorry for the delay in reply. If you include the maintainers in the post then > I will get a quicker notification. > > > I usually supply blacklists as GRanges objects and this is what i have done > when using mm9 blacklists myself form Anshul Kudaje's site. ChIPQC expects > there to be a header when reading from a file. > > You could use paired-end data with ChIPQC but for now this would require you > to filter your Bam file for only "first read in pair" in order to avoid double > counting and biasing the cross-coverage scores plots. > This should be pretty straightforward to do using samtools view. > > In the future we will include paired-end data analysis for ChIPQC. Not sure > how Diffbind handles paired end data, perhaps Rory has an idea? > > > > > To retrieve consensus sets you could take the DBA object from ChIPQCexperiment > and work from there using the Diffbind package. > > dbaobject = ChIPQCexperiment at DBA > > > Then simply follow DiffBind vignette to select a suitable consensus set. > > > best, > > Tom > > > Thomas Carroll > Head of Bioinformatics > MRC Clinical Sciences Centre, Faculty of Medicine, > Imperial College London,Hammersmith Hospital Campus > Du Cane Road,London,W12 0NN

ADD REPLY • link 9.7 years ago Ugo Borello ▴ 340

0

Entering edit mode

Hi Ugo, >To be sure I understand you mean: >$ samtools view -f 64 That sounds right to get the first in pair. Cheers, tom Thomas Carroll Head of Bioinformatics MRC Clinical Sciences Centre, Faculty of Medicine, Imperial College London,Hammersmith Hospital Campus Du Cane Road,London,W12 0NN ________________________________________ From: Ugo Borello [ugo.borello@inserm.fr] Sent: Wednesday, July 30, 2014 3:05 PM To: Carroll, Thomas; bioconductor at r-project.org Subject: Re: [BioC] ChiPQC and paired-end data Thank you Thomas, > You could use paired-end data with ChIPQC but for now this would require you > to filter your Bam file for only "first read in pair" in order to avoid double > counting and biasing the cross-coverage scores plots. > This should be pretty straightforward to do using samtools view. To be sure I understand you mean: $ samtools view -f 64 > To retrieve consensus sets you could take the DBA object from ChIPQCexperiment > and work from there using the Diffbind package. > > dbaobject = ChIPQCexperiment at DBA Indeed, I finally got my consensus playing with the Diffbind package. I needed to understand how to link properly ChIPQC with Diffbind. Thank you again for your help. Ugo > From: "Carroll, Thomas" <thomas.carroll at="" csc.mrc.ac.uk=""> > Date: Mon, 28 Jul 2014 12:16:15 +0000 > To: "bioconductor at r-project.org" <bioconductor at="" r-project.org=""> > Cc: "ugo.borello at inserm.fr" <ugo.borello at="" inserm.fr=""> > Subject: Re: [BioC] ChiPQC and paired-end data > > Hi Ugo, > > Sorry for the delay in reply. If you include the maintainers in the post then > I will get a quicker notification. > > > I usually supply blacklists as GRanges objects and this is what i have done > when using mm9 blacklists myself form Anshul Kudaje's site. ChIPQC expects > there to be a header when reading from a file. > > You could use paired-end data with ChIPQC but for now this would require you > to filter your Bam file for only "first read in pair" in order to avoid double > counting and biasing the cross-coverage scores plots. > This should be pretty straightforward to do using samtools view. > > In the future we will include paired-end data analysis for ChIPQC. Not sure > how Diffbind handles paired end data, perhaps Rory has an idea? > > > > > To retrieve consensus sets you could take the DBA object from ChIPQCexperiment > and work from there using the Diffbind package. > > dbaobject = ChIPQCexperiment at DBA > > > Then simply follow DiffBind vignette to select a suitable consensus set. > > > best, > > Tom > > > Thomas Carroll > Head of Bioinformatics > MRC Clinical Sciences Centre, Faculty of Medicine, > Imperial College London,Hammersmith Hospital Campus > Du Cane Road,London,W12 0NN

ADD REPLY • link 9.7 years ago Carroll, Thomas ▴ 20

0

Entering edit mode

Tom Carroll ▴ 10

@tom-carroll-6669

Last seen 9.6 years ago

Ugo Borello <ugo.borello at="" ...=""> writes: > > Dear Rory, > > I have few basic questions about ChiPQC. > > - Could I use ChiPQC with paired-end data? > > - I would like to use my mouse blacklist > https://sites.google.com/site/anshulkundaje/projects/blacklists > MOUSE (mm9): > http://www.broadinstitute.org/~anshul/projects/mouse/blacklist/mm9-b lacklist > .bed.gz > > I noticed that the formatting of this mm9-blacklist.bed is different from > your blacklist_hg19.bed. For example your file has an header, not mine. > Is it correct then to provide only a filename to my blacklist, when calling > ChIPQC(), or is it better to import the bed file as Granges object first? > > - If I understand correctly, while constructing a ChIPQCexperiment object > and setting consensus=TRUE, a consensus peak set is generated. This > consensus peak set consists of the peaks overlapping at least two of the > replicate samples, correct? > Is it possible to access this consensus peak set? > > Thank you for your help and for this very useful tool, > > Ugo > > _______________________________________________ > Bioconductor mailing list > Bioconductor at ... > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor > > Hi Ugo, Sorry for the delay in reply. Supplying a GRanges object should work well and typically what I do. ChIPQC expects there to be a header when reading from a file so your file should be good. You could use paired-end data with ChIPQC but for now this would require you to filter your Bam file for only "first read in pair" in order to avoid double counting and biasing the cross-coverage scores plots. This should be straightforward to do using something like samtools view. In the future I do want to include paired-end data analysis for ChIPQC to accommodate MNAse-seq. I'm not sure how Diffbind handles paired end data, perhaps Rory has an idea? To retrieve consensus sets you could take the DBA object from ChIPQCexperiment and work from there using the Diffbind package. dbaobject = ChIPQCexperimentObject at DBA best, Tom Thomas Carroll Head of Bioinformatics, MRC Clinical Sciences Centre, Faculty of Medicine, Imperial College London,Hammersmith Hospital Campus, Du Cane Road,London,W12 0NN

ADD COMMENT • link 9.7 years ago Tom Carroll ▴ 10

Login before adding your answer.