chip-chip data
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@fire1976-wyoming-324
Last seen 9.6 years ago
Hi there, I am trying to analyze chip-chip data from Nimblegen 385k arrays for histone methylated regions. I have replicates from both wild type and knock out cells with separate inputs (controls) for the KO and WT. That makes a total of 12 arrays. I was wondering if anybody could help me in pointing at the right package or tools. I am new to chip-chip data. Thanks in advance, Som. _________________________________________________________________ Hotmail: Free, trusted and rich email service. [[alternative HTML version deleted]]
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Noah Dowell ▴ 410
@noah-dowell-3791
Last seen 9.6 years ago
Hello Som, The Ringo package works quite nicely with Nimblegen arrays. I also used the wonderful Starr package for chip-chip on tiling Affymetrix arrays. After using those packages for looking at data quality and normalization there are some graphical tools and analysis tools (like finding the chip-enriched regions) too, but many other packages can work with the data in the resulting Ringo/Starr derived expression sets. noah On Mar 4, 2010, at 4:27 PM, somnath bandyopadhyay wrote: > > Hi there, > > I am trying to analyze chip-chip data from Nimblegen 385k arrays for histone methylated regions. I have replicates from both wild type and knock out cells with separate inputs (controls) for the KO and WT. That makes a total of 12 arrays. I was wondering if anybody could help me in pointing at the right package or tools. I am new to chip-chip data. > > > > Thanks in advance, > > Som. > > _________________________________________________________________ > Hotmail: Free, trusted and rich email service. > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor
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@sean-davis-490
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United States
On Thu, Mar 4, 2010 at 7:27 PM, somnath bandyopadhyay <genome1976 at="" hotmail.com=""> wrote: > > Hi there, > > I am trying to analyze chip-chip data from Nimblegen 385k arrays for histone methylated regions. I have replicates from both wild type and knock out cells with separate inputs (controls) for the KO and WT. That makes a total of 12 arrays. I was wondering if anybody could help me in pointing at the right package or tools. I am new to chip-chip data. > Hi, Somnath. Off the top of my head, you could check out the Ringo, Starr, BAC, or ACME packages; there may be others. Sean
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Noah Dowell ▴ 410
@noah-dowell-3791
Last seen 9.6 years ago
The vignettes for Starr and Ringo are quite helpful for getting started on reading in your files, processing and normalization. There is also a publication associated with Ringo for a little more explanation. It seems like you have all of the files so just fire up Ringo and see how it works :). (There are example data "made" for Ringo that you can use to test it out and make sure your files look like they "should.") Here is the link to the vignette: Ringo: http://www.bioconductor.org/packages/release/bioc/vignettes/Ringo/inst /doc/Ringo.pdf And the paper citation: J. Toedling, O. Sklyar, T. Krueger, J. J. Fischer, S. Sperling, and W. Huber. Ringo - an R/Bioconductor package for analyzing ChIP-chip readouts. BMC Bioinformatics, 8:221, 2007. I am certainly not the expert on this board but if you start to get specific errors (on your data analysis) after you read through the vignette and worked with the example data then post them and I will do my best to help out. noah Hello Noah, Thanks for the suggestions. Do you have a protocol or something for Starr or Ringo? I am starting from .pair, .ndf, .pos and .gff (for the nimblegen refseq mouse genome) nimblegen files. I would really appreciate it if you would share your protocol/s. Thanks so much, Som. > Subject: Re: [BioC] chip-chip data > From: noahd@ucla.edu > Date: Thu, 4 Mar 2010 19:55:21 -0800 > CC: bioconductor@stat.math.ethz.ch > To: genome1976@hotmail.com > > Hello Som, > > The Ringo package works quite nicely with Nimblegen arrays. I also used the wonderful Starr package for chip-chip on tiling Affymetrix arrays. After using those packages for looking at data quality and normalization there are some graphical tools and analysis tools (like finding the chip-enriched regions) too, but many other packages can work with the data in the resulting Ringo/Starr derived expression sets. > > noah > > > On Mar 4, 2010, at 4:27 PM, somnath bandyopadhyay wrote: > > > > > Hi there, > > > > I am trying to analyze chip-chip data from Nimblegen 385k arrays for histone methylated regions. I have replicates from both wild type and knock out cells with separate inputs (controls) for the KO and WT. That makes a total of 12 arrays. I was wondering if anybody could help me in pointing at the right package or tools. I am new to chip-chip data. > > > > > > > > Thanks in advance, > > > > Som. > > [[alternative HTML version deleted]]
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Hi Som, there also is a Plos Computional Biology article, which also provides many details on how to use Ringo: http://tinyurl.com/ydvrjq8 You may also want to have a look at the associated data package "ccTutorial". Best regards, Joern On Fri, 5 Mar 2010 11:42:30 -0800, Noah Dowell wrote > The vignettes for Starr and Ringo are quite helpful for getting > started on reading in your files, processing and normalization. > There is also a publication associated with Ringo for a little more > explanation. It seems like you have all of the files so just fire > up Ringo and see how it works :). (There are example data "made" for > Ringo that you can use to test it out and make sure your files look > like they "should.") > > Here is the link to the vignette: > > Ringo: > > http://www.bioconductor.org/packages/release/bioc/vignettes/Ringo/inst /doc/Ringo.pdf > > And the paper citation: > > J. Toedling, O. Sklyar, T. Krueger, J. J. Fischer, S. Sperling, and > W. Huber. Ringo - an R/Bioconductor package for analyzing ChIP-chip > readouts. BMC Bioinformatics, 8:221, 2007. > > I am certainly not the expert on this board but if you start to get > specific errors (on your data analysis) after you read through the > vignette and worked with the example data then post them and I will > do my best to help out. > > noah > > Hello Noah, > > Thanks for the suggestions. Do you have a protocol or something for > Starr or Ringo? I am starting from .pair, .ndf, .pos and .gff (for > the nimblegen refseq mouse genome) nimblegen files. I would really > appreciate it if you would share your protocol/s. > > Thanks so much, > Som. > --- Joern Toedling Institut Curie -- U900 26 rue d'Ulm, 75005 Paris, FRANCE Tel. +33 (0)156246927
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Hello Joern, I am having some trouble with the mapping of the reporters to the genomic positions. 1. I have downloaded the ccTutorial and have takena look at the exonerateData folder. I was wondering how I could create a .fsa file like RenMM5TilingProbe-Sequences.fsa from my Nimlegen .ndf file for the sequences for all the reporters on my 385k chip? 2. I have the .sh and .pl files in the exonerateData folder. Once I have my .fsa file from above, what exactly do I need to run to create the "allChromExonerateOut.txt" file?Do all the files ... .fsa, .sh and the .pl have to be in the current working directory? Thanks in advance! Best Regards, Som. > From: Joern.Toedling@curie.fr > To: bioconductor@stat.math.ethz.ch > Date: Sat, 6 Mar 2010 09:58:21 +0100 > Subject: Re: [BioC] chip-chip data > > Hi Som, > > there also is a Plos Computional Biology article, which also provides many > details on how to use Ringo: > http://tinyurl.com/ydvrjq8 > You may also want to have a look at the associated data package "ccTutorial". > > Best regards, > Joern > > On Fri, 5 Mar 2010 11:42:30 -0800, Noah Dowell wrote > > The vignettes for Starr and Ringo are quite helpful for getting > > started on reading in your files, processing and normalization. > > There is also a publication associated with Ringo for a little more > > explanation. It seems like you have all of the files so just fire > > up Ringo and see how it works :). (There are example data "made" for > > Ringo that you can use to test it out and make sure your files look > > like they "should.") > > > > Here is the link to the vignette: > > > > Ringo: > > > > > http://www.bioconductor.org/packages/release/bioc/vignettes/Ringo/in st/doc/Ringo.pdf > > > > And the paper citation: > > > > J. Toedling, O. Sklyar, T. Krueger, J. J. Fischer, S. Sperling, and > > W. Huber. Ringo - an R/Bioconductor package for analyzing ChIP- chip > > readouts. BMC Bioinformatics, 8:221, 2007. > > > > I am certainly not the expert on this board but if you start to get > > specific errors (on your data analysis) after you read through the > > vignette and worked with the example data then post them and I will > > do my best to help out. > > > > noah > > > > Hello Noah, > > > > Thanks for the suggestions. Do you have a protocol or something for > > Starr or Ringo? I am starting from .pair, .ndf, .pos and .gff (for > > the nimblegen refseq mouse genome) nimblegen files. I would really > > appreciate it if you would share your protocol/s. > > > > Thanks so much, > > Som. > > > > --- > Joern Toedling > Institut Curie -- U900 > 26 rue d'Ulm, 75005 Paris, FRANCE > Tel. +33 (0)156246927 > > _______________________________________________ > Bioconductor mailing list > Bioconductor@stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor _________________________________________________________________ [[alternative HTML version deleted]]
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Hi Som, On Sun, 7 Mar 2010 15:56:15 -0500, somnath bandyopadhyay wrote > Hello Joern, > ? > I am having some trouble with the mapping of the reporters to the genomic positions. there are many ways to map the reporter sequences to the genome and the one using Exonerate that is mentioned in the tutorial is just one of them, so you could use an alternative one that you are more familiar with. For example, using the Biostrings function "matchPDict", you can even do this in R now. > ? > 1. I have downloaded the ccTutorial and have takena look at the exonerateData folder. I was wondering how I could create a .fsa file like RenMM5TilingProbe-Sequences.fsa from my Nimlegen .ndf file for the sequences for all the reporters on my 385k chip? These sequences are one of the columns of the ndf file (the sixth, I think). Also unique identifiers for each reporter are given in another column of that file. So you need to extract these two columns and write them out into a Fasta-file. You can read in the file into R using "read.delim" and then use the function "cat" to export just two of the columns. The package Ringo also contains a Perl script "extractProbeSequenceFasta.pl" in its scripts directory which performs the same task. > ? > 2. I have the .sh and .pl files in the exonerateData folder.. Once I have my .fsa file from above, what exactly do I need to run to create the "allChromExonerateOut..txt" file?Do all the files ...?? .fsa, .sh and the .pl have to be in the current working directory? Basically, you need to modify the .sh file to change the paths such that the work for you system. The Perl script in there is just for combining the multiple output files from Exonerate into one file. For details on the Exonerate parameters, please read the manual that comes with Exonerate. And again, if you are not happy with Exonerate, you also use another tool for this step. Regards, Joern --- Joern Toedling Institut Curie -- U900 26 rue d'Ulm, 75005 Paris, FRANCE Tel. +33 (0)156246927
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Hello Joern, Thanks for all the suggestions. In my experiment, I had 3 replicates for WT and 3 replicates for knockouts and each had respective inputs. Could you please suggest me a way to use the replicate information? The examples you had dinot have replicates in them. Any suggestions would be greatly appreciated. Thanks, Som. > From: Joern.Toedling@curie.fr > To: bioconductor@stat.math.ethz.ch; genome1976@hotmail.com > Subject: RE: [BioC] chip-chip data > Date: Mon, 8 Mar 2010 10:42:31 +0100 > > Hi Som, > > On Sun, 7 Mar 2010 15:56:15 -0500, somnath bandyopadhyay wrote > > Hello Joern, > > > > I am having some trouble with the mapping of the reporters to the genomic > positions. > > there are many ways to map the reporter sequences to the genome and the one > using Exonerate that is mentioned in the tutorial is just one of them, so you > could use an alternative one that you are more familiar with. > For example, using the Biostrings function "matchPDict", you can even do this > in R now. > > > > > 1. I have downloaded the ccTutorial and have takena look at the > exonerateData folder. I was wondering how I could create a .fsa file like > RenMM5TilingProbe-Sequences.fsa from my Nimlegen .ndf file for the sequences > for all the reporters on my 385k chip? > > These sequences are one of the columns of the ndf file (the sixth, I think). > Also unique identifiers for each reporter are given in another column of that > file. So you need to extract these two columns and write them out into a > Fasta-file. You can read in the file into R using "read.delim" and then use > the function "cat" to export just two of the columns. > The package Ringo also contains a Perl script "extractProbeSequenceFasta.pl" > in its scripts directory which performs the same task. > > > > > 2. I have the .sh and .pl files in the exonerateData folder.. Once I have my > .fsa file from above, what exactly do I need to run to create the > "allChromExonerateOut..txt" file?Do all the files ... .fsa, .sh and the .pl > have to be in the current working directory? > > Basically, you need to modify the .sh file to change the paths such that the > work for you system. The Perl script in there is just for combining the > multiple output files from Exonerate into one file. > > For details on the Exonerate parameters, please read the manual that comes > with Exonerate. And again, if you are not happy with Exonerate, you also use > another tool for this step. > > Regards, > Joern > > > --- > Joern Toedling > Institut Curie -- U900 > 26 rue d'Ulm, 75005 Paris, FRANCE > Tel. +33 (0)156246927 > _________________________________________________________________ Hotmail: Free, trusted and rich email service. [[alternative HTML version deleted]]
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Hi, they way I suggest to handle replicates is to combine them at the smoothing step. The function "computeRunningMedians" has an argument "combineReplicates" which you need to set to TRUE. And using the argument "modColumn" you specify which column of your data object's phenoData marks the class and thus indicates replicates. Alternatively, you could take medians or means over the reporter-wise values in each group but I think smoothing over replicates is preferable. Regards, Joern On Mon, 8 Mar 2010 17:08:18 -0500, somnath bandyopadhyay wrote > Hello Joern, > ? > Thanks for all the suggestions.?In my experiment, I had 3 replicates for WT and 3 replicates for knockouts and each had respective inputs.?Could you please suggest me a way to use the replicate information? The examples you had dinot have replicates in them. Any suggestions would be?greatly appreciated. > Thanks, > Som. > ? > --- Joern Toedling Institut Curie -- U900 26 rue d'Ulm, 75005 Paris, FRANCE Tel. +33 (0)156246927
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