Chris, Thanks for your kind comment! The following code snippets should do. FeatureIDs = annotatedPeak[!is.na(annotatedPeak$distancetoFeature) & abs(annotatedPeak$distancetoFeature<5000000),]$feature library(org.Hs.eg.db) EnrichedGO = GetEnrichedGO(featureIDs, orgAnn="org.Hs.eg.db", maxP=0.01, multiAdj=FALSE, minGOterm=10, multiAdjMethod="") Best regards, Julie On 1/20/11 3:13 PM, "Christopher Ricupero" <ricupero@eden.rutgers.edu> wrote: Hello Dr. Zhu, I have recently been introduced to your ChIPpeakAnno package and think it is great. However, I am having some difficulties when working with the RangedData dataset once it is convereted and then annotated. I followed your manuscript and exported the annotated Peak file into excel, but I would like to do something different. What I am trying to accomplish is to filter the annotated peak Ranged Data by either the “distancetoFeature” or “shortestDistance” variables. I am only interested in peaks that are very close to the promoter regions and TSS so I wanted to limit these distances by approx 5000 kb. After this , I would then run the GO analysis. Is this possible to select on this variable to get a subset of my annotated peaks before I run the enrichedGo function? Thank you, Chris Christopher Ricupero Graduate Fellow Rutgers Univeristy Piscataway, NJ 08854 [[alternative HTML version deleted]]

Chris, Please type helpis.na) in a R session to access the menu about is.na function. Please use & for and, | for or inside the [ ] for combining selection criteria. The online book at http://cran.r-project.org/doc/manuals/R-intro.pdf is a very useful resource, it helped me a lot when I started. FeatureIDs = annotatedPeak[!is.na(annotatedPeak$distancetoFeature) & abs(annotatedPeak$distancetoFeature<5000000) & annotatedPeak$ insideFeature %in% c("upstream" , "inside" , "overlapStart"),]$feature Best regards, Julie On 1/20/11 4:52 PM, "Christopher Ricupero" <ricupero@eden.rutgers.edu> wrote: Hi Julie Thanks for the quick reply. Could I potentially bother you one more time. If you could send me some info on how to manipulate the ranged data that would be great. This function did work, but I wanted to take it 1 step further: To take only (5000 upstream, inside, overlap) and limit to only (500 bp downstream) My questions are: 1. What is the [!is.na mean? 2. I would like to combine my arguments. Instead of taking just the absolute value of 50000000 in distance to feature. I would like to take 50000 distance to feature plus insideFeature : upstream, inside, overlapStart, etc.. but then only 500 bp downsteam. I am sure there is a way to do this, I am just unsure of the syntax and how to combine the arguments. Could I say something like : abs(annotatedPeak$distancetoFeature<5000000) and annotatedPeak$ insideFeature=”upstream”, “inside”, “overlapStart”)]? Thanks, Chris From: Zhu, Lihua (Julie) [mailto:Julie.Zhu@umassmed.edu] Sent: Thursday, January 20, 2011 3:36 PM To: Christopher Ricupero; Ou, Jianhong Cc: bioconductor@stat.math.ethz.ch Subject: Re: ChIPpeak Anno RangedData question Chris, Thanks for your kind comment! The following code snippets should do. FeatureIDs = annotatedPeak[!is.na(annotatedPeak$distancetoFeature) & abs(annotatedPeak$distancetoFeature<5000000),]$feature library(org.Hs.eg.db) EnrichedGO = GetEnrichedGO(featureIDs, orgAnn="org.Hs.eg.db", maxP=0.01, multiAdj=FALSE, minGOterm=10, multiAdjMethod="") Best regards, Julie On 1/20/11 3:13 PM, "Christopher Ricupero" <ricupero@eden.rutgers.edu> wrote: Hello Dr. Zhu, I have recently been introduced to your ChIPpeakAnno package and think it is great. However, I am having some difficulties when working with the RangedData dataset once it is convereted and then annotated. I followed your manuscript and exported the annotated Peak file into excel, but I would like to do something different. What I am trying to accomplish is to filter the annotated peak Ranged Data by either the “distancetoFeature” or “shortestDistance” variables. I am only interested in peaks that are very close to the promoter regions and TSS so I wanted to limit these distances by approx 5000 kb. After this , I would then run the GO analysis. Is this possible to select on this variable to get a subset of my annotated peaks before I run the enrichedGo function? Thank you, Chris Christopher Ricupero Graduate Fellow Rutgers Univeristy Piscataway, NJ 08854 [[alternative HTML version deleted]]