Hi There, I am a newbie to Bioconductor. I am trying to get off the ground with regards to my analysis. My question is as follows. 1) I have a list of 1000-2000 SNP's which are associated with a set of few diseases (Hemochromatosis etc). 2) We would like to use Affy6.0 Chip to look for the presence of these SNPs experimentally. 3) Even before we use the chips, How do I verify that these SNP's are actually located on the Affy6.0 chip? 4) I am assuming I will need to write a small R script of some sorts which will obtain the list of my SNP's -> Compare it against a database which has the numbers of the all the SNP's on 6.0 chip and append into an empty list the ones which are present on the chip and ones that are not. 5) The problem is, I do not know which software package in bioconductor to start using with...There are well over 400 packages and I am confused as to which ones to start off with (Affy?, Oligo? Affyparser?). I understand this is extremely basic, but I would be glad for any information regarding a workflow I could adopt, and also any possible literature references. Thank you. Rama [[alternative HTML version deleted]]

Hi Rama, -- James W. MacDonald, M.S. Biostatistician Douglas Lab University of Michigan Department of Human Genetics 5912 Buhl 1241 E. Catherine St. Ann Arbor MI 48109-5618 734-615-7826 >>> quantrum75 <quantrum75 at="" yahoo.com=""> wrote: > Hi There, > I am a newbie to Bioconductor. I am trying to get off the ground with > regards to my analysis. My question is as follows. > > 1) I have a list of 1000-2000 SNP's which are associated with a set of few > diseases (Hemochromatosis etc). And what sort of data do you have? RSIDs? > > 2) We would like to use Affy6.0 Chip to look for the presence of these SNPs > experimentally. > > 3) Even before we use the chips, How do I verify that these SNP's are > actually located on the Affy6.0 chip? There are numerous ways to do this. You could for instance download the snpArrayAffy6 table from here http://genome.ucsc.edu/cgi-bin/hgTables?hgsid=183744723&clade=mammal&o rg=Human&db=hg18&hgta_group=allTables&hgta_track=hg18&hgta_table=snpAr rayAffy6&hgta_regionType=range&position=chr1%3A1-48&hgta_outputType=pr imaryTable&hgta_outFileName= and then import into R and then see what overlap you have. Or you could query it directly using RMySQL: > library(RMySQL) Loading required package: DBI > con <- dbConnect("MySQL", user="genome", host="genome- mysql.cse.ucsc.edu", dbname="hg18") > fakersids <- paste("rs", sample(1000:10000, 200), sep = "") > head(fakersids) [1] "rs7579" "rs2720" "rs4184" "rs9439" "rs3179" "rs4682" > sql <- paste("select name from snpArrayAffy6 where rsId in ('", paste(fakersids, collapse = "','"), "');", sep = "") > length(dbGetQuery(con, sql)[,1]) [1] 27 > dbGetQuery(con, sql) name 1 SNP_A-2276689 2 SNP_A-8607650 3 SNP_A-8288820 4 SNP_A-2077380 5 SNP_A-2122995 6 SNP_A-8336953 7 SNP_A-8364177 <snip> LOL. So there are 27 of my fake RSIDs on the Affy SNP6 chip. Best, Jim > > 4) I am assuming I will need to write a small R script of some sorts which > will obtain the list of my SNP's -> Compare it against a database which has the > numbers of the all the SNP's on 6.0 chip and append into an empty list the > ones which are present on the chip and ones that are not. > > 5) The problem is, I do not know which software package in bioconductor to > start using with...There are well over 400 packages and I am confused as to > which ones to start off with (Affy?, Oligo? Affyparser?). > > I understand this is extremely basic, but I would be glad for any > information regarding a workflow I could adopt, and also any possible > literature references. > Thank you. > Rama > > > > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor ********************************************************** Electronic Mail is not secure, may not be read every day, and should not be used for urgent or sensitive issues