FW: Using HTqPCR for Fluidigm BioMark input data (48.48 array)
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@fletez-brant-christopher-nihvrc-c-5360
Last seen 9.6 years ago
Just following my own advice here. On 11/19/12 9:22 AM, "Fletez-Brant, Christopher (NIH/VRC) [C]" <christopher.fletez-brant at="" nih.gov=""> wrote: >Hi Jens, > >Sorry for taking so long to get back to you - I was out of town. A couple >of things: > >1) Please always use 'reply to all', as we use the Bioconductor mailing >list as a kind of knowledge repository for others. > >2) Fluidigm numbering and well number aligns in multiples of 12. That is, >Well01 = A01, Well13 = B01 etc. > >3) For calculating sample means, I have been doing that manually and then >creating a new qPCRset. Manual calculation has involved removing subject >ID information from sample Ids (I.e. The row named "BJ_fibroblast_well01" >becomes "BJ_fibroblast"), taking sample specific subsets and calculating >gene means for each of them. That looks something like this: > >samples <- gsub("BJ_fibroblast|RiPSC.HUF1", "\\1", sampleNames(myqPCRset)) > #remove sample-specific ID components >myqPCRset.names <- unique(samples) #get unique sample names; equivalent >to getting the number of sample types >inds <- lapply(myqPCRset.names, grep, x=sampleNames(myqPCRset)) #split >into groups >groups.myqPCRset <- lapply(inds, function(i) exprs(myqPCRset)[,i]) >myqPCRset.means <- matrix(ncol=length(groups.myqPCRset[[1]]), >nrow=length(groups.myqPCRset)) #data structure to save means in >for (i in 1:length(groups.myqPCRset)){ > if (length(inds[[i]]) > 1){ #only calculate the mean if there's >more than one in the group > myqPCRset.means[i,] <- apply(groups.myqPCRset[[i]], 1, mean) > } > else { > myqPCRset.means[i,] <- groups.myqPCRset[[i]] > } >} > > >I hope this is sufficient to get you started. Feel free to ask more >questions as needed. > >Kipper > > >________________________________________ >From: Jens Durruthy-Durruthy [jensdd at stanford.edu] >Sent: Tuesday, November 13, 2012 4:03 PM >To: Fletez-Brant, Christopher (NIH/VRC) [C] >Subject: Re: [BioC] Using HTqPCR for Fluidigm BioMark input data (48.48 >array) > >Hi Kipper, > >Thanks for your email and your help! I really appreciate it. I think I >have a fundamental problem in understanding how the data in my Fluidigm >.csv file are read into the qPCRset. I do see that all the features where >recognized in the right order. > >> featureNames(raw) > [1] "HSP90AB1" "CD13" "COL1A1" "PDGF3B" "CD90" "VIM" > [7] "BUB1" "CCNF" "CDC20" "CDKN1A" "LATS2" "MAD2L1" >[13] "RBL1" "BPTF" "CBX7" "DNMT1" "EED" "GLP" >[19] "G9A" "P300" "EZH2" "INO80C" "JARID2" "KDM3B" >[25] "MBD3" "MCRS1" "MLL2" "RING1B" "BRG1" "SNF2H" >[31] "HP1" "TAF1" "TET1" "THAP11" "WDR5" "PRMT5" >[37] "CDH1" "CDKN2A" "GRB2" "LEFTY1" "LEFTY2" "LMNB1" >[43] "MAPK1" "MAPK3" "P53" "WNT1" "PIK3CG" > > >But when I type in > >> sampleNames(raw) > [1] "Sample1" "Sample2" "Sample3" "Sample4" "Sample5" "Sample6" > [7] "Sample7" "Sample8" "Sample9" "Sample10" "Sample11" "Sample12" >[13] "Sample13" "Sample14" "Sample15" "Sample16" "Sample17" "Sample18" >[19] "Sample19" "Sample20" "Sample21" "Sample22" "Sample23" "Sample24" >[25] "Sample25" "Sample26" "Sample27" "Sample28" "Sample29" "Sample30" >[31] "Sample31" "Sample32" "Sample33" "Sample34" "Sample35" "Sample36" > > >I don?t know if Sample1 corresponds to inlet one of my Fluidigm chip. >Also, I loaded three different samples onto the chip with each sample >loaded in 6 biological replicates and 2 technical replicates. So the first >12 inlets are one sample (BJ fibroblasts), inlets 13-24 are the second >sample RiPSC.BJ) and inlets 25-36 are the third sample (RiPSC.HUF1). How >does HTqPCR know that I want the technical (and later biological) >replicates to be combined so that I end up having three samples with each >being represented by 6 biological replicates? > > >From what and how I ask you may notice that I'm really just at the >beginning of understanding R, HTqPCR and the coding language. Sorry for >bugging you about this but I'd appreciate any help. >Thanks much! > >Jens > >PS: I attached the .csv file Fluidigm gave me. There are two ways to >export the data. One HeatMap format and one Table format. I attached both. > > >On 11/13/12 5:42 AM, "Fletez-Brant, Christopher (IH/VRC) [C]" ><christopher.fletez-brant at="" nih.gov=""> wrote: > >>Jens, >> >>If your qPCRset recognizes that there are 47 features and 3 samples, then >>you should be able to perform downstream analyses. If you are having >>trouble modifying sample names, I have been storing sample names in a >>file, ordered as the actual samples are in the Fluidigm output file, then >>assigning sample names. That is, something like: >> >>Temp <- read.csv("sample.names.csv") >>sampleNames(raw) <- Temp >> >> >>Best, >>Kipper >> >>On 11/11/12 3:27 AM, "Jens Durruthy-Durruthy" <jensdd at="" stanford.edu=""> >>wrote: >> >>>Hi all, >>> >>>I'm fairly new to the HTqPCR package and to R. >>>I wanted to analyze my Ct values that I get from the BioMark output in >>>form >>>of a .cvs file. I managed to read my file in with: >>> >>>> raw<-readCtData(files="test2.csv",format="BioMark",n.features=47, >>>+ n.data=3,samples=samples) >>>Warning message: >>>In readCtData(files = "test2.csv", format = "BioMark", n.features = 47, >>>: >>> Not enough sample names provided; using Sample1, Sample2, ? Instead >>> >>>> show(raw) >>>An object of class "qPCRset" >>>Size: 47 features, 3 samples >>>Feature types: >>>Feature names: HSP90AB1 CD13 COL1A1 ... >>>Feature classes: >>>Feature categories: OK >>>Sample names: Sample1 Sample2 Sample3 ... >>> >>>I ran 3 samples (three different cell types), each in 6 biological and 2 >>>technical replicates (12 total) but I don't know how to modify or edit >>>my >>>qPCRset object in order to visualize them or perform downstream analysis >>>(PCA, clustering etc.). I read through the PDF "HTqPCR - high?throughput >>>qPCR analysis in R and Bioconductor" by Heidi Dvinge but couldn't find >>>an >>>answer to my specific problem (mainly because I'm fairly new to the >>>language >>>R I think). >>> >>>If anyone could help out I would greatly appreciate it. Let me know if I >>>need to provide additional information about the input .cvs file) >>> >>>Thanks! >>>Jens >>> >>>:: Jens Durruthy-Durruthy :: >>>:: Research Scholar :: >>>:: Reijo Pera Lab :: >>> >>>:: Stanford University School of Medicine :: >>>:: Institute for Stem Cell Biology & Regenerative Medicine :: >>>:: Lorry Lokey Stem Cell Research Building :: >>>:: 265 Campus Drive, Rm 3015 :: >>>:: Stanford, CA 94305 ? United States :: >>>:: Mail: durruthy at stanford.edu :: >>>:: Phone: +1-650-498-7303 :: >>>:: Fax: 650-725-6910 :: >>> >>> >>>This e-mail may contain confidential and/or privileged >>>i...{{dropped:12}} >>> >> >
Clustering HTqPCR Clustering HTqPCR • 1.6k views

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