Hi Bingbing, > Hi Heidi, > We downloaded the R-devel version, and all the functions and sample > fluidigm_sample.csv is included. Thank you! Glad you got it to work. > I have 2 samples of 96x96 fluidigm data. How can I display the layout of > the qPCR in the 2nd sample? In order to plot each array individually, you'll have to apply changeCtLayout to each of the 2 samples in your qPCRset individually. Otherwise you'll get an object of other dimensions that yu probably expect. E.g.: > # Locate test dta > exPath <- system.file("exData", package="HTqPCR") > exFiles <- "fluidigm_sample.csv" > > # Create qPCRset object > # Reading is same file twice, to pretend to have multiple samples > temp <- readCtData(c(exFiles, exFiles), path=exPath, n.features=48*48, flag=9, feature=5, type=6, Ct=7, position=1, skip=12, sep=",") > > # Re-format data, to contain n.features individual genes > all.raw <- changeCtLayout(temp, sample.order=rep(1:48, each=48)) > all.raw An object of class "qPCRset" Size: 48 features, 96 samples Feature types: Test Feature names: b actin b actin b actin ... Feature classes: Feature categories: OK Sample names: 1:fluidigm_sample 1:fluidigm_sample 2:fluidigm_sample ... On my two arrays I have a total of 96 samples (or 2x96 in your case for the different dimension of the Fluidigm array). Hence, the final qPCRset object will have 96 columns, since these are considered to be all the individual samples that will be tested for differential expression further downstream. In order to process each of your original Fluidigm cards individually, you can say: > # Process each sample individually > for (n in 1:n.samples(temp)) { + # Re-format from 1x2304 samples in input file into 48x48 as on array + raw <- changeCtLayout(temp[,n], sample.order=rep(1:48, each=48)) + # Plot + plotCtArray(raw, main=paste("Sample ", n, ": ", sampleNames(temp)[n])) + } You'd probably want to write that to a file, or open a new window for each plot, but that's the general approach. Please let me know if this doesn't work. \Heidi > > Here is my qPCRset >> temp <- readCtData(path="data/4HTqPCR", file=files$File, n.features = >> 96*96, flag=5, feature=3, type=4, Ct=2, position =1, sep = "\t") > >>temp > An object of class "qPCRset" > Size: 9216 features, 2 samples > Feature types: S01, S02, S03, S04, S05, S06, S07, S08, S09, S10, > S11, S12, S13, S14, S15, S16, S17, S18, S19, S20, S21, S22, S23, S24, S25, > S26, S27, S28, S29, S30, S31, S32, S33, S34, S35, S36, S37, S38, S39, S40, > S41, S42, S43, S44, S45, S46, S47, S48, S49, S50, S51, S52, S53, S54, S55, > S56, S57, S58, S59, S60, S61, S62, S63, S64, S65, S66, S67, S68, S69, S70, > S71, S72, S73, S74, S75, S76, S77, S78, S79, S80, S81, S82, S83, S84, S85, > S86, S87, S88, S89, S90, S91, S92, S93, S94, S95, S96 > Feature names: control1 control1 control2 ... > Feature classes: > Feature categories: Undetermined, OK > Sample names: sample1 sample2 NA ... > > >> raw <- changeCtLayout(temp, sample.order = rep(1:96, each = 96)) >> plotCtArray(raw) > >> raw2 <- changeCtLayout(temp, sample.order = rep(97:192, each = 96)) >> plotCtArray(raw2) > > but, plotCtArray(raw) gave the same layout as plotCtArray(raw2) > > > Thanks, > Bingbing > > > > > > > > > > ----- Original Message ----- > From: "Heidi Dvinge" <heidi at="" ebi.ac.uk=""> > To: "Bingbing Yuan" <byuan at="" wi.mit.edu=""> > Sent: Thursday, September 1, 2011 2:09:12 AM > Subject: Re: HTqPCR > > Hi Bingbing, > > what version of HTqPCR do you have? The Fluidigm-related functions are > relatively newly added. What's your output of sessionInfo() > > The current version is 1.7.3, c.f. > http://www.bioconductor.org/packages/devel/bioc/html/HTqPCR.html This is > technically for the R-devel version, i.e. 2.14, but I'm running it myself > on 2.13 without any issues so far. In that case you can't install it with > biocLite though, but will have to download it from the webpage above, and > install it manually. > > Cheers > \Heidi > > >> Hi Heidi, >> Thanks a lot for quick reply. >> In the package that we downloaded, there is no function of >> plotCtVariation >> and plotCtArray. Any idea? >> Thanks, >> Bingbing >> >> >> ----- Original Message ----- >> From: "Heidi Dvinge" <heidi at="" ebi.ac.uk=""> >> To: "Bingbing Yuan" <byuan at="" wi.mit.edu=""> >> Sent: Wednesday, August 31, 2011 1:52:28 PM >> Subject: Re: HTqPCR >> >> Hi Bingbing, >> >> my apologies, the file should be attached here. I'll make sure it's >> added >> to future HTqPCR releases. >> >> Best wishes >> \Heidi >> >>> Dear Heidi, >>> We downloaded the HTqPCR ( Release 2.8 ) from bioconductor this week, >>> and >>> fluidigm_sample.csv is not in the HTqPCR/exData/ folder. Could you >>> direct >>> me or send me this example file? >>> Thanks, >>> Bingbing >>> >>> >>> -- >>> Bingbing Yuan M.D. Ph.D. >>> Bioinformatics Scientist >>> Whitehead Institute for Biomedical Research >>> tel: 617 258 6109 >>> byuan at wi.mit.edu >>> >> >> -- >> Bingbing Yuan M.D. Ph.D. >> Bioinformatics Scientist >> Whitehead Institute for Biomedical Research >> tel: 617 258 6109 >> byuan at wi.mit.edu >> > > > > -- > Bingbing Yuan M.D. Ph.D. > Bioinformatics Scientist > Whitehead Institute for Biomedical Research > tel: 617 258 6109 > byuan at wi.mit.edu >

Hi Bingbing > Hi Heidi, > After setting Ct values to NA with filterCategory for avoiding unreliable > or undetermined data in part of the analysis, I normalized data with > deltaCt method. The mean of each card is NA. I am confused because I > thought only non-NAs were used for calculating means. You're right, it was supposed to be that way. I just never use deltaCt myself, so didn't test it after filterCategory. I submitted a fix for this a couple of days ago, so it should now be in HTqPCR v. 1.7.4. I suggest you either updated to that version (download + install it manually unless you have R-devel), or wait with filterCategory until after you've done the normalisation. HTH \Heidi > Here is my code: > >>files <- read.delim("data/4HTqPCR/files.txt") >> files > File Treatment > 1 sample1.txt Control > 2 sample2.txt Treated > >>comb <- readCtData(files = files$File, path = "data/4HTqPCR", n.features >> = 96 *96, flag = 5, feature = 3, type = 6, position = 1, Ct = 2, sep = >> "\t") >> comb > An object of class "qPCRset" > Size: 9216 features, 2 samples > Feature types: sample1 > Feature names: control1 control1 control2 ... > Feature classes: > Feature categories: Undetermined, OK > Sample names: sample1 sample2 NA ... > > >> raw.cat <- setCategory(q = comb, flag=TRUE, groups = files$Treatment) > Categories after Ct.max and Ct.min filtering: > sample1 sample2 > OK 6518 6567 > Undetermined 2698 2647 > Unreliable 0 2 > Categories after standard deviation filtering: > sample1 sample2 > OK 6302 6341 > Undetermined 2698 2647 > Unreliable 216 228 > > # set NA >> comb.filtered <- filterCategoryraw.cat, na.categories = c("Unreliable", >> "Undetermined")) >> comb.filtered > An object of class "qPCRset" > Size: 9216 features, 2 samples > Feature types: sample1 > Feature names: control1 control1 control2 ... > Feature classes: > Feature categories: Undetermined, Unreliable, OK > Sample names: sample1 sample2 NA ... > > # normalization >> d.norm <- normalizeCtData(comb.filtered, norm = "deltaCt", deltaCt.genes >> = c("control1", "control2")) > Calculating deltaCt values > Using control gene(s): control1 control2 > Card 1: Mean=NA Stdev=1.96 > Card 2: Mean=NA Stdev=1.83 > > > Thanks, > Bingbing > > > ----- Original Message ----- > From: "Bingbing Yuan" <byuan at="" wi.mit.edu=""> > To: "Heidi Dvinge" <heidi at="" ebi.ac.uk=""> > Sent: Friday, September 2, 2011 10:00:34 AM > Subject: Re: HTqPCR > > Hi Heidi, > I got it. Thanks for the very clear explanation. > Bingbing > > > ----- Original Message ----- > From: "Heidi Dvinge" <heidi at="" ebi.ac.uk=""> > To: "Bingbing Yuan" <byuan at="" wi.mit.edu=""> > Cc: bioconductor at r-project.org > Sent: Friday, September 2, 2011 7:07:24 AM > Subject: Re: HTqPCR > > Hi Bingbing, > >> Hi Heidi, >> We downloaded the R-devel version, and all the functions and sample >> fluidigm_sample.csv is included. Thank you! > > Glad you got it to work. > >> I have 2 samples of 96x96 fluidigm data. How can I display the layout of >> the qPCR in the 2nd sample? > > In order to plot each array individually, you'll have to apply > changeCtLayout to each of the 2 samples in your qPCRset individually. > Otherwise you'll get an object of other dimensions that yu probably > expect. E.g.: > >> # Locate test dta >> exPath <- system.file("exData", package="HTqPCR") >> exFiles <- "fluidigm_sample.csv" >> >> # Create qPCRset object >> # Reading is same file twice, to pretend to have multiple samples >> temp <- readCtData(c(exFiles, exFiles), path=exPath, n.features=48*48, > flag=9, feature=5, type=6, Ct=7, position=1, skip=12, sep=",") >> >> # Re-format data, to contain n.features individual genes >> all.raw <- changeCtLayout(temp, sample.order=rep(1:48, each=48)) >> all.raw > An object of class "qPCRset" > Size: 48 features, 96 samples > Feature types: Test > Feature names: b actin b actin b actin ... > Feature classes: > Feature categories: OK > Sample names: 1:fluidigm_sample 1:fluidigm_sample 2:fluidigm_sample ... > > On my two arrays I have a total of 96 samples (or 2x96 in your case for > the different dimension of the Fluidigm array). Hence, the final qPCRset > object will have 96 columns, since these are considered to be all the > individual samples that will be tested for differential expression further > downstream. > > In order to process each of your original Fluidigm cards individually, you > can say: > >> # Process each sample individually >> for (n in 1:n.samples(temp)) { > + # Re-format from 1x2304 samples in input file into 48x48 as on array > + raw <- changeCtLayout(temp[,n], sample.order=rep(1:48, each=48)) > + # Plot > + plotCtArray(raw, main=paste("Sample ", n, ": ", sampleNames(temp)[n])) > + } > > You'd probably want to write that to a file, or open a new window for each > plot, but that's the general approach. > > Please let me know if this doesn't work. > \Heidi > > >> >> Here is my qPCRset >>> temp <- readCtData(path="data/4HTqPCR", file=files$File, n.features = >>> 96*96, flag=5, feature=3, type=4, Ct=2, position =1, sep = "\t") >> >>>temp >> An object of class "qPCRset" >> Size: 9216 features, 2 samples >> Feature types: S01, S02, S03, S04, S05, S06, S07, S08, S09, >> S10, >> S11, S12, S13, S14, S15, S16, S17, S18, S19, S20, S21, S22, S23, S24, >> S25, >> S26, S27, S28, S29, S30, S31, S32, S33, S34, S35, S36, S37, S38, S39, >> S40, >> S41, S42, S43, S44, S45, S46, S47, S48, S49, S50, S51, S52, S53, S54, >> S55, >> S56, S57, S58, S59, S60, S61, S62, S63, S64, S65, S66, S67, S68, S69, >> S70, >> S71, S72, S73, S74, S75, S76, S77, S78, S79, S80, S81, S82, S83, S84, >> S85, >> S86, S87, S88, S89, S90, S91, S92, S93, S94, S95, S96 >> Feature names: control1 control1 control2 ... >> Feature classes: >> Feature categories: Undetermined, OK >> Sample names: sample1 sample2 NA ... >> >> >>> raw <- changeCtLayout(temp, sample.order = rep(1:96, each = 96)) >>> plotCtArray(raw) >> >>> raw2 <- changeCtLayout(temp, sample.order = rep(97:192, each = 96)) >>> plotCtArray(raw2) >> >> but, plotCtArray(raw) gave the same layout as plotCtArray(raw2) >> >> >> Thanks, >> Bingbing >> >> >> >> >> >> >> >> >> >> > > -- > Bingbing Yuan M.D. Ph.D. > Bioinformatics Scientist > Whitehead Institute for Biomedical Research > tel: 617 258 6109 > byuan at wi.mit.edu >