Hi everyone,

I have one csv file that contains the delta Ct values for several samples (columns) and genes as row names. I have samples from different Groups, Grp A, Grp B and Grp C. My data columns look something like this. Samples in Group A and B start with baseline disease condition while Group C samples are healthy.

Gene  GrpA1_baseline GrpA1_flare GrpA2_baseline GrpA2_flare GrpB1_baseline GrpB2_baseline

          GrpC1.1_healthy   GrpC1.2_healthy  GrpC2.1_healthy   GrpC2.2_healthy

I have different conditions within Group A biological replicates (meaning samples), only baseline condition for Group B biological replicates, and I have 2 technical replicates for each sample in Group C. I was wondering how I could create a new qPCRset object using HTqPCR package in R. I understand that I could use the readCtData function but I am unsure of how to specify and tackle biological replicates and technical replicates or how to read all this in from one file.

The ultimate goal is for me to find differentially expressed genes between different groups (GrpA_flare vs GrpC_healthy) for example. As I am completely new to analyzing Ct values, any advice at all about how I could go about doing this would be greatly appreciated. Thank you.

As of now, my dataframe that contains delta Ct values look like this:

ID_REF GSM2437228 GSM2437229 GSM2437230 GSM2437231 GSM2437232 GSM2437233
    1   ABCA1   2.741219   2.822219   4.275552  5.6885521   4.581885  3.4185521
    2    ACP1   4.388677   2.662677   2.910011  3.7580108   2.712344  2.5180108

I have 347 genes under the column name ID_REF and 337 samples from Groups A,B and C. I tried the following to create a qPCR object:

> readCtData('gene_data.csv', n.data= 337, n.features = 99 , header = TRUE, column.info=list(feature=1, Ct=337))

 but I see the following error:

Error in `[.data.frame`(sample, , column.info[["Ct"]]) : 
  undefined columns selected
In addition: Warning message:
In .readCtPlain(readfile = readfile, header = header, n.features = n.features,  :
  347 gene names (rows) expected, got 347

It would seem that you're trying to read the RT-PCR data from GEO series GSE92776. It's easy to read this data into R, directly from the GEO website. I've explained to you how to that here: Performing differential gene analysis on RT PCR experimental data