Dear Ryan, Thank you for the advice. I am happy to do it both ways but these are large projects and also it would be difficult to quantify if the differences are small enough. Which is why I wanted to get the opinion of others in this list. And yes, you are right in that we need to include project and scan date into the adjustment if I batch correct first. Thanks. Regards, Adai On Tue, Aug 26, 2014 at 6:31 PM, Ryan <rct at="" thompsonclan.org=""> wrote: > Hi Adaikalavan, > > Why not try it both ways and see if it even makes a difference? If you get > the same results either way, then just do whatever is easier. > > If you do batch correction before removing other projects' samples, I > would think you would need to include the project identifier as a batch > effect in addition to the scan date or chip number, right? > > -Ryan > > > On 8/18/14, 5:11 AM, Adaikalavan Ramasamy wrote: > >> Dear all, >> >> I would like to appeal to the collective wisdom in this group on how best >> to solve this problem of normalization and batch correction. >> >> We are a service unit for an academic institute and we run several >> projects >> simultaneously. We use Illumina HT12-v4 microarrays which can take up to >> 12 >> different samples per chip. As we QC the data from one project, the RNA >> from failed samples can be repeated to include into chips from another >> project (rather than running partial chips to avoid wastage). Sometimes we >> include samples from other projects also. Here is a simple illustration >> >> Chip No ScanDate Contents >> 1 1st July *12 samples from project A* >> 2 1st July *8 samples from project A* + 4 from >> >> project B >> 3 1st August 12 samples from Project B >> 4 1st August *1 sample from Project A* + 5 samples from >> >> B + 6 from project C >> ... >> >> What is the best way to prepare the final data for *project A*? One option >> >> is to do the following: >> >> 1. Pool chips 1, 2 and 4 together. >> 2. Remove failed samples >> 3. Remove samples from other projects. >> 4. Normalize using NEQC from limma >> 5. Correct for scan date using COMBAT from sva. >> >> >> The other option we considered is to omit step 3 (i.e. use other samples >> for normalization and COMBAT) and subset at the end. >> >> I feel this second option allows for better estimation of batch effects >> (especially in chip 4). However, sometimes project A and B can be quite >> different (e.g. samples derived from different tissues) which might mess >> up >> the normalization especially if we want to compare project A to B >> directly. We >> also considered nec() followed by normalizeBetweenArrays with "Tquantile" >> but I felt it was too complicated. Anything else to try? >> >> Thank you. >> >> -- >> >> Adaikalavan Ramasamy >> >> Senior Leadership Fellow in Bioinformatics >> >> Head of the Transcriptomics Core Facility >> >> >> >> Email: adaikalavan.ramasamy at ndm.ox.ac.uk >> >> Office: 01865 287 710 >> >> Mob: 07906 308 465 >> >> http://www.jenner.ac.uk/transcriptomics-facility >> >> [[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 >> > > [[alternative HTML version deleted]]