![]() There are also more GC fluctuations in those first 10bps as well.Ģ. NB2: I have used FastQC to look at a sample of my data (around 198,000 seqs), I didn't find any overrpresented sequences but I did find increased 5-mer representation in the first 10 base pairs of my pairs (which I am assuming to be the 5' end?). This was expected in the experimental setup but makes me wonder if I have any adapters to begin with. NB1: Read length in 101bp as observed in FastQC. I am still trying to understand how Illumina TruSeq works but on principle, should the trimming be done at the 3' only, or also at the 5' end of the read? Or is it that only the Universal Adapter should be trimmed at the 5', and the indexed adapters at the 3'? Please kindly help me with the following:ġ. I have checked the indexed adapters and they are all exactly identical except at the 6bp barcode in the middle of the sequence. I have been provided with a Universal adapter and 5'-3' indexed adapters. The files have been demultiplexed, so I have a barcode per sample which matches a specific barcode in a corresponding indexed adapter. It is unknown which of the R1 and R2 represent the 'forward' or 'reverse' reads. The FASTQ files are pair-ended (so I have an R1.fastq and R2.fastq for each of my samples). The details of my RNA-seq data are as follows: I have read through some of the posts but they have gotten me more confused! I am new to the analysis of RNA-seq data, and I am confused regarding trimming of my adapters from the FASTQ files using cutadapt. Please accept my apologies if this has been posted elsewhere. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |