Mon, 11/11/2013 at 1:57 PM
Customer is a professor at Stanford University, and he asks about a solution to process short-read data, each read consisting of several 20-40 nt scaffold sequences separated by shorter variable segments. The objective is to align millions of reads with the scaffold sequences and identify the shorter variable segments for ID purposes, in addition to visualizing the alignment results.
Mon, 11/11/2013 at 4:21 PM
AccuraScience LB: 1) What input do we have for the program other than the read sequences? 2) What levels of substitutions are allowed in the scaffold sequences? Are insertions/deletions allowed? 3) For visualization, we could either generate an image file or an html file for you to scroll up and down to see different regions of the alignment. Will this be adequate?
Mon, 11/11/2013 at 8:22 PM
Customer: 1) The input includes a .fasta or .fastq file with millions of reads, known scaffold sequences, and known sequences in the small segments. 2) 1-2 base substitution per 10 bases should be allowed, deletions etc should be allowed. 3) Yes.
Tue, 11/12/2013 at 12:14 PM
AccuraScience LB: Here is a strategy that we've come up with: we will align each scaffold sequence to the read sequence, using Smith-Waterman algorithm or Blast, then we will extract the small segments of sequences between the positions matching with neighboring scaffolds. We will then match these segments with the known list of segment sequences in the input, and get the best matches and generate the output.
Tue, 11/12/2013 at 2:02 PM
Customer: Yes, this is exactly correct/good.
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Note: LB stands for Lead Bioinformatician. An AccuraScience LB is a senior bioinformatics expert and leader of an AccuraScience data analysis team.
Disclaimer: This text was selected and edited based on genuine communications that took place between a customer and AccuraScience data analysis team at specified dates and times. The editing was made to protect the customer’s privacy and for brevity. The edited text has been reviewed and approved by the customer.