How to map/align fastq sequences to scrambled sequences and quantify them

Question

[Naresh D J]

Hi, I am analyzing the MPRA (massively parallel reporter assays) sequencing data for enhancers function validation. In this experiment, we have included around 1000 scrambled sequences as a control. I can align the fastq sequences to reference hg19 and quantify the enhancers activity but how to map/align the sequences to my scrambled sequences (controls in the experiment) and counting them. Any suggestions or help would be appreciated. Thank you.

Best Regards, Naresh D J

[cschu181]

What do you use to map to hg19? Assuming MPRA sequencing is RNAseq (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4540663/), I'd say you build a reference from your decoys and map to that with exactly the same tool.

[Naresh D J]

Hi, Thanks for your response. I was also thinking of the same, i.e. building my own reference and mapping. I am not sure on how to count the reads to mapping to those scrambled sequences. I have been using HTseq-count or featureCounts from subread package and not sure of these tools quantify my reads. Do you know any other tools for this purpose.

[GenoMax]

my scrambled sequences (controls in the experiment)

Are these sequences unrelated to human? If so you could add them as additional "chromosomes" to the standard hg19 build. Create a new index and map. You will also need to make a new GTF file that contains these "chromosomes" so you can count using featureCounts.

[Naresh D J]

Thanks. These sequences are randomly generated and not related to human. Yes, I will try your suggestion.