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Hi all,
I have prepared a pool of 9 mouse ATAC-seq libraries for HiSeq sequencing, but our facility manager strongly recommended running them on MiSeq Nano as a quality check prior to the main run. Her point was to validate my pooling calculations, as it's difficult to accurately quantify the ATAC libraries.
I've now recevied my data back (~1 million 150 bp PE reads in total), checked the alignment rates (~75-80% of uniquely mapping reads, ~15% mapping more than once) and mitochondrial contamination (less than 5% as I've used FACS sorted nuclei). The pooling seems to be more or less OK as all the samples take around 10% of reads.
What I was wondering is whether there is any other information that I can extract out of this run to be confident in my ATAC libraries? I imagine that 700k reads for mouse genome is nowhere near being sufficient to call peaks and/or try to generate bigwig coverage files for visual inspection? Is there anything else I should be looking at prior to submission?
Many thanks in advance!
Olga
I have prepared a pool of 9 mouse ATAC-seq libraries for HiSeq sequencing, but our facility manager strongly recommended running them on MiSeq Nano as a quality check prior to the main run. Her point was to validate my pooling calculations, as it's difficult to accurately quantify the ATAC libraries.
I've now recevied my data back (~1 million 150 bp PE reads in total), checked the alignment rates (~75-80% of uniquely mapping reads, ~15% mapping more than once) and mitochondrial contamination (less than 5% as I've used FACS sorted nuclei). The pooling seems to be more or less OK as all the samples take around 10% of reads.
What I was wondering is whether there is any other information that I can extract out of this run to be confident in my ATAC libraries? I imagine that 700k reads for mouse genome is nowhere near being sufficient to call peaks and/or try to generate bigwig coverage files for visual inspection? Is there anything else I should be looking at prior to submission?
Many thanks in advance!
Olga