Originally posted by Neuromancer
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If you import as single end then both ends of the pair will be shown as separate reads but there will be no connection between them in the internal data model so you can't switch between the two views within the same set of imported data.
One of the main trade offs which seqmonk makes in order to allow it to handle large datasets quickly is that it doesn't maintain links between alignment segments, either for paired reads, or for splice segments in spliced reads. For our internal quantitation of spliced data we use the relative length of each aligned segment to infer how many reads we should count when we're summing up the contribution of different spliced segments.
In your case as long as you're correcting for total read counts then it shouldn't matter too much that you have a mix of single and paired end data. In terms of counts the paired data will be somewhat similar to simply doubling a single end sample, and the global correction will normalise this away. If you want to more explicity correct for this then you could apply a manual correction to halve the counts for your paired end data (this is one of the quantitation options).
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