You may try looking into our collaborator's pipeline to at least get an idea of the steps, but if you're completely new to bioinformatics, I think there is a lot of ground to cover here.

https://github.com/junchaoshi/sports1.1

PANDORA-seq expands the repertoire of regulatory small RNAs... | Nat. Cell Biol

The accompanying paper focuses on a library construction method, but uses the pipeline, so you can get an idea of what types of questions they ask and answer. I'm not entirely sure how different small RNA analysis would be for mosquito.

I would suggest collecting a few more pipelines/workflows/papers and working through them to understand all the steps more deeply, focusing on the purpose of each step and why that step is important. Of course if you can find a pipeline that matches what you want, or at least a paper, then it's easier to follow that. But if not, then learning about each step can help you properly apply it to your specific question.

In general, you will want to trim reads to remove any readthrough of adapter sequence and then map the small RNA to the reference with minimal mismatches allowed (maybe 1 or 2, if not 0). This may be a problem if your mosquito species is not the same as the reference mosquito species, so I would check on that too.

Trimming reads is important because small RNAs have a higher occurrence of the sequencer reading through the small fragment and into the adapter on the other end (e.g. 3' ends of reads may be enriched with adapter sequence). Then, since reads are so small, multimapping can be more of an issue so it's good to have exact matches only. This includes no "soft clipping", which is a mode where an aligner will potentially ignore the ends of a read if they don't map exactly to a certain loci. Having exact matches and no soft clipping means adapter sequence in your reads can have a larger negative effect on alignments.