Hi @chuang,
It depends on the length of those reads. If you are using V4, for example (which is around 290 nt in length total on average), 250 will give you a similar degree of resolution. But much longer reads or different marker gene sites may give better resolution.
Importantly, you will not be able to directly compare results (e.g., merge multiple datasets of different read length into a feature table containing the same features) unless if you trim those other reads to the exact same read length... otherwise the features will be slightly different and contain different feature IDs. You have a few options to compare:
- collapse on taxonomy and compare taxonomic composition
- use q2-fragment-insertion to compare different marker genes/read lengths.
- trim all reads to the same length prior to merging and downstream analysis.
See this thread for more discussion of those options. If you have follow-up questions on performing these comparisons, please open up a new forum post to make that question easier for other users to find. Thanks!