@@ -23,7 +23,7 @@ The algorithm will take into account the errors in the modelling phase, so this
- In the trimming procedure, the `truncLen` cuts all the reads to an specific length and *removes* all reads being smaller. It is important then to know the average read length, since if you go too low with the trimming you will lose too much reads.
* In the pipeline of DADA2 there is a quality profile, you should be aware of it in deciding where to cut.
*
* For each run the trimming point is different, so if you are working on multiple runs each of them have to be processed separatedly and then joined together with `mergeSequenceTables`.
* You should have an analysis of the FASTQs. The av. length, the avg quality for each sample, and so on. Many of the problems with recovering most of the reads
