Good Morning,
I am brand new to qiime 2 and have spent a lot of time on the forum reading over posts to get familiar with problems I may run into. I have successfully imported by data and I am currently working on denoising using dada2. I received end-paired demultiplexed data which by the looks of it, barcodes and primers have already been removed.
@M00941:895:GW20022630:1:1103:11026:15185 1:N:0:CGCTCATT+TAATCTTA
GTGCAGACCAGCTGCCGCCCTGCCCGATGCTTCTCCTGGCAACCTGGAGCAGCCACCAGACAACATGGAGACCCTCTGTGCACCCCAGGTCTGTCCCCTGCCTCTTAACTCCACCACGGAAGCTGGGCACGTGCTTCCACACGCAGGGGCGCCGAGATCGGAAGAGCACACGTCTGAACTCCAGTCACCGCTCATTATCTCGTATGCCGTCTTCTGCTTGAAAAAAAAAAAAAAAATATATATCTAACAA
+
CBBCCFFFCFFCGGGGGGGGGGHHHGGGGGHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHGHHHHHHHHHHGGHHHHCGBFGHHGGGGGHHHHHHHHHHGHHHHHHHHHHHHHHHHHGGGGGHHHHGHHGGHHHGHHHHHHGGGGGGGGGGGGGFGGGHGGGGGGGGGGGGGGGGGGGGGGGGGGGGGFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFDFD-9-<----.:000000000000
my target region was the V3-V4 region of the 16S gene using forward primer 341F (CCTACGGGAGGCAGCAG) and 806R (GGACTACHVGGGTWTCTAAT).
These are my quality plots for my forward and reverse reads.
(I hope the image uploads, if not i apologize. I was having some issues)
From reading a lot of different posts on the forum, it seems many people had the same issue I am having which is determining proper trim/trunc parameters for denosing. From what I understand p-trunc-len-f and p-trunc-len-r are based on the where the quality score begins to drop off. For mine, I am thinking --trunc-len-f 240 and --trunc-len-f 220? However, from what I've read I have to make sure the trunc paramters leave enough overlap for joining pairs which, depsite reading several posts, I can not understand how to determine that there will be sufficient overlap (~20 nt?). Since barcodes and primers have been removed would my p-trim values be zero?
thank you in advance for any help. I went through many tutorials before getting my data to get familiar with qiime2 but doing it on my own now it feels all brand new. I hope my quality plots upload properly.
