Hello, I have a project ~ 100 samples and sequenced twice (16S rRNA PE MiSeq) because some samples didn’t work during the first time sequencing. Let’s say the first time 30 samples didn’t work and I need to sequence these 30 samples again.
What I need to do is filter 30 samples out from the 1st sequencing data and merge the 2nd sequence data (30 samples) together with the filtered data.
I just switched from QIIME1 to QIIME2. This is what I do in QIIME 1. Since demux and QC are one-step, I will demultiplex the fastq data. I got good quality fasta data. So, it’s very easy to filter the unwanted sequences from fasta file and merge with the 2nd time good sequencing data in a new fasta file. Then, start building OTU table with new fasta file.
However, I checked the information here “https://docs.qiime2.org/2018.4/tutorials/filtering/”. It seems to me that I can’t filter from very beginning. Most of filtering starts after build a feature table, which is equivalent to an OTU table. If I follow the example, I have to build two feature tables based on two batches of sequencing. Later, I filter and merge the feature tables
Here are my questions:
Would it be possible for me to do something as I did in QIIME 1. I filter those unwanted samples’ reads from very beginning and merge with 2nd sequencing reads. Use the total data to do the downstream analyses. In doing this, I don’t have to build 2 individual feature tables. – I think this would be a really simple workflow. If I can do this, which scripts I should use?
Any suggestions about the workflow and at which step I should start filter and merge.