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In a sequence library’s rawdata/ directory (e.g., /project/gtl/data/raw/ALF1/ITS/rawdata/) I made run_aggregate.sh, to run aggregate_usearch_fastx_info.pl with a slurm job. Summaries are written to summary_sample_fastq.csv.

Stopped here on 8-31-22

Trim, merge and filter reads

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Remaining Steps

mkdir /project/gtl/data/raw/ALF1/rawdata/sample_fastq

cd /project/gtl/data/raw/ALF1/16S/rawdata/tfmergedreads , we used run_slurm_mergereads.plto crawl the project folders and sample files (created in the splitting step above) to merge read pairs, and filter based on base quality. This script conforms to the steps in https://microcollaborative.atlassian.net/wiki/spaces/MICLAB/pages/1123778569/Bioinformatics+v3.0?focusedCommentId=1280377080#comment-1280377080, including trimming primers, and joining unmerged reads. This writes a new set of fasta files for each sample and project, rather than fastq, to be used in subsequent steps. These files are found in the 16S/ and ITS/ folders in tfmergedreads/. For example, see contents of sample_fastq

cp -R 16S /project/gtl/data/raw/ALF1/rawdata/sample_fastq

cd /project/gtl/data/raw/ALF1/ITS/rawdata/sample_fastq

cp -R ITS /project/gtl/data/distributionraw/ALF1/ITSrawdata/rawdata/

Within each of these directories are files for the trimmed, merged, and filtered reads, in subfolders trimmed/, joined/, and unmerged/ (the last one is used as a working directory, should be empty; unmerged reads are filtered and joined and put in joined/ if they can be joined; the joined directory can be empty, if all unmerged reads were coligos for example).

Statistics on the initial number reads, the number of reads that merged, and the number of reads that remain after filtering are in filtermergestats.csv in each project folder. Please note that this will not include the number of reads that failed to merge, but we were able to join. This category is likely to include ITS sequences for which the amplicon was large enough that our 2x250bp reads could not span the whole length. The greater number removed in ITS (orange) in the plot below is consistent with this idea. For the full lane these summaries were concatenated in tfmergedreads/ with

cat */*/filtermergestats.csv > all_filtermergestats.csv

I used commands.R in that folder to make a plot of numbers of reads per sample (horizontal axis) and the number reads that were removed because they did not merge, or did meet quality criteria and were filtered out (vertical axis). Purple is for 16S and orange is for ITS. It might be interesting to do that plot for each of the projects in the library (TODO), and possibly to have marginal histograms (or put quantiles on the plots).

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Make OTU table

In /project/gtl/data/raw/ALF1/ITS/rawdata/otu, I ran run_slurm_mkotu.pl, which I modified to also pick up the joined reads (in addition the merged reads).

Make coligo table

In /project/gtl/data/raw/ALF1/ITS/coligoISD and /project/gtl/data/raw/ALF1/ITS/otu there are 16S and ITS directories for all projects. These contain a file named coligoISDtable.txt with counts of the coligos and the ISD found in the trimmed forward reads, per sample. The file run_slurm_mkcoligoISDtable.pl has the code that passes over all of the projects and uses vsearch for making the table.

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sample_fastq/

Go to 16S Bioinformatics for ALF1 to see the remaining processing steps from section “Trim, merge and filter reads”