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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.
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Remaining Steps
mkdir /project/gtl/data/raw/ALF1/rawdata/sample_fastq
cd /project/gtl/data/raw/ALF1/16S/rawdata/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/raw/ALF1/rawdata/sample_fastq/
Go to 16S Bioinformatics for ALF1 to see the remaining processing steps from section “Trim, merge and filter reads”
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Gregg Randolph : please see You run the nextflow script with: I tried this on pair of input files and one of the vsearch steps in the middle fails because the inputs are too small. But the I then ran it on all input. The nextflow script completes. Please have a look and see what you find and can figure out. , but one the vsearch steps appears to produce no output. It might be that some of the input files are genuinely too small. I can see that the trimming step is working. You can see this in Logs and other files for debugging from Nextflow will be typically be made automatically in |
Trim, merge and filter reads
In /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 /project/gtl/data/distribution/ALF1/ITS/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
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. I think a next step would be to try the commands with some sample data (an R1 and R2 fastq file) that we expect should work. Right now each job requests 1 hour from SLURM. I suspect this will be much smaller in the end and we can tailor it down. |