The red Low Read II samples were renormalized via pooling and the new MC samples were added to that same pool at 1 ul per sample. This pool was then adjusted to 1nM. The pool of the repeated RMJan22 samples was also adjusted to 1 nM. 50 ul of Low Read was added to 100 ul RMJan22. However, when the LowRead pool was qPCRed, one replicate was much higher than the other 2. The 1:2 ratio might be off because of this. We are running an RNaseP plate to recheck the recalibration of the 7500 qPCR machine.
Assign reads and otus to samples:
/project/microbiome/data_queue/seq/LowReadII/rawdata salloc --account=microbiome -t 0-06:00 mkdir -p /gscratch/grandol1/loc_ad2/rawdata cd /gscratch/grandol1/loc_ad2/rawdata unpigz --to-stdout /project/microbiome/data_queue/seq/loc_ad2/rawdata/LRII-RMJAN22_S1_L001_R1_001.fastq.gz | split -l 1000000 -d --suffix-length=3 --additional-suffix=.fastq - LowReadII_R1_ ;unpigz --to-stdout /project/microbiome/data_queue/seq/loc_ad2/rawdata/LRII-RMJAN22_S1_L001_R2_001.fastq.gz | split -l 1000000 -d --suffix-length=3 --additional-suffix=.fastq - LowReadII_R2_ //project/microbiome/data_queue/seq/loc_ad2/rawdata/run_parse_count_onSplitInput.pl cd /project/microbiome/data_queue/seq/loc_ad2/rawdata ./run_splitFastq_fwd.sh ./run_splitFastq_rev.sh cd /project/microbiome/data_queue/seq/loc_ad2/rawdata ./run_aggregate.sh
Exploration of Data created so far:
From my understanding, Line 9 from above simply splits the raw data into equal sized files, but the total number of reads should remain constant.
cd /gscratch/grandol1/loc_ad2/rawdata
wc -l LowRead*
Should return 8x the number of paired end reads (2x for R1 and 4x for the structure of fastq files).
This returns: 21045424 total
Divided by 8: 2630678
Line 11 then reads through all of the split files and assigns each read to a sample (parsed), to PhiX or non target (phixOther), or a mid error (truemiderrors). The reads assigned to these should add up to the numbers above.
wc -l parsed*
Returns: 15371232
Divided by 8: 1921404 assigned to samples.
Assigned/Total (*100) = percent assigned: ~73%
The target for samples was 83% (Off target by 12%).
Things get more confusing with the phixOther and truemiderror files, because they do not appear to be true fastq files nor do they appear to be Fasta. So, I do not know how to count reads.
Blasting random lines from phixOther returns a mix of phiX and ‘uncultured bacterium 16S’. I see no way of disentangling this.
So, let us explore the results of lines 13 to 17. These should be found in /project/microbiome/data_queue/seq/loc_ad2/rawdata/sample_fastq/16S/locad2
and
/project/microbiome/data_queue/seq/loc_ad2/rawdata/sample_fastq/16S/LRII
For locad2:
wc -l locad2*
Returns: 4071280
The file formats appear the same as the “parsed*” files above.
Divided by 8: 508910
For LRII:
wc -l LRII*
Returns: 11299952
Divided by 8: 1412494
LRII + locad2: 1921404
Even if all the unassigned reads are from locad2, this does not fix the expected ration of 2lo:1LR.
[508910+(2630678-1921404)] = 1218184 total possible locad2 reads
cd /project/microbiome/data_queue/seq/loc_ad2/tfmergedreads
./run_slurm_mergereads.pl
cd /project/microbiome/data_queue/seq/LowReadII/otu
./run_slurm_mkotu.pl
Assign taxonomy
salloc --account=microbiome -t 0-02:00 --mem=500G module load swset/2018.05 gcc/7.3.0 module load vsearch/2.15.1 vsearch --sintax zotus.fa --db /project/microbiome/users/grandol1/ref_db/gg_16s_13.5.fa -tabbedout LRII.sintax -sintax_cutoff 0.8
Output:
Reading file /project/microbiome/users/grandol1/ref_db/gg_16s_13.5.fa 100%
1769520677 nt in 1262986 seqs, min 1111, max 2368, avg 1401
Counting k-mers 100%
Creating k-mer index 100%
Classifying sequences 100%
Classified 4038 of 4042 sequences (99.90%)
Convert into useful form:
awk -F "\t" '{OFS=","} NR==1 {print "OTU_ID","SEQS","SIZE","DOMAIN","KINGDOM","PHYLUM","CLASS","ORDER","FAMILY","GENUS","SPECIES"} {gsub(";", ","); gsub("centroid=", ""); gsub("seqs=", ""); gsub("size=", ""); match($4, /d:[^,]+/, d); match($4, /k:[^,]+/, k); match($4, /p:[^,]+/, p); match($4, /c:[^,]+/, c); match($4, /o:[^,]+/, o); match($4, /f:[^,]+/, f); match($4, /g:[^,]+/, g); match($4, /s:[^,]+/, s); print $1, d[0]=="" ? "NA" : d[0], k[0]=="" ? "NA" : k[0], p[0]=="" ? "NA" : p[0], c[0]=="" ? "NA" : c[0], o[0]=="" ? "NA" : o[0], f[0]=="" ? "NA" : f[0], g[0]=="" ? "NA" : g[0], s[0]=="" ? "NA" : s[0] }' LRII.sintax > LRIItaxonomy.csv