NS5 Blank Analysis

GTLCON

Assign taxonomy

cd /project/microbiome/data/seq/cu_29april22novaseq5/otu/16S/GTLCON/
salloc --account=microbiome -t 0-08:00 --mem=500G

module load swset/2018.05  
module load 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 /project/microbiome/data_queue/seq/GtlAnalyses/GTLCON_16S_NS5.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 631 of 631 sequences (100.00%)

Convert into useful form:

cd /project/microbiome/data_queue/seq/GtlAnalyses/
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] }' GTLCON_16S_NS5.sintax > GTLCON_16S_NS5taxonomy.csv

AIR21

Assign taxonomy

cd /project/microbiome/data/seq/cu_29april22novaseq5/otu/16S/AIR21

vsearch --sintax zotus.fa --db /project/microbiome/users/grandol1/ref_db/gg_16s_13.5.fa -tabbedout /project/microbiome/data_queue/seq/GtlAnalyses/AIR21_16S_NS5.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 631 of 631 sequences (100.00%)

Convert into useful form:

ARG20

Assign taxonomy

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 631 of 631 sequences (100.00%)

Convert into useful form:

BSAGE21

Assign taxonomy

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 631 of 631 sequences (100.00%)

Convert into useful form:

DRAG21

Assign taxonomy

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 631 of 631 sequences (100.00%)

Convert into useful form:

LIBB19

Assign taxonomy

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 631 of 631 sequences (100.00%)

Convert into useful form:

MAWC21

Assign taxonomy

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 631 of 631 sequences (100.00%)

Convert into useful form:

MULFIRE22

Assign taxonomy

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 631 of 631 sequences (100.00%)

Convert into useful form:

OUTLVD

Assign taxonomy

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 631 of 631 sequences (100.00%)

Convert into useful form:

SM19FIRE

Assign taxonomy

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 631 of 631 sequences (100.00%)

Convert into useful form:

SM19HILL

Assign taxonomy

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 631 of 631 sequences (100.00%)