I have a collection samples spanning 3 different studies. I am performing differential abundance to identify the OTUs which are significant in seawater vs membranes.
With the entire collection, I can easily do
differential_abundance.py studies.biom -o diff_otus.txt -a DESeq2_nbinom \
-m source_type.map -c SourceType \
-x Membrane -y Seawater -d
I also want to perform differential abundance for each study individually.
Can I just add a new column into my mapping file called SourceStudy
to discriminate the study and the source type at the same time?
Will the results from DESeq2 from running the following be meaningful?
differential_abundance.py studies.biom -o diff_otus_s1.txt -a DESeq2_nbinom \
-m source_type.map -c SourceStudy \
-x S1Membrane -y S1Seawater -d
differential_abundance.py studies.biom -o diff_otus_s2.txt -a DESeq2_nbinom \
-m source_type.map -c SourceStudy \
-x S2Membrane -y S2Seawater -d
differential_abundance.py studies.biom -o diff_otus_s3.txt -a DESeq2_nbinom \
-m source_type.map -c SourceStudy \
-x S3Membrane -y S3Seawater -d
Should I instead split the BIOM table into individual studies and then perform differential abundance like the following?
differential_abundance.py study1.biom -o diff_otus_s1.txt -a DESeq2_nbinom \
-m source_type.map -c SourceType \
-x Membrane -y Seawater -d
differential_abundance.py study2.biom -o diff_otus_s2.txt -a DESeq2_nbinom \
-m source_type.map -c SourceType \
-x Membrane -y Seawater -d
differential_abundance.py study3.biom -o diff_otus_s3.txt -a DESeq2_nbinom \
-m source_type.map -c SourceType \
-x Membrane -y Seawater -d
Thanks for letting me know, I should have tried the QIIME forums first. Thanks anyway