Now that you have installed PARTIE you should run some tests on it.

Here are some examples for you to work with.

Run partie with fasta or fastq files

perl partie.pl tests/16STest.fq 
perl partie.pl tests/16STest.fna 
perl partie.pl tests/phagesTest.fna 
perl partie.pl tests/phagesTest.fq  
perl partie.pl tests/prokaryote.fna 
perl partie.pl tests/prokaryote.fq

Run partie with an SRA ID

perl partie.pl ERR696648.sra
perl partie.pl ERR162903.sra

Run all the tests simultaneously

You can run all the tests and create a single output file. Notice that the noheader flag suppresses the output of the column labels. If you redirect this output to a file, you should get the same results as in tests/Example_partie_output.txt

perl partie.pl tests/16STest.fq
perl partie.pl -noheader tests/16STest.fna
perl partie.pl -noheader tests/phagesTest.fna
perl partie.pl -noheader tests/phagesTest.fq 
perl partie.pl -noheader tests/prokaryote.fna
perl partie.pl -noheader tests/prokaryote.fq
perl partie.pl -noheader ERR696648.sra
perl partie.pl -noheader ERR162903.sra
perl partie.pl -noheader SRR3939281.sra

Results

These are the numbers you should get out of partie for these examples.

sample_name	percent_unique_kmer	percent_16S	percent_phage	percent_Prokaryote
16STest.fq	14.39	100	0	100
16STest.fna	14.39	100	0	100
phagesTest.fna	99.98	0	100	50
phagesTest.fq	99.98	0	100	50
prokaryote.fna	100	0	0	100
prokaryote.fq	100	0	0	100
ERR696648.sra	71.72	0.03	0.01	3.49
ERR162903.sra	33.64	13.92	0.5	25.5
SRR3939281.sra	88.88	0.33	0.89	1.39

Classification

To use the classifier, you can run the Rscript:

Rscript RandomForest/PARTIE_Classification.R tests/Example_partie_output.txt

This will generate the following output:

Data	percent unique kmer	percent 16S	percent phage	percent Prokaryote	PARTIE Annotation
16STest.fq	14.39	100	0	100	AMPLICON
16STest.fna	14.39	100	0	100	AMPLICON
phagesTest.fna	99.98	0	100	50	OTHER
phagesTest.fq	99.98	0	100	50	OTHER
prokaryote.fna	100	0	0	100	WGS
prokaryote.fq	100	0	0	100	WGS
ERR696648.sra	71.72	0.03	0.01	3.49	WGS
ERR162903.sra*	33.64	13.92	0.5	25.5	AMPLICON
SRR3939281.sra	88.88	0.33	0.89	1.39	WGS

Note the additional column that includes the PARTIE classification.

*Example in which both WGS and amplicon sequencing is used. In this case the authors used viral metagenomics and 16S rRNA amplicon sequencing. We recommend examining the four calculated parameters as no partition approach will correctly classify this library.