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TEST.md

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Testing PARTIE

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.