Metadata-Version: 2.1
Name: panphlan
Version: 3.0
Summary: PanPhlAn is a strain-level metagenomic profiling tool for identifying the gene composition and *in-vivo* transcriptional activity of individual strains in metagenomic samples. PanPhlAn’s ability for strain-tracking and functional analysis of unknown pathogens makes it an efficient tool for culture-free infectious outbreak epidemiology and microbial population studies.
Home-page: http://github.com/SegataLab/panphlan/
Author: Leonard Dubois
Author-email: leonard.dubois@unitn.it
License: UNKNOWN
Description: # README #
        
        ## PanPhlAn 3 - strain detection and characterization 
        
        #### Pangenome-based Phylogenomic Analysis
        
        PanPhlAn is a strain-level metagenomic profiling tool for identifying
        the gene composition of individual strains in metagenomic samples.
        PanPhlAn’s ability for strain-tracking and functional analysis of unknown
        pathogens makes it an efficient tool for culture-free microbial population studies.
        
        PanPhlAn is written in Python and covers the 4 main tasks:
        
        * `panphlan_download_pangenome.py`, to download pangenome files (fasta, BowTie2 indexes and general information) for over 3,000 species
        * `panphlan_map.py`, to profile each metagenomic sample by mapping it against the species of interest
        * `panphlan_profile.py`, to merge and process the mapping results in order to get the final gene presence/absence matrix
        * `panphlan_find_gene_grp.py`, organise OPTICS clustering to find some group of gene with similar profile and assess if they could be mobile elements in the genome. Also plot the presence/absence matrix as Heatmap. 
        
        PanPhlAn runs under Ubuntu/Linux and requires the following software tools to be installed on your system:
        
        * Bowtie2
        * Samtools
        * Python 3
        
        And the following Python libraries:
        
        * numpy
        * pandas
        * scipy
        * sklearn (only if using `panphlan_find_gene_grp.py`)  
        If visualizations are made, one also needs :
        * matplotlib
        * seaborn
        
        For any help see the wiki or the [bioBakery forum](https://forum.biobakery.org/)
        
        ----
        
        [PanPhlAn] is a project of the [Computational Metagenomics Lab at CIBIO](http://segatalab.cibio.unitn.it/), University of Trento, Italy
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
