Metadata-Version: 2.1
Name: assembly_stats
Version: 0.1
Summary: Calculates both scaffold and contig statistics (N50, L50, etc.) from a scaffold FASTA file.
Home-page: https://github.com/MikeTrizna/assembly_stats
Author: Mike Trizna
Author-email: triznam@si.edu
License: UNKNOWN
Description: # assembly_stats
        
        A Python script that takes a FASTA file as input and calculates both scaffold and contig statistics (N50, L50, etc.) from a scaffold FASTA file. It does this by breaking each scaffold wherever there is more than one N and then calculating statistics for both the scaffolds and contigs.
        
        This is a re-write of fasta_metadata_parser to speed up the old implementation, and -- most importantly -- to learn how to install Python scripts onto the Smithsonian HPC.
        
        
        ## Usage
        
        The only Python library that this script relies on is NumPy, but this is installed and set up in a conda environment on the HPC.
        
        ``` 
          # Load the HPC assembly_stats module, which activates a conda environment
          # with the appropriate versions of Python and NumPy installed.
        
          $ module load bioinformatics/assembly_stats
        
          # Now that the module is loaded, assembly_stats.py should be accessible directly
          # in your PATH.
        
          $ assembly_stats.py [genome_file.fasta]
        ```
        
        After calculating the statistics for the genome assembly, they will be printed out in JSON format.
        
        Next steps
        ----------
        
        * Add ability to save NumPy sequence length arrays for further visualization, since generating these are what takes the most time.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
