phylogenetics/project.py
def compute_clusters(self, **kwargs):

        """
        Cluster sequences by similarity cutoff using cdhit. http://weizhongli-lab.org/cd-hit/

        Sequences are sorted from longest to shortest before running cd-hit,
        ensuring that the larger sequences always end up in the final output.

        Parameters
        ----------
        cutoff : float
            percent sequence identity cutoff (between 0 and 1.0) at which to
                place two sequences in the same cluster
        """

        print("Computing clusters...")
        output = "/1_clustering_output.csv"

        new_df = phylogenetics.tools.cdhit.run(self.data, **kwargs)
        self.data = new_df

        new_df.to_csv(self.project_dir + output)

        print("Writing clustering results to " + self.project_dir + output + "...Done.\n")

        Cluster sequences by similarity cutoff using cdhit. http://weizhongli-lab.org/cd-hit/

        Sequences are sorted from longest to shortest before running cd-hit,
        ensuring that the larger sequences always end up in the final output.

        Parameters
        ----------
        cutoff : float
            percent sequence identity cutoff (between 0 and 1.0) at which to
                place two sequences in the same cluster
        
Cluster sequences by similarity cutoff using cdhit.

Parameters

cutoff : float
percent sequence identity cutoff (between 0 and 1.0) at which to
place two sequences in the same cluster
Cluster sequences by similarity cutoff using cdhit . Parameters cutoff : float percent sequence identity cutoff ( between 0 and 1 . 0 ) at which to place two sequences in the same cluster
def compute_clusters(self, **kwargs):
        print("Computing clusters...")
        output = "/1_clustering_output.csv"
        new_df = phylogenetics.tools.cdhit.run(self.data, **kwargs)
        self.data = new_df
        new_df.to_csv(self.project_dir + output)
        print("Writing clustering results to " + self.project_dir + output + "...Done.\n")
def compute_clusters ( self , ** kwargs ) : print ( "Computing clusters..." ) output = "/1_clustering_output.csv" new_df = phylogenetics . tools . cdhit . run ( self . data , ** kwargs ) self . data = new_df new_df . to_csv ( self . project_dir + output ) print ( "Writing clustering results to " + self . project_dir + output + "...Done.\n" )
Cluster sequences by similarity cutoff using cdhit.
Cluster sequences by similarity cutoff using cdhit .
"""
        Cluster sequences by similarity cutoff using cdhit. http://weizhongli-lab.org/cd-hit/

        Sequences are sorted from longest to shortest before running cd-hit,
        ensuring that the larger sequences always end up in the final output.

        Parameters
        ----------
        cutoff : float
            percent sequence identity cutoff (between 0 and 1.0) at which to
                place two sequences in the same cluster
        """
self