Bio::Community::Alpha - Calculate the alpha diversity of a community
use Bio::Community::Alpha; my $alpha = Bio::Community::Alpha->new( -community => $community, -type => 'observed' ); my $richness = $alpha->get_alpha;
The Bio::Community::Alpha module calculates the alpha diversity within a community. The goal is to support many different alpha diversity metrics, but the only metric available at the moment is: richness.
For all these metrics, a higher value means that the community is more diverse.
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The rest of the documentation details each of the object methods. Internal methods are usually preceded with a _
Function: Create a new Bio::Community::Alpha object Usage : my $alpha = Bio::Community::Alpha->new( ... ); Args : -community : See community(). -type : See type(). Returns : a new Bio::Community::Alpha object
Function: Get or set the community to process. Usage : my $community = $alpha->community(); Args : A Bio::Community object Returns : A Bio::Community object
Function: Get or set the type of alpha diversity metric to measure. Usage : my $type = $alpha->type; Args : String for the desired type of alpha diversity ('observed' by default). Richness (or estimated number of species): * observed : C<S> * menhinick: C<S/sqrt(n)>, where C<n> is the total counts (observations). * margalef : C<(S-1)/ln(n)> * chao1 : Bias-corrected chao1 richness, C<S+n1*(n1-1)/(2*(n2+1))> where C<n1> and C<n2> are the number of singletons and doubletons, respectively. Particularly useful for data skewed toward the low-abundance species, e.g. microbial. Based on counts, not relative abundance. * ace : Abundance-based Coverage Estimator (ACE). Based on counts, not relative abundance. Evenness (or equitability): * buzas : Buzas & Gibson's (or Sheldon's) evenness, C<e^H/S>. Ranges from 0 to 1. * heip : Heip's evenness, C<(e^H-1)/(S-1)>. Ranges from 0 to 1. * shannon_e : Shannon's evenness, or the Shannon-Wiener index divided by the maximum diversity possible in the community. Ranges from 0 to 1. * simpson_e : Simpson's evenness, or the Simpson's Index of Diversity divided by the maximum diversity possible in the community. Ranges from 0 to 1. * brillouin_e: Brillouin's evenness, or the Brillouin's index divided by the maximum diversity possible in the community. Ranges from 0 to 1. * hill_e : Hill's C<E_2,1> evenness, i.e. Simpson's Reciprocal index divided by C<e^H>. * mcintosh_e : McIntosh's evenness. * camargo : Camargo's eveness. Ranges from 0 to 1. Indices (accounting for species abundance): * shannon : Shannon-Wiener index C<H>. Emphasizes richness. Ranges from 0 to infinity. * simpson : Simpson's Index of Diversity C<1-D>, where C<D> is Simpson's dominance index. C<1-D> is the probability that two individuals taken randomly are not from the same species. Emphasizes evenness. Ranges from 0 to 1. * simpson_r: Simpson's Reciprocal Index C<1/D>. Ranges from 1 to infinity. * brillouin: Brillouin's index, appropriate for small, completely censused communities. Based on counts, not relative abundance. * hill : Hill's C<N_inf> index, the inverse of the Berger-Parker dominance. Ranges from 1 to infinity. * mcintosh : McIntosh's index. Based on counts, not relative abundance. Dominance (B<not> diversity metrics since the higher their value, the lower the diversity): * simpson_d: Simpson's Dominance Index C<D>. Ranges from 0 to 1. * berger : Berger-Parker dominance, i.e. the proportion of the most abundant species. Ranges from 0 to 1. Returns : String for the desired type of alpha diversity.
Function: Calculate the alpha diversity of a community. Usage : my $metric = $alpha->get_alpha; Args : None Returns : A number for the alpha diversity measurement