Hmm, ok. Cathy had made parametric Pearson the only option previously, and I was just going along with that

On Jul 9, 2013, at 2:51 PM, Greg Caporaso <notifications@github.com> wrote:

> In qiime/otu_category_significance.py:
> 
> >          if r:
> > -            result[OTU] = [r, prob, str(OTU_abundance_vals), str(category_vals)]
> > +            if corr_test == 'spearman':
> > +                result[OTU] = [r, nonparametric_p_val, \
> > +                     str(OTU_abundance_vals), str(category_vals)]
> > +            elif corr_test == 'pearson':
> > +                result[OTU] = [r, parametric_p_val, \
> I use non-parametric Pearson.
> 
> —
> Reply to this email directly or view it on GitHub.
>