docs: def gaussianize(Y):
      """
      Gaussianize X: [samples x phenotypes]
      - each phentoype is converted to ranks and transformed back to normal using the inverse CDF
      """
      N,P = Y.shape
  
      YY=toRanks(Y)
      quantiles=(sp.arange(N)+0.5)/N
      gauss = st.norm.isf(quantiles)
      Y_gauss=sp.zeros((N,P))
      for i in range(P):
          Y_gauss[:,i] = gauss[YY[:,i]]
      Y_gauss *= -1
      return Y_gauss