Run PCA and calculate the cumulative fraction of variance
    Args:
        Y: phenotype values
        standardize: if True, phenotypes are standardized
    Returns:
        var: cumulative distribution of variance explained

def PC_varExplained(Y,standardized=True):
    """
    Run PCA and calculate the cumulative fraction of variance
    Args:
        Y: phenotype values
        standardize: if True, phenotypes are standardized
    Returns:
        var: cumulative distribution of variance explained
    """
    # figuring out the number of latent factors
    if standardized:
        Y-=Y.mean(0)
        Y/=Y.std(0)
    covY = sp.cov(Y)
    S,U = linalg.eigh(covY+1e-6*sp.eye(covY.shape[0]))
    S = S[::-1]
    rv = np.array([S[0:i].sum() for i in range(1,S.shape[0])])
    rv/= S.sum()
    return rv