def plot_correlated_genes(
            self,
            name,
            n_genes=5,
            number_of_features=1000,
            **kwargs):
        """Plots gene expression patterns correlated with the input gene.

        Parameters
        ----------
        name - string
            The name of the gene with respect to which correlated gene
            expression patterns will be displayed.

        n_genes - int, optional, default 5
            The number of top ranked correlated genes to display.

        **kwargs -
            All keyword arguments in 'show_gene_expression' and 'scatter'
            are eligible.
        """
        all_gene_names = np.array(list(self.adata.var_names))
        if((all_gene_names == name).sum() == 0):
            print(
                "Gene not found in the filtered dataset. Note that genes "
                "are case sensitive.")
            return
        sds = self.corr_bin_genes(
            input_gene=name,
            number_of_features=number_of_features)
        if (n_genes + 1 > sds.size):
            x = sds.size
        else:
            x = n_genes + 1

        for i in range(1, x):
            self.show_gene_expression(sds[i], **kwargs)
        return sds[1:]