Mercurial > repos > mvdbeek > plot_correlation_matrix
diff plot_corr.py @ 0:0cee38fb62af draft
planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/plot_correlation_matrix commit 8451e17775c0ffcd7fa63ef65081f442bef91496
| author | mvdbeek |
|---|---|
| date | Fri, 27 Apr 2018 09:48:24 -0400 |
| parents | |
| children | e9268619b503 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/plot_corr.py Fri Apr 27 09:48:24 2018 -0400 @@ -0,0 +1,51 @@ +import os +import click +import matplotlib +matplotlib.use('tkagg') + +import pandas as pd # noqa: E402 +import seaborn as sns # noqa: E402 + + +def get_dataframe(files, labels, column, skiprows=1, sep='\t'): + d = {} + for file, label in zip(files, labels): + d[label] = pd.read_csv(file, usecols=[column], sep=sep, skiprows=skiprows, header=None, squeeze=True) + return pd.DataFrame.from_dict(d) + + +def plot_correlation(df, plot_path=None, method='pearson', correlation_matrix_path=None, figsize=(12, 12)): + corr = df.corr(method=method) + if correlation_matrix_path: + corr.to_csv(correlation_matrix_path, sep="\t") + if plot_path: + g = sns.clustermap(corr, annot=True, method="centroid", figsize=figsize, cbar_kws={'label': "%s correlation" % method}) + g.fig.suptitle("Cluster based on %s correlation for all samples" % method) + g.savefig(plot_path, bbox_inches='tight') + + +@click.command() +@click.argument("files", type=click.Path(exists=True), nargs=-1, required=True) +@click.option("-c", "--column", help="Use this numeric column to calculate correlation across files", default=1, required=True) +@click.option("--labels", help="File containing a list of labels, one label per line. Must match number of files", type=click.Path(exists=True), required=False) +@click.option("--plot_path", help="Write correlation plot to this path", type=click.Path(exists=False), required=False) +@click.option("--correlation_matrix_path", help="Write correlation plot to this path", type=click.Path(exists=False), required=False) +@click.option("--method", help="Use this method for calculating the correlation", required=False, type=click.Choice(['pearson', 'spearman', 'kendall'])) +@click.option("--skiprows", help="Skip this number of rows", required=False, default=0) +@click.option("--sep", help="Use this field separator when reading files", required=False, default="\t") +def main(files, column, labels=None, method="pearson", skiprows=1, plot_path=None, correlation_matrix_path=None, figsize=(12, 12), sep='\t'): + """Plot heatmap of pearson correlation and/or write matrix of pearson correlation values.""" + if labels: + labels = [l.strip() for l in open(labels) if l.strip()] + assert len(labels) == len(files), "Got %d files for plotting, but %d labels. Label and file length must be equal" % (len(files), len(labels)) + if not labels: + labels = [os.path.basename(f) for f in files] + if column != -1: + # Adjust for 0-based column selection + column -= 1 + df = get_dataframe(files, labels, column=column, skiprows=skiprows, sep=sep) + plot_correlation(df, plot_path=plot_path, correlation_matrix_path=correlation_matrix_path, figsize=figsize, method=method) + + +if __name__ == '__main__': + main()