def main():
parser = argparse.ArgumentParser(
description=
"Compute a sample correlation matrix from a matrix of expression values. Including --probes_csv causes this to only compute correlation values for one probe per gene (the 'median' probe)."
)
parser.add_argument('-p', '--probes_csv', help="path to Probes.csv.")
parser.add_argument('expression_csv',
help="path to MicroarrayExpression.csv")
parser.add_argument('output_npz', help="output .npz file name")
args = parser.parse_args()
print "Reading Expression Values"
values = aibs.read_expression_values(args.expression_csv)
if args.probes_csv:
print "Filtering Probes"
probes, gene_probes = aibs.read_probes(args.probes_csv)
best_probes = find_best_probes(gene_probes, values)
best_probe_indices = np.array([p['index'] for p in best_probes])
values = values[best_probe_indices, :]
print values.shape
values = np.transpose(values)
print "Computing Sample Covariance"
cov = np.corrcoef(values)
print "Saving " + args.output_npz
np.savez(args.output_npz, cov)
def main():
parser = argparse.ArgumentParser(description="Compute a sample correlation matrix from a matrix of expression values. Including --probes_csv causes this to only compute correlation values for one probe per gene (the 'median' probe).")
parser.add_argument('-p','--probes_csv', help="path to Probes.csv.")
parser.add_argument('expression_csv', help="path to MicroarrayExpression.csv")
parser.add_argument('output_npz', help="output .npz file name")
args = parser.parse_args()
print "Reading Expression Values"
values = aibs.read_expression_values(args.expression_csv)
if args.probes_csv:
print "Filtering Probes"
probes, gene_probes = aibs.read_probes(args.probes_csv)
best_probes = find_best_probes(gene_probes, values)
best_probe_indices = np.array([ p['index'] for p in best_probes ])
values = values[best_probe_indices, :]
print values.shape
values = np.transpose(values)
print "Computing Sample Covariance"
cov = np.corrcoef(values)
print "Saving " + args.output_npz
np.savez(args.output_npz, cov)
def main():
parser = argparse.ArgumentParser(
description=
"Create a CSV file that lists one probe (the 'median' probe) for every gene."
)
parser.add_argument('probes_csv', help="path to Probes.csv")
parser.add_argument('expression_csv',
help="path to MicroarrayExpression.csv")
parser.add_argument('output_csv', help="output .csv file name")
args = parser.parse_args()
print "Reading Expression Values"
values = aibs.read_expression_values(args.expression_csv)
print "Reading Probes"
probes, gene_probes = aibs.read_probes(args.probes_csv)
print "Finding Best Probes"
out_probes = find_best_probes(gene_probes, values)
print "Writing " + args.output_csv
with open(args.output_csv, 'w') as outfile:
print >> outfile, "probe_id,array_index"
for probe in out_probes:
print >> outfile, ','.join(
[probe['probe_id'], str(probe['index'])])
def main():
parser = argparse.ArgumentParser(description="Create a CSV file that lists one probe (the 'median' probe) for every gene.")
parser.add_argument('probes_csv', help="path to Probes.csv")
parser.add_argument('expression_csv', help="path to MicroarrayExpression.csv")
parser.add_argument('output_csv', help="output .csv file name")
args = parser.parse_args()
print "Reading Expression Values"
values = aibs.read_expression_values(args.expression_csv)
print "Reading Probes"
probes, gene_probes = aibs.read_probes(args.probes_csv)
print "Finding Best Probes"
out_probes = find_best_probes(gene_probes, values)
print "Writing " + args.output_csv
with open(args.output_csv, 'w') as outfile:
print>>outfile, "probe_id,array_index"
for probe in out_probes:
print>>outfile, ','.join([probe['probe_id'], str(probe['index'])])
