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Example script for calculating differential expression with Spark
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| #!/usr/bin/env python | |
| from pyspark import SparkContext | |
| SparkContext.setSystemProperty('spark.executor.memory', '2g') | |
| sc = SparkContext('local', 'Differential Expression Calculator') | |
| cond1 = sc.textFile('yeast/eXpress-66.txt,yeast/eXpress-67.txt,yeast/eXpress-68.txt') | |
| cond2 = sc.textFile('yeast/eXpress-69.txt,yeast/eXpress-70.txt,yeast/eXpress-71.txt') | |
| def title_filter(line): | |
| if line.startswith('bundle_id'): | |
| return False | |
| else: | |
| return True | |
| def map_fpkm(line): | |
| data = line.split('\t') | |
| target_id = data[1] | |
| fpkm = float(data[10]) | |
| return (target_id, fpkm) | |
| def diff_fpkm(pair): | |
| value1, value2 = pair | |
| if value2 == 0: | |
| return 0 | |
| return value1 / value2 | |
| def de_filter(pair): | |
| target_id, value = pair | |
| if value > 2 or value < 0.5: | |
| return True | |
| else: | |
| return False | |
| merged_cond1 = cond1.filter(title_filter) \ | |
| .map(map_fpkm) \ | |
| .aggregateByKey((0, 0), lambda x, y: (x[0] + y, x[1] + 1), lambda x, y: (x[0] + y[0], x[1] + y[1])) \ | |
| .mapValues(lambda x: x[0] / x[1]) | |
| merged_cond2 = cond2.filter(title_filter) \ | |
| .map(map_fpkm) \ | |
| .aggregateByKey((0, 0), lambda x, y: (x[0] + y, x[1] + 1), lambda x, y: (x[0] + y[0], x[1] + y[1])) \ | |
| .mapValues(lambda x: x[0] / x[1]) | |
| result = merged_cond1.join(merged_cond2).mapValues(diff_fpkm).filter(de_filter) | |
| result.saveAsTextFile('file:///share/de-result') |
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