usage = 'usage: %prog [options] <diff1_file> <diff2_file>'

parser = OptionParser(usage)

parser.add_option('-s', dest='stat', default='test_stat')

parser.add_option('-g', dest='genes_gtf', default=None)

parser.add_option('-m', dest='min_fpkm', default=0, type='float')

parser.add_option('-o', dest='out_dir', default='.')

parser.add_option('-p', dest='pseudocount', default=0.125, type='float')

(options,args) = parser.parse_args()

if len(args) != 2:

parser.error('Must provide two diff files')

else:

diff1_file = args[0]

diff2_file = args[1]

gtf_genes = None

if options.genes_gtf:

gtf_genes = gff.gtf_gene_set(options.genes_gtf)

diff1_stats = cuffdiff.hash_stat(diff1_file, stat=options.stat, min_fpkm=options.min_fpkm, pseudocount=options.pseudocount, gene_set=gtf_genes)

diff1_sig = cuffdiff.hash_sig(diff1_file, gene_set=gtf_genes)

diff2_stats = cuffdiff.hash_stat(diff2_file, stat=options.stat, min_fpkm=options.min_fpkm, pseudocount=options.pseudocount, gene_set=gtf_genes)

diff2_sig = cuffdiff.hash_sig(diff2_file, gene_set=gtf_genes)

if not os.path.isdir(options.out_dir):

os.mkdir(options.out_dir)

for diff_key in diff1_stats:

sample1, sample2 = diff_key

gene_stats1 = diff1_stats[diff_key]

gene_sig1 = diff1_sig[diff_key]

gene_stats2 = diff2_stats[diff_key]

gene_sig2 = diff2_sig[diff_key]

report_out = open('%s/%s-%s_report.txt' % (options.out_dir,sample1,sample2), 'w')

# compare numbers of genes quantified

common_genes = set(gene_stats1.keys()) & set(gene_stats2.keys())

print >> report_out, 'Genes quantified'

print >> report_out, '%s\t%d' % (diff1_file,len(gene_stats1))

print >> report_out, '%s\t%d' % (diff2_file,len(gene_stats2))

print >> report_out, 'Common\t%d' % len(common_genes)

print >> report_out, ''

up1 = set([gene_id for gene_id in gene_sig1 if gene_sig1[gene_id]])

up2 = set([gene_id for gene_id in gene_sig2 if gene_sig2[gene_id]])

print >> report_out, 'Genes upregulated'

print >> report_out, '%s\t%d' % (diff1_file,len(up1))

print >> report_out, '%s\t%d' % (diff2_file,len(up2))

print >> report_out, 'Common\t%d' % len(up1 & up2)

print >> report_out, ''

down1 = set([gene_id for gene_id in gene_sig1 if not gene_sig1[gene_id]])

down2 = set([gene_id for gene_id in gene_sig2 if not gene_sig2[gene_id]])

print >> report_out, 'Genes downregulated'

print >> report_out, '%s\t%d' % (diff1_file,len(down1))

print >> report_out, '%s\t%d' % (diff2_file,len(down2))

print >> report_out, 'Common\t%d' % len(down1 & down2)

print >> report_out, ''

# scatter plot test stat

df = {'diff1':[], 'diff2':[]}

for gene_id in common_genes:

df['diff1'].append(gene_stats1[gene_id])

df['diff2'].append(gene_stats2[gene_id])

r_script = '%s/diff_diff_scatter.r' % os.environ['RDIR']

out_pdf = '%s/%s-%s_scatter.pdf' % (options.out_dir, sample1, sample2)

ggplot.plot(r_script, df, [out_pdf], df_file='%s.df'%out_pdf[:-4])

# compute correlation

cor, p = spearmanr(df['diff1'], df['diff2'])

print >> report_out, 'Spearman correlation: %f (%f)' % (cor,p)

cor, p = pearsonr(df['diff1'], df['diff2'])

print >> report_out, 'Pearson correlation: %f (%f)' % (cor,p)

report_out.close()

# plot test_stat versus test_stat difference

df = {'minus':[], 'avg':[]}

for gene_id in common_genes:

df['minus'].append(gene_stats1[gene_id] - gene_stats2[gene_id])

df['avg'].append(0.5*gene_stats1[gene_id] + 0.5*gene_stats2[gene_id])

r_script = '%s/diff_diff_ma.r' % os.environ['RDIR']

out_pdf = '%s/%s-%s_ma.pdf' % (options.out_dir, sample1, sample2)