for median in bp['medians']:
median.set(color='#b2df8a', linewidth=2)
## change the style of fliers and their fill
for flier in bp['fliers']:
flier.set(marker='o', color='#e7298a', alpha=0.5)
ax.set_xticklabels(["Forward Strand\nPromoter", "Reverse Strand\nPromoter", "eRNA\nUnannotated"], fontsize=20)
ax.grid()
plt.tight_layout()
plt.savefig("/Users/joazofeifa/Lab/Talks/2015/CSHL/Parameter_Comparison")
plt.show()
if __name__ == "__main__":
# f = lambda x: (1. / math.sqrt(2*math.pi*10) )*math.exp(-pow(x-50,2)/ (2*10) )
# g = lambda x: (1. / math.sqrt(2*math.pi*10) )*math.exp(-pow(x-60,2)/ (2*10) )
# print f(50)
# print g(50)
DIR ="/Users/joazofeifa/Lab/gro_seq_files/HCT116/EMG_out_files/"
DIR = "/Users/joazofeifa/Lab/gro_seq_files/Allen2014/EMG_out_files/"
REF = "/Users/joazofeifa/Lab/genome_files/RefSeqHG19.txt"
DMSO2_3 ="DMSO2_3-2_bidirectional_hits_intervals.bed"
DMSO2_3 = "DMSO2_3-3_bidirectional_hits_intervals.bed"
DMSO2_3_L,DMSO2_3_G = load.load_model_fits_bed_file(DIR+DMSO2_3)
R = refseq(REF)
run(DMSO2_3_L,R)
def run(root): display_fits = False parameters = False correlation = False correlation_BO = True if correlation_BO: DIR ="/Users/joazofeifa/Lab/gro_seq_files/HCT116/EMG_out_files/" DMSO1hr101911 ="DMSO1hr101911_model_fits/EMG-4_bidirectional_hits_intervals.bed" DMSO1027 ="DMSO1027_1212_model_fits/EMG-3_bidirectional_hits_intervals.bed" Ma6_NoIndex ="Ma6_NoIndex_L008_R1_001/EMG-6_bidirectional_hits_intervals.bed" DMSO2_3 ="Allen2014_DMSO2_3-2_bidirectional_hits_intervals.bed" Nutlin2_3 = "Nutlin2_3_model_fits/EMG-2_bidirectional_hits_intervals.bed" RefSeq = "/Users/joazofeifa/Lab/genome_files/RefSeqHG19.txt" ChIP_p53 = "/Users/joazofeifa/Lab/ACM_IEEE_Paper_analysis/files/bedFiles/Atleast7of7.bedbothstrands.bed_norefgene.bed" ChIP_p53 = "/Users/joazofeifa/Lab/nutlin_bidirectional_hits_intervals_091715.bed.count.bed.h.bed.namescoreDMSObi.resSig.txt.bed.txt" DMSO_forward = "/Users/joazofeifa/Lab/gro_seq_files/HCT116/bed_graph_files/DMSO2_3.pos.BedGraph" DMSO_reverse = "/Users/joazofeifa/Lab/gro_seq_files/HCT116/bed_graph_files/DMSO2_3.neg.BedGraph" Nutlin_forward = "/Users/joazofeifa/Lab/gro_seq_files/HCT116/bed_graph_files/Nutlin2_3.sorted.pos.BedGraph" Nutlin_reverse = "/Users/joazofeifa/Lab/gro_seq_files/HCT116/bed_graph_files/Nutlin2_3.sorted.neg.BedGraph" # DMSO1hr101911_L,DMSO1hr101911_G = load.load_model_fits_bed_file(DIR+DMSO1hr101911) # DMSO1027_L,DMSO1027_G = load.load_model_fits_bed_file(DIR+DMSO1027) # Ma6_NoIndex_L,Ma6_NoIndex_G = load.load_model_fits_bed_file(DIR+Ma6_NoIndex) DMSO2_3_L,DMSO2_3_G = load.load_model_fits_bed_file(DIR+DMSO2_3) correlations.parameters_dist(DMSO2_3_L) #Nutlin2_3_L,Nutlin2_3_G = load.load_model_fits_bed_file(DIR+Nutlin2_3) # density_plots.insert_bedgraph(DMSO2_3_L,(DMSO_forward,DMSO_reverse )) # density_plots.insert_bedgraph(Nutlin2_3_L,(Nutlin_forward,Nutlin_reverse )) # overlaps = correlations.match_UP(Ma6_NoIndex_L, DMSO2_3_L) # density_plots.plot_density(overlaps) # correlations.p53_binding(Nutlin2_3_L, DMSO2_3_L, overlaps) # correlations.label_p53(overlaps, attr="lam", LOG=True ) # correlations.promoter_differences_test((DMSO2_3_L,Nutlin2_3_L)) # correlations.p53_differences_test((Nutlin2_3_L,)) # correlations.si_lam(overlaps) # correlations.run(overlaps, attr="si", LOG=False ) # correlations.run_all(overlaps) if correlation: DIR ="/Users/joazofeifa/Lab/gro_seq_files/HCT116/EMG_out_files/" DMSO1hr101911 ="DMSO1hr101911_model_fits/model_fits.txt" DMSO1027 ="DMSO1027_1212_model_fits/model_fits.txt" Ma6_NoIndex ="Ma6_NoIndex_L008_R1_001/model_fits.txt" DMSO2_3 ="DMSO2_3_model_fits/model_fits.txt" Nutlin2_3 = "Nutlin2_3_model_fits/model_fits.txt" DMSO1hr101911_L,DMSO1hr101911_G = load.load_model_fits_bed_file(DIR+DMSO1hr101911) DMSO1027_L,DMSO1027_G = load.load_model_fits_bed_file(DIR+DMSO1027) Ma6_NoIndex_L,Ma6_NoIndex_L = load.load_model_fits_bed_file(DIR+Ma6_NoIndex) DMSO2_3_L,DMSO2_3_G = load.load_model_fits_bed_file(DIR+DMSO2_3) Nutlin2_3_L,Nutlin2_3_G = load.load_model_fits_bed_file(DIR+Nutlin2_3) correlations.run(DMSO2_3_L,DMSO2_3_L,Ma6_NoIndex_L,Ma6_NoIndex_L ) if display_fits: out_dir = "/Users/joeyazo/Desktop/Lab/gro_seq_files/HCT116/EMG_out_files/" model_file = out_dir+"model_fits_out_all_4" data_file = out_dir+"test_file_2.tsv" intervals = load.EMG_out(model_file) load.insert_data(data_file, intervals) dmf.display(intervals,bins=300) if parameters: EMG_out_FILE = root + "gro_seq_files/HCT116/EMG_out_files/EMG_model_fits_all_0" parameters = False BIC_analysis = True #only supports loading one at a time fits = load.EMG_out(EMG_out_FILE) if parameters: lap.run(fits, spec=None, weight_thresh=0.1,retry_tresh=0, converged=True) if BIC_analysis: BIC.run(fits)
