def get_plotter():
from config import mnase_seq_path, pileup_path
from src.reference_data import all_orfs_TSS_PAS
all_orfs = all_orfs_TSS_PAS()
plotter = TyphoonPlotter(mnase_path=mnase_seq_path,
rna_seq_pileup_path=pileup_path,
orfs=all_orfs)
return plotter
def __init__(self):
self.all_orfs = all_orfs_TSS_PAS()
self.fimo = FIMO()
self.window = 80
self.window_2 = self.window/2
# plotting
self.bin_scale = 14.
self.im_scale = 7
self.tf_threshold = 0.1
self.fc_threshold = 1
self.datastore = ChromatinDataStore()
def entropy_examples():
all_orfs = all_orfs_TSS_PAS()
global plotter
if plotter is None:
plotter = get_plotter()
from src.entropy import plot_entropy_example
orf = get_orf('CLF1', all_orfs)
plot_entropy_example(plotter, orf, (-460, 40), "Low entropy")
plt.savefig('%s/low_entropy.pdf' % (misc_figures_dir), dpi=100)
from src.entropy import plot_entropy_example
orf = get_orf('HSP26', all_orfs)
plot_entropy_example(plotter, orf, (200, 700), "High entropy")
plt.savefig('%s/high_entropy.pdf' % (misc_figures_dir), dpi=100)
def plot_small_peaks(gene, all_peaks, plotter):
all_orfs = all_orfs_TSS_PAS()
orf_name = get_orf_name(gene)
orf = get_orf(orf_name, all_orfs)
span = orf.TSS - 1000, orf.TSS + 1000
plotter.set_span_chrom(span, orf.chr)
plotter.dpi = 100
fig, axs, tween_axs = plotter.plot()
for i in range(len(times)):
time = times[i]
ax = axs[i]
data = all_peaks[(all_peaks.cross_correlation > 0.05) &
(all_peaks.orf == orf.name) &
(all_peaks.time == time)]
ax.scatter(data.original_mid, data.cross_correlation+10.0)
def collect_small_peaks():
from src.small_peak_calling import call_orf_small_peaks
from src.timer import Timer
orfs = all_orfs_TSS_PAS()
timer = Timer()
all_peaks = pd.DataFrame()
for chrom in range(1, 17):
print("Chromosome %d" % chrom)
chr_orfs = orfs[orfs.chr == chrom]
# load relevant cross correlations
chrom_cross_correlation = pd.read_hdf(
'%s/cross_correlation_chr%d.h5.z' %
(cc_sense_chrom_dir, chrom))
small_cc = -1 * chrom_cross_correlation.loc['diff']
for idx, orf in chr_orfs.iterrows():
try:
peaks = call_orf_small_peaks(small_cc, orf)
except KeyError:
continue
all_peaks = all_peaks.append(peaks)
timer.print_time()
all_peaks = all_peaks.reset_index(drop=True)
all_peaks['name'] = all_peaks['orf'] + '_' + all_peaks['time'].astype(str) + '_' + \
all_peaks['chr'].astype(str) + '_' + all_peaks['original_mid'].astype(str)
all_peaks = all_peaks.set_index('name')
return all_peaks
def shift_plots():
from src.nucleosome_calling import plot_p123
from src.reference_data import read_sgd_orf_introns, read_sgd_orfs
from src.reference_data import read_park_TSS_PAS
from src.summary_plotter import SummaryPlotter
global plotter
orf_cc = pd.read_hdf(cross_corr_sense_path, 'cross_correlation')
all_orfs = all_orfs_TSS_PAS()
sum_plotter = SummaryPlotter(datastore, all_orfs, orf_cc)
if plotter is None:
plotter = get_plotter()
save_dir = '%s/shift' % OUTPUT_DIR
mkdirs_safe([save_dir])
shift_genes = ['RPS7A']
for gene_name in shift_genes:
fig = plot_p123(gene_name, orf_cc, plotter, sum_plotter, save_dir)
p1 = datastore.p1_shift[[120.0]]
p2 = datastore.p2_shift[[120.0]]
p3 = datastore.p3_shift[[120.0]]
p12 = p1.join(p2, lsuffix='_+1', rsuffix='_+2')
p23 = p2.join(p3, lsuffix='_+2', rsuffix='_+3')
from src.chromatin_summary_plots import plot_distribution
x = datastore.p1_shift[120]
y = datastore.transcript_rate_logfold.loc[x.index][120.0]
model = plot_distribution(x,
y,
'$\\Delta$ +1 nucleosome shift',
'$\log_2$ fold-change transcription rate',
title='+1 shift vs transcription, 0-120 min',
xlim=(-40, 40),
ylim=(-8, 8),
xstep=10,
ystep=2,
pearson=True,
s=10)
plt.savefig('%s/shift_+1_xrate.pdf' % save_dir, transparent=True)
x = datastore.p1_shift[120]
y = datastore.p2_shift[120]
model = plot_distribution(x,
y,
'$\\Delta$ +1 nucleosome shift',
'$\\Delta$ +2 nucleosome shift',
title='+1, +2 nucleosome shift\n0-120 min',
xlim=(-40, 40),
ylim=(-40, 40),
xstep=10,
ystep=10,
pearson=False,
s=10)
plt.savefig('%s/shift_p12.pdf' % save_dir, transparent=True)
import pandas as pd
from src.timer import Timer
from src.typhoon import TyphoonPlotter
from src import met4
from src.typhoon import draw_example_mnase_seq
from src.typhoon import draw_example_rna_seq
from src.typhoon import plot_example_cross, get_plotter
from src.gene_list import get_gene_list, get_paper_list
from src.datasets import read_orfs_data
from src.summary_plotter import SummaryPlotter
from src.chromatin_metrics_data import ChromatinDataStore
from src.utils import get_orf
from src.reference_data import all_orfs_TSS_PAS, read_sgd_orfs
from src.transformations import difference
all_orfs = all_orfs_TSS_PAS()
timer = Timer()
datastore = ChromatinDataStore()
genes = get_paper_list()
plotter = None
selected_genes = ['HSP26', 'RPS7A', 'CKB1']
def go_bar_plots():
from src.go_analysis import GOChromatinAnalysis
write_dir = "%s/go" % OUTPUT_DIR
save_path = '%s/disorg_terms.csv' % write_dir