'''
Created on Jan 11, 2013
@author: karmel
What do enhancers that are gaining methyl with KLA look like?
'''
from __future__ import division
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
from glasslab.utils.functions import nonzero
from collections import OrderedDict
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/HiC/'
dirpath = yzer.get_path(dirpath)
data_dirpath = yzer.get_filename(dirpath, 'enhancer_sets')
kla_col = 'kla_lfc'
tss_only = False
img_dirpath = yzer.get_and_create_path(
dirpath, 'novel_me2_sites', tss_only and 'genic' or 'all_interactions',
'ratio_10')
if False:
enhancers = yzer.import_file(
yzer.get_filename(data_dirpath,
'all_distal_enhancers_inc_me2.txt'))
'''
Created on Mar 4, 2013
@author: karmel
'''
from __future__ import division
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/NOD_BALBc/ThioMacs/Analysis_2013_02/'
dirpath_bmdc = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/NOD_BALBc/BMDCs/Analysis_2013_03/'
dirpath = yzer.get_path(dirpath)
dirpath_bmdc = yzer.get_path(dirpath_bmdc)
img_dirpath = yzer.get_and_create_path(dirpath, 'bmdc_vs_thiomac')
thio = yzer.import_file(
yzer.get_filename(dirpath, 'transcript_vectors.txt'))
bmdc = yzer.import_file(
yzer.get_filename(dirpath_bmdc, 'transcript_vectors.txt'))
sets = []
for data in (thio, bmdc):
data = data.fillna(0)
refseq = yzer.get_refseq(data)
# Remove low tag counts
#refseq = refseq[refseq['transcript_score'] >= 4]
'''
Created on Jul 11, 2012
@author: karmel
'''
from __future__ import division
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/Classes/Rotations/Finland_2012/GR_Project/'
dirpath = yzer.get_path(dirpath)
img_dirpath = yzer.get_and_create_path(dirpath, 'peak_scatterplots')
if True:
for main, compare, basal_cond in (('p65', 'GR', 'KLA'), ('GR', 'p65',
'Dex')):
data = yzer.import_file(
yzer.get_filename(dirpath, 'motifs', 'from_peaks',
'{0}_kla_dex_vectors.txt'.format(main)))
data = data.fillna(0)
data = data.groupby(['id', 'chr_name'], as_index=False).mean()
xcolname, ycolname = 'tag_count_2', 'tag_count' #'p65_kla_tag_count', 'p65_kla_dex_tag_count',
data = data[data[ycolname] >= 10]
cond_1 = (data['tag_count_3'] == 0)
cond_2 = (data['tag_count_3'] > 0) & (data['tag_count_3'] <
data['tag_count_4'])
cond_3 = (data['tag_count_3'] > 0) & (data['tag_count_3'] >=
'''
Created on Aug 25, 2013
@author: karmel
Plot supplementary figure showing Hah et al error rates
against MAX EDGE values when Vespucci is built without knowledge
of RefSeq boundaries.
'''
from __future__ import division
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/Glass Atlas/NAR_review_data/no_refseq'
dirpath = yzer.get_path(dirpath)
img_dirpath = yzer.get_and_create_path(dirpath, 'plots')
ax = yzer.set_up_plot()
title = 'Benchmarking without Foreknowledge of RefSeq'
yzer.add_title(title, ax)
yzer.add_axis_labels('MAX_EDGE value',
'Error rate defined by Hah et al. (%)')
max_edges = [100, 500, 1000, 4000, 5000, 5500, 6000, 10000]
error_rates = [
0.388551822833, 0.372390444765, 0.263807982126, 0.124663089396,
0.121784970634, 0.121807917409, 0.123263849815, 0.142530838464
]
error_pcts = [e * 100 for e in error_rates]
'''
Created on Oct 26, 2012
@author: karmel
'''
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
from matplotlib import pyplot
from glasslab.utils.functions import nonzero
from glasslab.dataanalysis.misc.gr_project_2012.v1.elongation import total_tags_per_run
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/GR_Analysis/enhancer_classification'
dirpath = yzer.get_path(dirpath)
consistent = False
img_dirpath = yzer.get_and_create_path(
dirpath, 'boxplots_by_expression', consistent and 'consistent'
or 'rep1')
data = yzer.import_file(
yzer.get_filename(dirpath, 'enhancers_with_nearest_gene.txt'))
data['ucsc_link_nod'] = data['ucsc_link_nod'].apply(
lambda s: s.replace('nod_balbc', 'gr_project_2012'))
draw_pies = True
min_tags = 30
ratio = 1.5
# Make sure we have dimethyl
data = data[data.filter(like='h3k4me2').max(axis=1) > min_tags]
data = data[data['minimal_distance'] >= 1000]
'''
Created on Mar 11, 2013
@author: karmel
Note: Made font.weight = bold and axes.titlesize = 24, font.size = 16 in matplotlibrc
'''
from __future__ import division
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
from glasslab.utils.functions import nonzero
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/Glass Atlas/Demo-data'
dirpath = yzer.get_path(dirpath)
img_dirpath = yzer.get_and_create_path(dirpath,
'refseq_to_homer/large_gap_500bp')
data = yzer.import_file(
yzer.get_filename(dirpath, 'refseq_tag_counts_500bp.txt'))
data['sum'] = nonzero(data['sum'].fillna(0))
homer_data = yzer.import_file(
yzer.get_filename(dirpath, 'RNA_GroSeq_CountsGenes.txt'))
homer_data['sequence_identifier'] = homer_data['Gene ID']
homer_data['homer_tag_count'] = nonzero(homer_data[
'ThioMac-GroSeq-notx-110513/ genes (Total: 12166480.0) normFactor 0.82']
.fillna(0))
homer_data = homer_data[['sequence_identifier', 'homer_tag_count']]
'''
Created on Nov 26, 2012
@author: karmel
Do the gene groups outlined in Ramirez-Carrozzi 2006 and 2009 correlate
with expression changes in Dex+KLA?
'''
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/GR_Analysis/cpg_island_promoters'
dirpath = yzer.get_path(dirpath)
for rep in (4, 3, 1):
img_dirpath = yzer.get_and_create_path(dirpath,
'boxplots_by_expression',
'genes_with_gr',
'rep{0}'.format(rep),
'transrepressed')
data = yzer.import_file(
yzer.get_filename(dirpath, 'transcript_vectors.txt'))
data['ucsc_link_nod'] = data['ucsc_link_nod'].apply(
lambda s: s.replace('nod_balbc', 'gr_project_2012'))
data = data.fillna(0)
data = data[(data['kla_{0}_lfc'.format(rep)] >= 1)
& (data['dex_over_kla_{0}_lfc'.format(rep)] <= -.58)]
'''
Created on Feb 12, 2013
@author: karmel
'''
from __future__ import division
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/NOD_BALBc/ThioMacs/Analysis_2013_02/'
dirpath = yzer.get_path(dirpath)
img_dirpath = yzer.get_and_create_path(dirpath, 'srf_binding')
data = yzer.import_file(
yzer.get_filename(dirpath, 'transcript_vectors.txt'))
data = data.fillna(0)
data = data[data[['nod_notx_1h_tag_count', 'balb_notx_1h_tag_count']].max(
axis=1) >= 10]
subsets = [
data,
data[(data['has_refseq'] == 1) & (data['transcript_score'] >= 4)],
data[(data['distal'] == 't') & (data['h3k4me2_tag_count'] > 10)]
]
# Add in nearest genes for enhancers
enh = subsets[2].copy()
nearest_genes = yzer.import_file(
'''
Created on Jan 11, 2013
@author: karmel
What do enhancers that are gaining methyl with KLA look like?
'''
from __future__ import division
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
from glasslab.utils.functions import nonzero
from collections import OrderedDict
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/HiC/'
dirpath = yzer.get_path(dirpath)
data_dirpath = yzer.get_filename(dirpath, 'enhancer_sets')
kla_col = 'kla_lfc'
tss_only = False
img_dirpath = yzer.get_and_create_path(
dirpath, 'interactions_by_kla_lfc', tss_only and 'genic'
or 'all_interactions', 'lfc_2')
# File generated in novel_me2_sites
enhancers = yzer.import_file(
yzer.get_filename(
data_dirpath,
'all_enhancers_with_me2_and_{0}interaction_stats.txt'.format(
'''
Created on May 2, 2013
@author: karmel
Note: Made font.weight = normal and axes.titlesize = 24 in matplotlibrc
'''
from __future__ import division
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
from glasslab.dataanalysis.misc.demoatlas.rpkm_to_score import PrettyAxisGrapher
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/Glass Atlas/NAR_review_data/Post-gene'
dirpath = yzer.get_path(dirpath)
img_dirpath = yzer.get_and_create_path(dirpath, 'scatterplots')
data = yzer.import_file(
yzer.get_filename(dirpath, 'post_gene_transcripts.txt'))
refseq = yzer.import_file(
yzer.get_filename(dirpath, 'all_expressed_refseq.txt'))
refseq_with_runoff = refseq[refseq['id'].isin(data['gene_id'])]
refseq_no_runoff = refseq[~refseq['id'].isin(data['gene_id'])]
if False:
print len(refseq_no_runoff)
print refseq_no_runoff.tail(100).to_string()
# Calculate length of runoff
data[
'length'] = data['transcription_end'] - data['transcription_start'] + 1
'''
Created on Jan 9, 2013
@author: karmel
Do novel interactions gain or lose me2?
'''
from __future__ import division
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
from glasslab.utils.functions import nonzero
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/HiC/'
dirpath = yzer.get_path(dirpath)
data_dirpath = yzer.get_filename(dirpath, 'enhancer_sets')
img_dirpath = yzer.get_and_create_path(dirpath,
'novel_interactions_kla_lfc',
'all_interactions')
interactions = yzer.import_file(
yzer.get_filename(
data_dirpath,
'transcript_pairs_enhancer_with_anything_with_me2_inc_me2_counts.txt'
))
interactions = interactions[interactions['count'] > 1]
all_transcripts = yzer.import_file(
yzer.get_filename(data_dirpath, 'transcript_vectors.txt'))
kla_col = 'kla_lfc'
'''
Created on Jan 9, 2013
@author: karmel
Do novel interactions gain or lose me2?
'''
from __future__ import division
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
from glasslab.utils.functions import nonzero
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/HiC/'
dirpath = yzer.get_path(dirpath)
data_dirpath = yzer.get_filename(dirpath, 'enhancer_sets')
img_dirpath = yzer.get_and_create_path(dirpath,
'novel_enhancer_me2_change',
'all_interactions')
interactions = yzer.import_file(
yzer.get_filename(
data_dirpath,
'transcript_pairs_enhancer_with_anything_with_me2_inc_me2_counts.txt'
))
interactions = interactions[interactions['count'] > 1]
interactions = interactions.fillna(0)
# Key on peak id, not enhancer id, which could be bidirectional
#interactions['id_2'] = interactions['h3k4me2_id']
'''
Created on Jan 2, 2013
@author: karmel
'''
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
import pandas
if __name__ == '__main__':
enhancer_counts = True # Are we looking at enhancer interactions (False) or counts (True)?
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/HiC/enhancers_by_gene_length'
dirpath = yzer.get_path(dirpath)
img_dirpath = yzer.get_and_create_path(dirpath, 'scatterplots')
counted = enhancer_counts and 'enhancer' or 'interaction'
# The first set has length with interaction counts;
# the second has length for all transcripts, even those without interactions.
# We want to merge such that we add the interaction-less genes with a count of 0.
data = yzer.import_file(yzer.get_filename(dirpath,'{0}_counts_by_refseq.txt'.format(counted)))
all_data = yzer.import_file(yzer.get_filename(dirpath,'refseq_all.txt'))
all_data = all_data[~all_data['id'].isin(data['id'])]
data = pandas.concat([data, all_data])
data = data.reset_index().fillna(0)
notx = data[data['sequencing_run_id'] == 765]
kla_30m = data[data['sequencing_run_id'] == 766]
'''
Created on Feb 12, 2013
@author: karmel
'''
from __future__ import division
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
from glasslab.utils.functions import nonzero
from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/CD4TCells/Oshea_enhancers/peak_overlaps'
dirpath = yzer.get_path(dirpath)
img_dirpath = yzer.get_and_create_path(dirpath, 'figures')
peak_pretty = 'p300'
peak = peak_pretty.lower()
th1 = yzer.import_file(
yzer.get_filename(dirpath,
'th1_with_th2_{0}.txt'.format(peak))).fillna(0)
th2 = yzer.import_file(
yzer.get_filename(dirpath,
'th2_with_th1_{0}.txt'.format(peak))).fillna(0)
# Filter out promoters
th1 = th1[th1['tss_id'] == 0]
th2 = th2[th2['tss_id'] == 0]
# Get venn-diagram sets
'''
Created on Oct 26, 2012
@author: karmel
'''
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
from matplotlib import pyplot
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/GR_Analysis/enhancer_classification'
dirpath = yzer.get_path(dirpath)
img_dirpath = yzer.get_and_create_path(dirpath, 'piecharts_for_genes_by_mechanism')
data = yzer.import_file(yzer.get_filename(dirpath, 'enhancers_with_nearest_gene.txt'))
data['ucsc_link_nod'] = data['ucsc_link_nod'].apply(lambda s: s.replace('nod_balbc','gr_project_2012'))
draw_pies = True
min_tags = 30
ratio = 1.5
# Make sure we have dimethyl
data = data[data.filter(like='h3k4me2').max(axis=1) > min_tags]
data = data[data['minimal_distance'] >= 1000]
#data = yzer.collapse_strands(data)
transcripts = yzer.import_file(yzer.get_filename(dirpath, 'transcript_vectors.txt'))
transcripts['nearest_refseq_transcript_id'] = transcripts['id']
# Join, keeping all transcripts
data = data.merge(transcripts, how='left', on='nearest_refseq_transcript_id', suffixes=['','_trans'])
'''
Created on Jan 3, 2013
@author: karmel
Plot gen-enhancer me2 LFC; do we see correlation?
'''
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
from glasslab.utils.functions import nonzero
import numpy
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/HiC/'
dirpath = yzer.get_path(dirpath)
data_dirpath = yzer.get_filename(dirpath, 'enhancer_sets')
img_dirpath = yzer.get_and_create_path(dirpath, 'gene_enhancer_me2_lfc',
'scatterplots')
interactions = yzer.import_file(
yzer.get_filename(
data_dirpath,
'transcript_pairs_enhancer_with_anything_with_me2_inc_me2_counts.txt'
))
interactions = interactions[interactions['count'] > 1]
all_transcripts = yzer.import_file(
yzer.get_filename(data_dirpath, 'transcript_vectors.txt'))
for me2_timepoint in ('6h', '24h'):
me2_col = 'me2_{0}_ratio'.format(me2_timepoint)
kla_col = 'kla_lfc'
'''
Created on Oct 1, 2012
@author: karmel
'''
from __future__ import division
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
from matplotlib import pyplot
import numpy
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/Classes/Rotations/Finland_2012/GR_Project/'
dirpath = yzer.get_path(dirpath)
img_dirpath = yzer.get_and_create_path(dirpath, 'piecharts_from_p65_gr')
if True:
for main, compare, basal_cond in (
('GR', 'p65', 'Dex'),
('p65', 'GR', 'KLA'),
):
data = yzer.import_file(
yzer.get_filename(dirpath, 'motifs', 'from_peaks',
'{0}_kla_dex_vectors.txt'.format(main)))
# Get nearby peaks first
ids_with_nearby = data[
(data['distance_to_tss_2'].isnull() == False)
& (data['distance_to_peak_2'] <= 1000)]['id']
data = data.fillna(0)
'''
Created on Nov 26, 2012
@author: karmel
'''
from __future__ import division
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
from random import shuffle
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/GR_Analysis/hic_domains'
dirpath = yzer.get_path(dirpath)
data = yzer.import_file(
yzer.get_filename(dirpath, 'transcript_vectors.txt'))
data['ucsc_link_nod'] = data['ucsc_link_nod'].apply(
lambda s: s.replace('nod_balbc', 'gr_project_2012'))
data = data.fillna(0)
for rep in (4, 3, 1):
img_dirpath = yzer.get_and_create_path(dirpath, 'lfc_histograms',
'rep{0}'.format(rep))
kla_key = 'kla_{0}_lfc'.format(rep)
dex_kla_key = 'dex_over_kla_{0}_lfc'.format(rep)
data = data[data[kla_key] >= 1]
563,449,491,118
359,108,148,169'''
raw_data = raw_data.split('\n')
dates = [
datetime.strptime(raw_data[x], '%Y_%m_%d')
for x in xrange(0, len(raw_data), 3)
]
set1 = numpy.array([
map(int, raw_data[x].split(',')) for x in xrange(1, len(raw_data), 3)
]).T
set2 = numpy.array([
map(int, raw_data[x].split(',')) for x in xrange(2, len(raw_data), 3)
]).T
grapher = SeqGrapher()
ax = grapher.timeseries(
dates, [set1, set2],
show_median=True,
colors=['blue', 'red'],
labels=['Control', 'TDB treated'],
title='Blood glucose values in NOD mice after TDB treatment',
xlabel='Date',
ylabel='Blood glucose (mg/dL, via Aviva AccuChek meter)',
show_plot=False,
show_legend=True)
dirpath = '/Users/karmel/Desktop/Projects/GlassLab/Notes_and_Reports/NOD_BALBc/TDB in vitro/'
grapher.save_plot(
os.path.join(
dirpath,
'''
Created on Feb 15, 2013
@author: karmel
'''
from __future__ import division
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/NOD_BALBc/ThioMacs/Analysis_2013_02/'
dirpath = yzer.get_path(dirpath)
img_dirpath = yzer.get_and_create_path(dirpath, 'srf_ko_targets')
data = yzer.import_file(
yzer.get_filename(dirpath, 'transcript_vectors.txt'))
data = data.fillna(0)
data = data[data[['nod_notx_1h_tag_count', 'balb_notx_1h_tag_count']].max(
axis=1) >= 10]
data = data[(data['has_refseq'] == 1) & (data['transcript_score'] >= 4)]
# From Amy Sullivan SRF paper
down_in_srf_ko = [
'Cnn2', 'Srf', 'Lima1', 'Rhoj', 'Coro1a', 'Il1rn', 'Lsp1', 'LOC277203',
'Vcl', 'Card11', 'Cbr2', 'Cd83', 'Acta2', 'Actb', 'Tspan7', 'Ebi2',
'Gpr162', 'Ckb', 'Dhcr24', 'LOC638632', 'Actg2', 'Trim29', 'Ppap2b',
'Klk1b11', 'Actc1', 'Pcp4l1', 'LOC621324', 'Cdkn1c', 'Slco2b1',
'Cd24a', 'Pdgfa', 'Lrrc58', 'Dnmt3a', 'Slamf9', '1100001H23Rik',
'Aldoc', 'Cd28', '1500003O03Rik', 'Rab15', 'Pld4', 'Pilra', 'Xlr',
'Tgm1', 'Lcp1', 'Fstl1', 'Slc40a1', 'Usp24', 'Jup', 'Cd74', 'Tpm4',
if False:
yzer.prep_files_for_homer(
repr_data,
'repressed_in_{0}_kla_{1}_promoter_200'.format(
thresh, min_ratio),
yzer.get_filename(dirpath, 'from_genes', 'derepressed'),
center=False,
reverse=False,
preceding=False,
size=200)
yzer.prep_files_for_homer(
repr_data,
'repressed_in_{0}_kla_{1}_preceding_200'.format(
thresh, min_ratio),
yzer.get_filename(dirpath, 'from_genes', 'derepressed'),
center=False,
reverse=False,
preceding=True,
size=200)
if True:
grapher = SeqGrapher()
grapher.boxplot(
[rest_data['length_5_utr'], repr_data['length_5_utr']],
['All Genes', 'LFC in KLA <= {0}'.format(min_ratio)],
title="Length of 5'UTR according to KLA response",
xlabel='Gene Set',
ylabel='Length in bp',
show_outliers=False,
show_plot=True)
'''
Created on Oct 1, 2012
@author: karmel
'''
from __future__ import division
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
from glasslab.utils.functions import nonzero
from glasslab.dataanalysis.misc.gr_project_2012.v1.enhancer_subsets_for_supershift import ucsc_link_cleanup
import numpy
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/Classes/Rotations/Finland_2012/GR_Project/'
dirpath = yzer.get_path(dirpath)
peak_type = 'p65'
img_dirpath = yzer.get_and_create_path(dirpath, 'boxplots_non_refseq_by_{0}'.format(peak_type))
transcripts = yzer.import_file(yzer.get_filename(dirpath, 'motifs', 'transcript_vectors_with_nearby_peaks.txt'))
if True:
pu_1 = False
for ratio in (1.5, 2, 3):
data = transcripts[transcripts['refseq'] == 'f']
data = data[data['has_infrastructure'] == 0]
data = data[data['length'] < 6000]
data = data[data['dex_1_lfc'] < 1]
data = data[data['kla_1_lfc'] >= 1]
data = data[data['gr_kla_dex_tag_count'] > 0]
'''
Created on Sep 28, 2014
@author: karmel
'''
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
from glasslab.dataanalysis.misc.rodrigo.samples import sample_name,\
get_threshold
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/' +\
'Miscellaneous_Collaborations/Rodrigo_CD8s_2014_09/Promoters'
dirpath = yzer.get_path(dirpath)
cond, seq, breed = ('naive', 'atac', '')
wt_prefix = sample_name(cond, seq, breed)
ko_prefix = sample_name(cond, seq, 'foxo1_ko_')
wt_dirpath = yzer.get_filename(dirpath, wt_prefix)
ko_dirpath = yzer.get_filename(dirpath, ko_prefix)
wt_filename = yzer.get_filename(wt_dirpath,
wt_prefix + '_promoters.txt')
ko_filename = yzer.get_filename(ko_dirpath,
ko_prefix + '_promoters.txt')
wt_data = yzer.import_file(wt_filename)
wt_data = wt_data.fillna(0)
ko_data = yzer.import_file(ko_filename)
ko_data = ko_data.fillna(0)
'''
Created on Oct 8, 2012
@author: karmel
'''
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
from matplotlib import pyplot
from glasslab.dataanalysis.misc.gr_project_2012.boxplots_redistribution_pairs import get_high_quality_pairs
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/Classes/Rotations/Finland_2012/GR_Project/'
dirpath = yzer.get_path(dirpath)
motif_dirpath = yzer.get_filename(dirpath, 'motifs', 'from_peaks')
transcripts = yzer.import_file(
yzer.get_filename(dirpath, 'motifs', 'transcript_vectors.txt'))
transcripts['glass_transcript_id'] = transcripts['id']
if True:
all_data = yzer.import_file(
yzer.get_filename(
dirpath, 'redistribution',
'p65_peaks_bigger_in_kla_dex_with_nearby_bigger_kla_peaks.txt')
)
data = get_high_quality_pairs(all_data, transcripts)
data = data.groupby(['id', 'chr_name'], as_index=False).mean()
'''
Created on Apr 19, 2013
@author: karmel
Note: Made font.weight = bold and axes.titlesize = 24 in matplotlibrc
'''
from __future__ import division
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/Glass Atlas/NAR_review_data/'
dirpath = yzer.get_path(dirpath)
img_dirpath = yzer.get_and_create_path(dirpath, 'hg19_mcf7_pie_charts')
yzer.legend_location = 'lower left'
pie1 = '''Annotated by RefSeq and/or ncRNA.org 14,022
Unannotated 67,046'''
pie1 = [row.split(' ') for row in pie1.split('\n')]
pie1 = zip(*pie1)
yzer.piechart(map(lambda s: int(s.replace(',', '')), pie1[1]),
pie1[0],
title='Hah et al MCF-7 Transcripts\nwith Score >= 1',
save_dir=img_dirpath,
show_plot=True)
pie2 = '''Promoter-associated RNA 7,055
Antisense of RefSeq 7,539
Other RefSeq Proximal 13,664
Distal with H3K4me2 2,352
'''
Created on Mar 23, 2012
@author: karmel
'''
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
import os
if __name__ == '__main__':
grapher = SeqGrapher()
dirpath = '/Users/karmel/Desktop/Projects/GlassLab/Notes_and_Reports/NOD_BALBc/BMDCs/Analysis/'
filename = os.path.join(dirpath, 'balbc_nod_vectors.txt')
data = grapher.import_file(filename)
# vs balbc counterpart
data = grapher.normalize(data, 'nod_notx_0h_tag_count', 2.790489)
data = grapher.normalize(data, 'diabetic_nod_notx_0h_tag_count', 1.083990)
data = grapher.normalize(data, 'slow_diabetic_nod_notx_0h_tag_count',
0.349747)
# Vs nod notx
data = grapher.normalize(data,
'diabetic_nod_notx_0h_tag_count',
0.483232,
suffix='_norm_2')
data = grapher.normalize(data,
'slow_diabetic_nod_notx_0h_tag_count',
0.276080,
suffix='_norm_2')
'''
Created on Sep 7, 2012
@author: karmel
'''
from __future__ import division
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
if __name__ == '__main__':
grapher = SeqGrapher()
base_dirpath = 'karmel/Desktop/Projects/Classes/Rotations/Finland_2012/GR_Project/'
base_dirpath = grapher.get_path(base_dirpath)
dirpath = grapher.get_filename(base_dirpath, 'motifs')
filename = grapher.get_filename(dirpath, 'transcript_vectors.txt')
data = grapher.import_file(filename)
# Boxplots for gr_dex peaks by lfc in Dex
if False:
#data = data[data['distal'] == 't']
data = data[data['has_refseq'] == 1]
down = data[data['dex_1_lfc'] <= -1]
up = data[data['dex_1_lfc'] >= 1]
nc = data[abs(data['dex_1_lfc']) < 1]
key = 'p65_kla_tag_count'
datasets = [down[key],nc[key],up[key]]
datasets = [d['p65_kla_dex_tag_count'] - d[key] for d in [down, nc, up]]
'''
Created on Jun 26, 2012
@author: karmel
'''
from glasslab.dataanalysis.misc.gr_project_2012.elongation import set_up_sequencing_run_ids, \
get_sequencing_run_id_sets, get_rep_string, total_tags_per_run
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer
if __name__ == '__main__':
grapher = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/Classes/Rotations/Finland_2012/GR_Project/'
dirpath = grapher.get_path(dirpath)
filename = grapher.get_filename(dirpath, 'transcript_vectors.txt')
data = grapher.import_file(filename)
run_ids = set_up_sequencing_run_ids()
dmso, kla, kla_dex, all_dmso, all_kla, all_kla_dex = get_sequencing_run_id_sets(
)
total_tags = total_tags_per_run()
# Norm sum scalars listed for all, group 1, group 2, group 3, group 4
kla_scalars = [1.223906, 1.281572, 1.118363, 1.104860, 1.503260]
kla_dex_scalars = [1.182574, 1.147695, 1.248636, 1.069588, 1.388871]
dex_over_kla_scalars = [1.069073, 0.967659, 1.122628, 1.008758, 0.927466]
for i, scalar in enumerate(kla_scalars):
data = grapher.normalize(data,
'kla_{0}tag_count'.format(get_rep_string(i)),
'''
Created on Jan 30, 2013
@author: karmel
'''
from __future__ import division
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
from collections import OrderedDict
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/HiC/'
dirpath = yzer.get_path(dirpath)
data_dirpath = yzer.get_filename(dirpath, 'enhancer_rewiring_lfc')
transcripts = yzer.import_file(
yzer.get_filename(dirpath, 'enhancer_sets', 'transcript_vectors.txt'))
sets = OrderedDict((
('all',
yzer.import_file(yzer.get_filename(data_dirpath, 'all_vectors.cdt'))),
#('all_6h', yzer.import_file(yzer.get_filename(data_dirpath,'kla_6h','all_vectors.cdt'))),
('rewired',
yzer.import_file(
yzer.get_filename(data_dirpath, 'rewired_vectors.cdt'))),
#('rewired_6h', yzer.import_file(yzer.get_filename(data_dirpath,'kla_6h','rewired_vectors.cdt'))),
('shared',
yzer.import_file(yzer.get_filename(data_dirpath,
'shared_vectors.cdt'))),
))
for key, val in sets.items():
'''
Created on Feb 14, 2013
@author: karmel
'''
from __future__ import division
from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher
from glasslab.utils.functions import nonzero
if __name__ == '__main__':
yzer = SeqGrapher()
dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/CD4TCells/Oshea_enhancers/ctcf_stat1_overlap'
dirpath = yzer.get_path(dirpath)
img_dirpath = yzer.get_and_create_path(dirpath, 'figures')
data = yzer.import_file(
yzer.get_filename(dirpath, 'ctcf_with_stat1_binding.txt')).fillna(0)
with_stat1 = data[data['p2_tag_count'] > 0]
without_stat1 = data[data['p2_tag_count'] == 0]
if True:
ax = yzer.piechart(
[len(with_stat1), len(without_stat1)],
['CTCF sites with STAT1', 'CTCF sites without STAT1'],
title='DP Thymocyte CTCF Sites with STAT1 in Th1 Cells',
save_dir=img_dirpath,
show_plot=True)
data['tag_count_nonzero'] = nonzero(data['tag_count'])
data['p2_tag_count_nonzero'] = nonzero(data['p2_tag_count'])
ax = yzer.scatterplot(