''' Created on Sep 7, 2012 @author: karmel ''' from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/Classes/Rotations/Finland_2012/GR_Project/' dirpath = yzer.get_path(dirpath) motif_dirpath = yzer.get_filename(dirpath, 'motifs', 'from_peaks') all_data = yzer.import_file( yzer.get_filename(motif_dirpath, 'p65_kla_vectors.txt')) size = 100 if True: for ratio in (3, 2, 1.5): enhancers = yzer.import_file( yzer.get_filename( dirpath, 'boxplots_non_refseq_by_p65', 'enhancer_like_lose_p65_{0}x_change_dsg_only.txt'.format( ratio))) enhancers['glass_transcript_id'] = enhancers['id'] # Limit to peaks and touching transcripts, then pull out peaks that intersect our enhancer set data = all_data[all_data['touches'] == 't'] data = data.merge(enhancers, how='right', on='glass_transcript_id',
@author: karmel ''' from __future__ import division from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/CD4TCells/Foxo1' dirpath = yzer.get_path(dirpath) motifs_dirpath = yzer.get_and_create_path(dirpath, 'motifs') peak_pretty = 'Foxo1' peak = peak_pretty.lower() foxo1 = yzer.import_file( yzer.get_filename(dirpath, '{0}_with_foxp3.txt'.format(peak))).fillna(0) datasets = [ ('foxo1_all', foxo1), ('foxo1_tss', foxo1[foxo1['tss_id'] > 0]), ('foxo1_enhancers', foxo1[foxo1['tss_id'] == 0]), ] for name, subset in datasets: subset['id'] = subset['{0}_id'.format(peak)] subset['start'] = subset['{0}_start'.format(peak)] subset['end'] = subset['{0}_end'.format(peak)] yzer.run_homer(subset, name, motifs_dirpath, cpus=6,
@author: karmel ''' from __future__ import division from glasslab.dataanalysis.misc.cd4tcell_finland_2012.resources import replicate_sets from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/CD4TCells_Finland_2012/Analysis_2013_02' dirpath = yzer.get_path(dirpath) go_path = yzer.get_and_create_path(dirpath, 'with_me3', 'go_analysis', '0_8_min_lfc') data = yzer.import_file( yzer.get_filename(dirpath, 'transcript_vectors.txt')) data = data.fillna(0) data = data[data['naive_me3_tag_count'] + data['act_me3_tag_count'] > 0] if False: curr_path = yzer.get_and_create_path(dirpath, 'with_me3', 'motif_analysis') yzer.run_homer(data, 'all_refseq_preceding', curr_path, center=False, reverse=False, preceding=True, size=200, cpus=6)
''' Created on Mar 28, 2013 @author: karmel ''' from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/CD4TCells/TReg_enhancers/2013_03_19' dirpath = yzer.get_path(dirpath) motif_dirpath = yzer.get_filename(dirpath, 'motifs') for antibody in ('me2', 'ac'): treg = yzer.import_file( yzer.get_filename( dirpath, 'treg_with_naive_{0}.txt'.format(antibody))).fillna(0) naive = yzer.import_file( yzer.get_filename( dirpath, 'naive_with_treg_{0}.txt'.format(antibody))).fillna(0) # Filter out promoters treg = treg[treg['tss_id'] == 0] naive = naive[naive['tss_id'] == 0] # Get venn-diagram sets for foxp3/me2 only_treg = treg[treg['naive_id'] == 0] only_naive = naive[naive['treg_id'] == 0] shared = treg[treg['naive_id'] > 0] print len(only_treg), len(only_naive), len(shared)
left outer join chipseq.peak_{} p{counter} on p1.chromosome_id = p{counter}.chromosome_id and p1.start_end && p{counter}.start_end '''.format(oth_breed[0][i], counter=counter)) # Put it all together sql += ',\n'.join(selects) sql += ''' from chipseq.peak_{} p1 join genome_reference_mm10.chromosome chr on p1.chromosome_id = chr.id '''.format(sample) sql += ''.join(joins) sql += ''' left outer join genome_reference_mm10.sequence_transcription_region reg on p1.chromosome_id = reg.chromosome_id and p1.start_end && reg.start_site_1000 where reg.id is NULL; ''' print(sql) # Set up output dir sample_path = yzer.get_and_create_path(dirpath, curr_name) # Get data data = dataframe_from_query(sql, engine) output_file = yzer.get_filename(sample_path, curr_name + '_enhancers.txt') data.to_csv(output_file, sep='\t', header=True, index=False)
The goal here is to see if we can tease out which features are predictive of characteristics of interest, such as pausing ratio or transrepression. Worth a stab. ''' from glasslab.dataanalysis.misc.gr_project_2012.elongation import get_rep_string import sys from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/Classes/Rotations/Finland_2012/GR_Project/motifs' dirpath = yzer.get_path(dirpath) grouped = yzer.import_file(yzer.get_filename(dirpath, 'feature_vectors.txt')) trans = [] if True: # Minimal ratio in KLA+Dex vs. KLA pausing try: min_ratio= float(sys.argv[1]) except IndexError: min_ratio = -1 try: try: secondary_min_ratio= float(sys.argv[2]) except ValueError: secondary_min_ratio= sys.argv[2] except IndexError: secondary_min_ratio = 'none' try: thresh = int(sys.argv[3]) except IndexError: thresh = 2 grouped['relevant_sets'] = 0
''' Created on Feb 12, 2013 @author: karmel ''' from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/CD4TCells/TReg_enhancers/2013_03_19' dirpath = yzer.get_path(dirpath) motif_dirpath = yzer.get_filename(dirpath, 'motifs') for antibody in ('me2', ): data = {} celltypes = ['treg', 'naive', 'th1', 'th2'] for celltype in celltypes: data[celltype] = yzer.import_file( yzer.get_filename( dirpath, '{0}_{1}_versus_others.txt'.format(celltype, antibody))).fillna(0) # Filter out promoters data[celltype] = data[celltype][data[celltype]['tss_id'] == 0] # Get venn-diagram "only" sets others = celltypes[:] others.remove(celltype)
The goal here is to see if we can tease out which features are predictive of characteristics of interest, such as pausing ratio or transrepression. Worth a stab. ''' from glasslab.dataanalysis.misc.gr_project_2012.elongation import get_rep_string import sys from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/Classes/Rotations/Finland_2012/GR_Project/motifs' dirpath = yzer.get_path(dirpath) grouped = yzer.import_file( yzer.get_filename(dirpath, 'feature_vectors.txt')) paused = [] if True: # Can we predict pausing ratio? # Minimal ratio in KLA+Dex vs. KLA pausing try: min_ratio = float(sys.argv[1]) except IndexError: min_ratio = 2 try: secondary_min_ratio = float(sys.argv[2]) except IndexError: secondary_min_ratio = 1.2
@author: karmel ''' from __future__ import division from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/CD4TCells/H3K4me2/Analysis/venn_diagrams' dirpath = yzer.get_path(dirpath) motifs_dirpath = yzer.get_and_create_path(dirpath, 'motifs') peak_pretty = 'H3K4me2' peak = peak_pretty.lower() th1 = yzer.import_file( yzer.get_filename( dirpath, 'th1_with_th2_me1_and_{0}.txt'.format(peak))).fillna(0) th2 = yzer.import_file( yzer.get_filename( dirpath, 'th2_with_th1_me1_and_{0}.txt'.format(peak))).fillna(0) naive = yzer.import_file( yzer.get_filename( dirpath, '{0}_with_th1_and_th2_me1.txt'.format(peak))).fillna(0) # Filter out promoters th1 = th1[th1['tss_id'] == 0] th2 = th2[th2['tss_id'] == 0] naive = naive[naive['tss_id'] == 0] # Get venn-diagram sets for th1/th2 only_th1 = th1[th1['th2_id'] == 0] only_th2 = th2[th2['th1_id'] == 0]
@author: karmel ''' from glasslab.dataanalysis.misc.rodrigo.samples import sample_name,\ get_threshold from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer if __name__ == '__main__': yzer = MotifAnalyzer() 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', '') sample_prefix = sample_name(cond, seq, breed) sample_dirpath = yzer.get_filename(dirpath, sample_prefix) filename = yzer.get_filename(sample_dirpath, sample_prefix + '_promoters.txt') data = yzer.import_file(filename) data = data.fillna(0) min_thresh = get_threshold(seq) data = data[data['tag_count'] >= min_thresh] fold = 2 if True: # ATAC peaks that are absent in the FOXO1 KO foxo1_critical = data[ data['foxo1_ko_naive_atac_tag_count'] < min_thresh] yzer.run_homer(foxo1_critical,
from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/Classes/Rotations/Finland_2012/GR_Project/motifs/from_peaks/vs_non_dsg' dirpath = yzer.get_path(dirpath) for peak_type in ( #'gr_dex_fa', 'gr_kla_dex_fa', #'gr_dex_dsg', 'gr_kla_dex_dsg', ): size = 200 if True: all_data = yzer.import_file( yzer.get_filename(dirpath, '{0}_vectors.txt'.format(peak_type))) all_data = all_data.fillna(0) for super_name, data in (( 'all', all_data, ), ): for name, dataset in (( 'all', data, ), ): # We have multiple copies of peaks if they align to different transcripts curr_path = yzer.get_and_create_path( dirpath, peak_type, super_name, name) # Group them after selecting those that we want
@author: karmel ''' from __future__ import division from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/CD4TCells/H3K4me2/Analysis/venn_diagrams' dirpath = yzer.get_path(dirpath) motifs_dirpath = yzer.get_and_create_path(dirpath, 'motifs') peak_pretty = 'H3K4me2' peak = peak_pretty.lower() dp = yzer.import_file( yzer.get_filename(dirpath, 'dp_with_{0}.txt'.format(peak))).fillna(0) naive = yzer.import_file( yzer.get_filename(dirpath, '{0}_with_dp.txt'.format(peak))).fillna(0) # Filter out promoters dp = dp[dp['tss_id'] == 0] naive = naive[naive['tss_id'] == 0] # Get venn-diagram sets for th1/th2 dp_only = dp[dp['naive_id'] == 0] naive_only = naive[naive['dp_id'] == 0] shared = naive[naive['dp_id'] > 0] datasets = [dp_only, naive_only, shared] main_peak = ['dp', 'naive', 'naive'] names = [
''' Created on Apr 18, 2013 @author: karmel ''' from __future__ import division from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/CD4TCells/TReg_enhancers/2013_04_01' dirpath = yzer.get_path(dirpath) motif_dirpath = yzer.get_filename(dirpath, 'motifs') foxp3 = yzer.import_file(yzer.get_filename( dirpath, 'foxp3_with_stat1.txt')).fillna(0) stat1 = yzer.import_file(yzer.get_filename( dirpath, 'stat1_with_foxp3.txt')).fillna(0) print len(foxp3), len(stat1) print sum(foxp3['stat1_id'] > 0) print sum(foxp3['stat1_id'] > 0) / len(foxp3) print sum(stat1['foxp3_id'] > 0) print sum(stat1['foxp3_id'] > 0) / len(stat1) foxp3_enh = foxp3[(foxp3['tss_me2_id'] == 0) & (foxp3['tss_id'] == 0)] foxp3_tss = foxp3[(foxp3['tss_me2_id'] > 0) | (foxp3['tss_id'] > 0)] print len(foxp3_enh) print sum(foxp3_enh['stat1_id'] > 0) / len(foxp3_enh)
@author: karmel ''' from __future__ import division from glasslab.dataanalysis.misc.gr_project_2012.elongation import get_rep_string import sys from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/Classes/Rotations/Finland 2012/KLA skew/' dirpath = yzer.get_path(dirpath) grouped = yzer.import_file( yzer.get_filename(dirpath, 'feature_vectors.txt')) repressed = [] if True: # Can we predict pausing ratio? # Minimal ratio in KLA+Dex vs. KLA pausing try: min_ratio = float(sys.argv[1]) except IndexError: min_ratio = -1 try: thresh = int(sys.argv[3]) except IndexError: thresh = 4
Note that set 1 of Rudensky's Foxp3 chip has 2x as many peaks, but he seems to use set 2 in the paper (?). Here we use summed tags and peaks found in that. ''' from __future__ import division from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher if __name__ == '__main__': yzer = MotifAnalyzer() grapher = SeqGrapher() dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/CD4TCells/TReg_enhancers/2013_04_01' dirpath = yzer.get_path(dirpath) motif_dirpath = yzer.get_filename(dirpath, 'motifs') graph_dirpath = yzer.get_filename(dirpath, 'piecharts') min_score = 10 for antibody in ('me2', ): data = {} celltypes = ['treg', 'naive', 'th1', 'th2'] for celltype in ('treg', 'th1'): data[celltype] = yzer.import_file( yzer.get_filename( dirpath, '{0}_{1}_versus_others_with_foxp3.txt'.format( celltype, antibody))).fillna(0) # Filter out promoters data[celltype] = data[celltype][data[celltype]['tss_id'] == 0]
@author: karmel Note that set 1 of Rudensky's Foxp3 chip has 2x as many peaks, but he seems to use set 2 in the paper (?). Here we use summed tags and peaks found in that. ''' from __future__ import division from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer from collections import OrderedDict if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/CD4TCells/TReg_enhancers/2013_04_01' dirpath = yzer.get_path(dirpath) motif_dirpath = yzer.get_filename(dirpath, 'motifs') min_score = 10 stats = OrderedDict() all_data = yzer.import_file( yzer.get_filename(dirpath, 'foxp3_with_treg_enhancers.txt')).fillna(0) stats['all'] = len(all_data) # Filter out promoters data = all_data[all_data['tss_id'] == 0] stats['enhancers'] = len(data) stats['me2_treg'] = sum(data['me2_id'] > 0) stats['ac_treg'] = sum(data['ac_id'] > 0) stats['me2_treg_naive'] = sum((data['me2_id'] > 0) & (data['naive_id'] > 0))
''' Created on Feb 12, 2013 @author: karmel ''' from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/CD4TCells/iTreg_enhancers/2014_04_11/' dirpath = yzer.get_path(dirpath) for ab in ('me2', 'ac'): condition = 'treg' motif_dirpath = yzer.get_filename(dirpath, 'Motifs') filename = yzer.get_filename( dirpath, '{}_{}_enhancers.txt'.format(condition, ab)) data = yzer.import_file(filename) data = data.fillna(0) min_thresh = 20 if False: subdata = data[data['tag_count'] > min_thresh] subdata = subdata[subdata['tag_count(2)'] > min_thresh] subdata = subdata[subdata['tag_count(3)'] <= 0] subdata = subdata[subdata['tag_count(4)'] <= 0] subdir = 'treg_shared_' + ab
@author: karmel ''' from glasslab.dataanalysis.misc.rodrigo.samples import SAMPLES, sample_name,\ get_threshold from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/' +\ 'Miscellaneous_Collaborations/Rodrigo_CD8s_2014_09/Enhancers' dirpath = yzer.get_path(dirpath) for cond, seq, breed in SAMPLES: sample_prefix = sample_name(cond, seq, breed) sample_dirpath = yzer.get_filename(dirpath, sample_prefix) filename = yzer.get_filename(sample_dirpath, sample_prefix + '_enhancers.txt') data = yzer.import_file(filename) data = data.fillna(0) if True: min_thresh = get_threshold(seq) subdata = data[data['tag_count'] >= min_thresh] yzer.run_homer(subdata, 'all', sample_dirpath, cpus=10,
''' Created on Feb 12, 2013 @author: karmel ''' from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/CD4TCells/H3K4me2/Analysis' dirpath = yzer.get_path(dirpath) motif_dirpath = yzer.get_filename(dirpath, 'motifs') filename = yzer.get_filename(dirpath, 'thio_peak_vectors.txt') data = yzer.import_file(filename) data = data.fillna(0) # me2 if True: if False: yzer.run_homer(data, 'thio_all', motif_dirpath, cpus=6, center=True, reverse=False, preceding=False, size=200, length=[8, 10, 12, 15]) data = data[data['tss_id'] == 0]
scatter_dirpath, 'two_color_kla_vs_kla_dex_group_{0}_runs_{1}.png'. format(x, slug_label))) grapher.show_plot() if False: # Gene names print grapher.get_gene_names(refseq[(refseq['kla_1_lfc'] >= 1)], add_quotes=True) print grapher.get_gene_names( refseq[(refseq['kla_1_lfc'] >= 1) & (refseq['dex_over_kla_1_lfc'] < -.58)]) if False: yzer = MotifAnalyzer() motif_dirpath = yzer.get_filename(dirpath, 'motifs/size_200') distal = data[data['distal'] == 't'] dataset = distal[(distal['kla_lfc'] >= 1)] yzer.prep_files_for_homer(dataset, 'distal_up_in_kla_all', motif_dirpath, center=False, reverse=False, preceding=True, size=200) dataset = distal[(distal['kla_1_lfc'] >= 1)] yzer.prep_files_for_homer(dataset, 'distal_up_in_kla_1', motif_dirpath,
@author: karmel ''' from __future__ import division from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/CD4TCells/Rudensky_enhancers' dirpath = yzer.get_path(dirpath) motifs_dirpath = yzer.get_and_create_path(dirpath, 'motifs') peak_pretty = 'Foxp3' peak = peak_pretty.lower() foxp3 = yzer.import_file( yzer.get_filename(dirpath, '{0}_1_with_naive_me2.txt'.format(peak))).fillna(0) naive = yzer.import_file( yzer.get_filename(dirpath, 'naive_me2_with_{0}.txt'.format(peak))).fillna(0) # Filter out promoters foxp3 = foxp3[foxp3['tss_id'] == 0] naive = naive[naive['tss_id'] == 0] # Get venn-diagram sets for foxp3/me2 only_foxp3 = foxp3[foxp3['naive_id'] == 0] only_naive = naive[naive['foxp3_1_id'] == 0] shared = foxp3[foxp3['naive_id'] > 0] print len(only_foxp3), len(only_naive), len(shared) # Now factor in foxo1
''' Created on Jul 5, 2012 @author: karmel ''' from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer from glasslab.dataanalysis.misc.gr_project_2012.elongation import get_rep_string import sys if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/Classes/Rotations/Finland_2012/GR_Project/motifs' dirpath = yzer.get_path(dirpath) pausing_data = yzer.import_file( yzer.get_filename(dirpath, 'feature_vectors.txt')) data = yzer.import_file( yzer.get_filename(dirpath, 'transcript_vectors.txt')) try: min_ratio = float(sys.argv[1]) except IndexError: min_ratio = 1.5 if False: yzer.prep_files_for_homer(data, 'all_transcripts_promoter', dirpath, center=False, reverse=False, preceding=True,
''' Created on Sep 7, 2012 @author: karmel ''' from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/Classes/Rotations/Finland_2012/GR_Project/motifs' dirpath = yzer.get_path(dirpath) motif_dirpath = yzer.get_filename(dirpath,'from_peaks') transcripts = yzer.import_file(yzer.get_filename(dirpath, 'transcript_vectors.txt')) transcripts['glass_transcript_id'] = transcripts['id'] for peak_type in ('gr_dex', 'gr_kla_dex', 'p65_kla_dex','p65_kla'): size = 100 if True: all_data = yzer.import_file(yzer.get_filename(motif_dirpath, '{0}_vectors.txt'.format(peak_type))) all_data = all_data.merge(transcripts, how='left', on='glass_transcript_id',suffixes=['','trans']) all_data = all_data.fillna(0) for super_name, data in (#('all', all_data,), #('refseq', all_data[(all_data['score'] > 10) & (all_data['has_refseq'] == 1) # & (all_data['touches'] == 't') | (all_data['relationship'] == 'is downstream of')],), #('distal', all_data[(all_data['distal'] == 't')],),
''' Created on Feb 12, 2013 @author: karmel ''' from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/CD4TCells/iTreg_enhancers/2014_02_14/Motifs' dirpath = yzer.get_path(dirpath) for ab in ('me2', 'ac'): for condition in ('treg', 'itreg', 'activated'): cond_dirpath = yzer.get_filename(dirpath, '{}_{}'.format(condition, ab)) if True: filename = yzer.get_filename( cond_dirpath, '{}_{}_enhancers.txt'.format(condition, ab)) data = yzer.import_file(filename) data = data.fillna(0) yzer.run_homer(data, 'all', cond_dirpath, cpus=6, center=True, reverse=False, preceding=False,
''' Created on Feb 8, 2013 @author: karmel ''' from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer if __name__ == '__main__': yzer = MotifAnalyzer() base_dirpath = yzer.get_path( 'karmel/GlassLab/Notes_and_Reports/NOD_BALBc/ThioMacs/Analysis_2013_02/' ) dirpath = yzer.get_and_create_path(base_dirpath, 'motifs/') filename = yzer.get_filename(base_dirpath, 'transcript_vectors.txt') data = yzer.import_file(filename) data = data.fillna(0) # Promoters if False: refseq = data[data['has_refseq'] == 1] refseq = refseq[refseq['transcript_score'] >= 4] if True: yzer.run_homer(refseq, 'refseq_promoter', dirpath, cpus=6, center=False, reverse=False, preceding=True, size=400,
@author: karmel ''' from glasslab.dataanalysis.misc.gr_project_2012.elongation import get_rep_string import sys from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer from glasslab.dataanalysis.graphing.seq_grapher import SeqGrapher if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/Classes/Rotations/Finland 2012/KLA skew/' dirpath = yzer.get_path(dirpath) grouped = yzer.import_file( yzer.get_filename(dirpath, 'feature_vectors.txt')) repressed = [] if True: # Can we predict pausing ratio? # Minimal ratio in KLA+Dex vs. KLA pausing try: min_ratio = float(sys.argv[1]) except IndexError: min_ratio = -1 try: thresh = int(sys.argv[3]) except IndexError: thresh = 4
''' Created on Feb 12, 2013 @author: karmel ''' from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/AND_TCR/Analysis/Chips1_2/Motifs' dirpath = yzer.get_path(dirpath) for ab in ('me2', 'ac'): for peptide in ('K99A', 'NoPep', 'PCC'): pep_dirpath = yzer.get_filename(dirpath, '{}_{}'.format(peptide, ab)) if False: filename = yzer.get_filename( pep_dirpath, '{}_{}_enhancers.txt'.format(peptide, ab)) data = yzer.import_file(filename) data = data.fillna(0) yzer.run_homer(data, 'all', pep_dirpath, cpus=6, center=True, reverse=False, preceding=False,
''' Created on Apr 12, 2013 @author: karmel ''' from __future__ import division from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer if __name__ == '__main__': yzer = MotifAnalyzer() dirpath = 'karmel/Desktop/Projects/GlassLab/Notes_and_Reports/CD4TCells/TReg_enhancers/2013_04_01' dirpath = yzer.get_path(dirpath) data = yzer.import_file(yzer.get_filename( dirpath, 'th1_with_stat1_ko.txt')).fillna(0) print len(data) data = data[data['tss_id'] == 0] data['ko_ratio'] = data['ko_id'] / data['th1_id'] data['treg_ratio'] = data['treg_id'] / data['th1_id'] enh = len(data) print enh print sum(data['ko_ratio'] < .5), sum(data['ko_ratio'] < .5) / enh print sum(data['treg_ratio'] < .5), sum(data['treg_ratio'] < .5) / enh print sum((data['treg_ratio'] < .5) & (data['ko_ratio'] < .5)) print sum((data['treg_ratio'] < .5) & (data['ko_ratio'] < .5)) / enh
''' Created on Sep 7, 2012 @author: karmel ''' from glasslab.dataanalysis.motifs.motif_analyzer import MotifAnalyzer from glasslab.dataanalysis.misc.gr_project_2012.v1.boxplots_redistribution_pairs import get_high_quality_pairs if __name__ == '__main__': yzer = MotifAnalyzer() 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'] size = 200 if True: all_data = yzer.import_file( yzer.get_filename( dirpath, 'redistribution', 'p65_peaks_bigger_in_kla_dex_with_nearby_bigger_kla_peaks.txt') ) all_data = get_high_quality_pairs(all_data, transcripts) for super_name, data in ( (