In [1]:
import numpy as np
motif_name = 'FOXA2'
aitacdir = "/mnt/lab_data2/msharmin/oc-atlas/DanSkinData/fold_a_alex/{}".format(motif_name)

ave_filt_infl = np.load(aitacdir+"/ave_filt_infl.npy")
In [4]:
from matlas.matches import DenovoAitac
motif_name = 'FOXA2'
aitacdir = "/mnt/lab_data2/msharmin/oc-atlas/DanSkinData/fold_a_alex/{}".format(motif_name)

ob = DenovoAitac(aitacdir, influence=ave_filt_infl)
# ob.fetch_tomtom_matches(
#             meme_db="/mnt/lab_data/kundaje/users/msharmin/annotations/HOCOMOCOv11_core_pwms_HUMAN_mono.renamed.nonredundant.annotated.meme",
#             database_name="HOCOMOCO.nonredundant.annotated",
#             save_report=True, tomtom_dir= "{0}/{1}_tomtomout".format(aitacdir, "HOCOMOCO.nonredundant.annotated"))
ob.load_matched_motifs(database_name="HOCOMOCO.nonredundant.annotated")
ob.get_motif_per_celltype(match_threshold=0.05, database_name="HOCOMOCO.nonredundant.annotated")
pattern_tab, pattern_dict = ob.visualize_pattern_table()
tf_tab, tf_dict = ob.visualize_tf_table("Aitac")
In [5]:
from vdom.helpers import (b, summary, details)
from IPython.display import display

display(details(summary('Click here for ', b('Denovo Patterns'), ' by ', b('{}'.format('Aitac')),
                        ' in ', b(motif_name),
                        ": #{}".format(len(pattern_dict)),
                       ), pattern_tab))
Click here for Denovo Patterns by Aitac in FOXA2: #64
Pattern NameTF Name(s)AitacInfluence
filter30.018851675734348726
filter450.018494599037388502
filter40.01777000864770658
filter70.01693512368411496
filter280.016611276217690162
filter260.016273830239914723
filter320.016163065951904004
filter520.016138804659682877
filter20.016050653827072284
filter90.016043741219777502
filter250.016022150366264115
filter290.016004719134361616
filter370.015995807814353374
filter10.015986844593286618
filter60.015951882825469617
filter200.015948162135177354
filter350.015945766530005116
filter14HCLUST-144_CUX1.UNK.0.A, HCLUST-117_LHX3.UNK.0.A0.01593006296417669
filter180.015927920268968495
filter00.015895484777162856
filter610.015892361183440507
filter80.01587526571423301
filter630.015862977487760152
filter240.015844774142926104
filter570.015828682860277044
filter110.015826267495499473
filter360.015825274079169897
filter390.01582360915572451
filter160.01581930709786241
filter230.01581830097081625
filter600.015812980350152245
filter330.015812971346272884
filter400.01581296659276909
filter620.01581296367648535
filter100.015812963339168012
filter120.015812963339168012
filter130.015812963339168012
filter560.015812963339168012
filter170.015812963339168012
filter190.015812963339168012
filter580.015812963339168012
filter490.015812963339168012
filter430.015812963339168012
filter460.015812963339168012
filter410.015812963339168012
filter470.015812963339168012
filter420.015812963329481452
filter500.01580281456444825
filter440.015774368515950255
filter310.01577006385141546
filter340.015758402658940362
filter270.015734498044743132
filter220.01572670774327542
filter530.015722841958527488
filter510.015703320261617533
filter50.015697317970979348
filter480.0156698775971079
filter540.015660980041356527
filter150.01558618368696014
filter590.015562177775459634
filter300.015545678534537876
filter380.01554088670028902
filter550.015481181083953922
filter210.015448210725908367
In [6]:
display(details(summary('Click here for ', b('Motifs'), ' by ', b('{}'.format('Aitac')),
                        ' in ', b(motif_name),
                        ": #{}".format(len(tf_dict)),
                       ), tf_tab))
Click here for Motifs by Aitac in FOXA2: #2
TF NamePattern(s)
HCLUST-144_CUX1.UNK.0.A
Pattern NameAitacSignificance
filter140.0219914
HCLUST-117_LHX3.UNK.0.A
Pattern NameAitacSignificance
filter140.0306189
In [ ]: