Detailed information of deep learning profile BP001349.1

  1. Home
  2. Deep Learning Profile > BP001349.1
This page shows detailed deep learning-derived predictions and motifs for PPARG in HepG2 using a single trained BPNet model.

Model details

Name: PPARG
Model ID: BP001349.1
Cell line/tissue: HepG2
Class: Nuclear receptors with C4 zinc fingers
Family: Thyroid hormone receptor-related factors (NR1)
JASPAR ID: MA0065.3
Taxon: Vertebrates
Species: Homo sapiens
Data Type: ChIP-seq
Uniprot ID: P19793  
Source: ENCSR130VQL
Model: BPNet
Download trained model
Download TF-MoDISco Report

Sequence logo

 

Contribution weight matrix (CWM)

 
A [ 0.00 0.00 0.00 -0.00 -0.00 0.00 0.03 0.01 -0.00 -0.00 -0.00 -0.00 0.00 0.01 0.00 -0.00 -0.00 0.01 -0.00 0.00 ]
C [ 0.00 0.00 0.00 0.00 0.00 -0.00 -0.00 0.03 0.06 0.00 -0.00 -0.00 -0.00 0.00 0.03 0.04 0.01 0.00 0.00 -0.00 ]
G [ 0.00 0.00 0.00 0.00 -0.00 0.03 0.00 -0.00 -0.00 -0.00 -0.00 -0.00 0.03 0.00 -0.00 -0.00 -0.00 0.00 0.00 0.00 ]
T [ -0.00 -0.00 -0.00 0.00 0.03 -0.00 -0.00 -0.00 0.00 0.05 0.03 0.05 -0.00 -0.00 -0.00 -0.00 0.01 -0.00 -0.00 0.01 ]

Frequency matrix

       
A [ 2407 2406 2382 2298 2307 2434 2435 2540 2486 2320 2380 2734 2475 2268 1873 656 1270 6129 3154 93 30 325 57 1021 3484 1762 793 1033 3616 1984 2991 2087 2404 2111 2157 2319 2439 2348 2432 2388 2351 2359 2290 2385 2345 2385 2405 2507 2365 2295 ]
C [ 2396 2406 2428 2363 2411 2209 2196 2248 2210 2339 2489 2420 2840 2501 2532 797 731 1369 5731 9014 804 1503 210 968 2554 5492 7699 3615 2165 2512 1248 1489 2284 2820 2710 2363 2414 2273 2193 2262 2170 2304 2312 2427 2405 2330 2325 2179 2170 2351 ]
G [ 2117 1963 2093 2145 2068 2160 2017 2098 2270 2184 2317 1988 1954 1966 2466 581 6860 1616 38 6 11 130 162 6901 1896 378 126 257 1691 2818 1322 1971 1983 1976 1817 1981 1985 1942 2170 2138 2130 2097 2051 2121 2103 2141 2057 2168 2188 2124 ]
T [ 2424 2569 2441 2538 2558 2541 2696 2458 2378 2501 2158 2202 2075 2609 2473 7310 483 230 421 231 8499 7386 8915 454 1410 1712 726 4439 1872 2030 3783 3797 2673 2437 2660 2681 2506 2781 2549 2556 2693 2584 2691 2411 2491 2488 2557 2490 2621 2574 ]

Hypothetical CWM

   
A [ 0.00 -0.00 0.00 -0.00 -0.02 0.01 0.04 0.03 -0.02 -0.04 -0.00 -0.02 0.01 0.02 -0.00 -0.00 -0.02 0.02 0.00 0.01 -0.00 0.00 ]
C [ 0.01 0.01 0.01 0.00 0.01 -0.01 0.01 0.05 0.07 0.02 0.01 0.00 0.00 0.01 0.04 0.04 0.02 0.00 0.01 -0.00 -0.00 0.00 ]
G [ 0.01 0.01 0.01 0.01 -0.01 0.04 0.01 -0.04 -0.03 -0.02 -0.03 -0.01 0.04 0.02 -0.01 -0.02 -0.00 0.01 0.01 -0.01 0.00 0.00 ]
T [ -0.00 -0.01 -0.00 0.00 0.03 -0.01 -0.03 -0.01 0.00 0.05 0.05 0.05 -0.01 -0.01 0.00 -0.00 0.02 -0.01 -0.01 0.01 0.01 -0.00 ]

Other motifs identified by TF-MoDISco

 

Motif name: counts.pos_patterns.pattern_1

Num. of seqlets: 3917

CWM

PFM

     

HCWM

Motif name: counts.pos_patterns.pattern_2

Num. of seqlets: 1070

CWM

PFM

     

HCWM

Motif name: counts.pos_patterns.pattern_3

Num. of seqlets: 965

CWM

PFM

     

HCWM

Motif name: counts.pos_patterns.pattern_4

Num. of seqlets: 938

CWM

PFM

     

HCWM

Motif name: counts.pos_patterns.pattern_5

Num. of seqlets: 344

CWM

PFM

     

HCWM

Motif name: counts.pos_patterns.pattern_6

Num. of seqlets: 209

CWM

PFM

     

HCWM

Motif name: counts.pos_patterns.pattern_7

Num. of seqlets: 187

CWM

PFM

     

HCWM

Motif name: counts.pos_patterns.pattern_8

Num. of seqlets: 166

CWM

PFM

     

HCWM

Motif name: counts.pos_patterns.pattern_9

Num. of seqlets: 114

CWM

PFM

     

HCWM