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Compare TF Sites Across Sequences
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Predict and visualize TF binding sites on one or multiple enhancers. Sites can be predicted using two approaches. The first and preferred is to predict sites with a core binding site and determine binding site affinity using a reference affinity dataset. When less studies on the TF have been performed, the alternative approach is to use a PWM to predict locations and binding scores. The output is (1) an image visualizing where the predicted sites are along with their affinity or PWM-binding score, and (2) a table with every binding site, its location, direction, affinity and a unique site identifier.
Links:
Tutorial Video
Documentation
Enter Enhancer DNA sequence(s)
Enhancer DNA Alignment Table
*
At least two DNA sequences to be analyzed. We suggest only inputting the alignment +/- 15 bp from where the genetic variation of interest occurs. if this is a SNV, you would simply input the 30bp window of the alignment containing the variant. If this is a deletion, you would add 15 bp upstream of the first - and 15bp downstream of the last -.
Manually enter table
Upload files
download example
DNA Name
*
DNA Alignment
*
Functional Group
*
wild-type
test
Add Row
Enter Enhancer Functional Group Table
*
Tab-separated file which labels each functional group. Functional group can be either wild-type, control, test, or na. If na, all enhancers associated with that label will be removed from the analysis. Binding sites are searched for within the test group that are not present within the wild-type or control group. At a minimum both of these requirements must be met, (1) at least one control or wild-type must be provided; (2) at least one test must be provided.
Choose TF Reference Data
Relative Affinity
motifs/PWMs
*
Input one of the following TF datasets:
Do not use relative affinity
All TFs
Enter your own TFs
Select TFs within tissues
Select all TFs from dataset using the selected normalization.
Affinity Normalization
Signal-to-noise
Relative
TF Family
*
Select TF family.
TF PBM Dataset
*
Select TF PBM dataset.
Core Site
*
IUPAC formatted core binding site.
Affinity Normalization
*
Select normalization method.
Select family
Select dataset
Select core site
Signal-to-noise
Relative
Add Row
Select Organism
Select Time
Select Organ
Select Cell
Add Selection
Groups
TFs to Analyze
Affinity Normalization
Signal-to-noise
Relative
Motif input file
*
JASPAR formatted file with multiple PWMs. You can generate a PWM with the
Generate Motif Database
tool.
My Motif databases
or
Choose Preloaded Database
Jaspar Vertebrates 2024
HOCOMOCO13 Core Motifs
or
download example
Pwm minimum score
*
Enter the minimum PWM score required for analysis. Default is 0.8.
*
Select PWM annotation method:
Do not use PWMs
All TFs
Selected TFs based on keywords
Subset TFs based on expression data
database to use
Either JASPAR or HOCOMOCO.
Choose Database
Jaspar Vertebrates 2024
HOCOMOCO13 Core Motifs
download example
Select Organism
Select Family
Select Type
Select Factor
Add Selection
Selected Motif Categories
Motifs to Include
List of keywords to filter
Keywords to indicate which PWMs to filter for. Keywords can either be TF name, family, or matrix ID.
Select Organism
Select Time
Select Organ
Select Cell
Add Selection
Groups
TFs to Analyze
Affinity Normalization
Signal-to-noise
Relative
Background nucleotide frequencies
What background frequencies of nucleotides. Description of background frequencies here.
Human genome
Mouse genome
Choose your own
A:
T:
G:
C:
Pwm minimum score
Enter the minimum PWM score required for analysis. Default is 0.8.
Other Parameters
Hypothesis
*
Both
GOF
LOF
Minimum binding change
*
Enter the minimum binding change threshold for analysis.
Submit