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A generalized linear model for peak calling in ChIP-Seq data
Jialin Xu, Yu Zhang
Statistics
Institute for Computational and Data Sciences (ICDS)
Huck Institutes of the Life Sciences
Penn State Cancer Institute
Cancer Institute, Mechanisms of Carcinogenesis
Research output
:
Contribution to journal
›
Article
›
peer-review
5
Scopus citations
Overview
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Dive into the research topics of 'A generalized linear model for peak calling in ChIP-Seq data'. Together they form a unique fingerprint.
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Keyphrases
Sequence Data
100%
Massively Parallel Sequencing
100%
Chromatin Immunoprecipitation (ChIP)
100%
Generalized Linear Model
100%
Peak Calling
100%
Genomic Location
40%
Protein-DNA Interaction
40%
Multiple Peaks
20%
Binding Site
20%
Genome Sequencing
20%
DNA Sequencing
20%
Genetic Structure
20%
Local Region
20%
Maximum Likelihood
20%
Interaction Events
20%
Count Data
20%
Binding Profile
20%
Negative Binomial Distribution
20%
Sequencing Data Analysis
20%
Multiple Binding Sites
20%
Sequence Content
20%
Neuroscience
Immunoprecipitation
100%
Deep Sequencing
100%
Generalized Linear Model
100%
Peak Calling
100%
Binding Site
40%
Protein DNA Interaction
40%
DNA Sequencing
20%
Biochemistry, Genetics and Molecular Biology
Deep Sequencing
100%
Chromatin Immunoprecipitation
100%
Peak Calling
100%
Binding Site
40%
Protein-DNA Interaction
40%
DNA Sequence
20%
Genomic Structure
20%
Binomial Distribution
20%
Engineering
Binding Site
100%
Strand
50%
Observed Data
50%
Local Region
50%
Maximum Likelihood
50%
Peak Signal
50%
Binomial Distribution
50%
Computer Science
maximum-likelihood
100%
Binomial Distribution
100%