@inproceedings{164adbc3c6cd48d4b8898e53fd152ccf,
title = "A comprehensive analysis workflow for genome-wide screening data from ChIP-sequencing experiments",
abstract = "ChIP-sequencing is a new technique for generating short DNA sequences useful in analyzing DNA-protein interactions and carrying out genome- wide studies. Although there are some studies to process and analyze ChIP-sequencing data, a complete workflow has not been reported yet. The size of the data and broad range of biological questions are the main challenges to establish a data analysis workflow for ChIP-sequencing data. In this paper, we present the ChIP-sequencing data analysis workflow that we developed at the Ohio State University Comprehensive Cancer Center Bioinformatics Shared Resources. This pipeline utilizes 1) use of different mapping algorithms such as Eland, MapReads, SeqMap, RMAP to align short sequence reads to the reference genome 2) a novel normalization algorithm to detect significant binding densities and to compare binding densities of different experiments 3) gene database mapping and 3D binding density visualization 4) distributed computing and high performance computing (HPC) supprt.",
keywords = "ChIP-seq, Normalization, Parallelization, Short sequence mapping, Visualization, Workflow",
author = "Ozer, {Hatice Gulcin} and Doruk Bozdaǧ and Terry Camerlengo and Jiejun Wu and Huang, {Yi Wen} and Tim Hartley and Parvin, {Jeffrey D.} and Tim Huang and Catalyurek, {Umit V.} and Kun Huang",
year = "2009",
doi = "10.1007/978-3-642-00727-9_30",
language = "English (US)",
isbn = "3642007260",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "320--330",
booktitle = "Bioinformatics and Computational Biology - First International Conference, BICoB 2009, Proceedings",
note = "1st International Conference on Bioinformatics and Computational Biology, BICoB 2009 ; Conference date: 08-04-2009 Through 10-04-2009",
}