Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

A computational genomics approach to identify cis-regulatory modules - a case study using E2F1

ABSTRACT: We first trained a set of experimentally identified E2F1 targets by a ChIPModules approach, the identified module of E2F1 and AP-2alpha was validated by ChIP-chip assays. We have performed 3 sets of ChIP-chip experiments in MCF-7 for E2F1 and AP-2alpha respectively. The common genes bound by both E2F1 and AP-2alpha were then identified as a co-localized set of genes. We also performed ChIP-PCR conformation for randomly selected 10 targets.

ORGANISM(S): Homo sapiens

SUBMITTER: Alina Rabinovich

PROVIDER: E-GEOD-5175 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

A computational genomics approach to identify cis-regulatory modules from chromatin immunoprecipitation microarray data--a case study using E2F1.

Jin Victor X VX Rabinovich Alina A Squazzo Sharon L SL Green Roland R Farnham Peggy J PJ

Genome research 20061019 12

Advances in high-throughput technologies, such as ChIP-chip, and the completion of human and mouse genomic sequences now allow analysis of the mechanisms of gene regulation on a systems level. In this study, we have developed a computational genomics approach (termed ChIPModules), which begins with experimentally determined binding sites and integrates positional weight matrices constructed from transcription factor binding sites, a comparative genomics approach, and statistical learning methods ...[more]

PMID: 17053090

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Project description:The goals of the study were to assess array platform performance and analysis algorithm performance. The most widely used method for detecting genome-wide protein-DNA interactions is chromatin immunoprecipitation on tiling microarrays, commonly known as ChIP-chip. Here, we conducted the first objective analysis of tiling array platforms, amplification procedures, and signal detection algorithms in a simulated ChIP-chip experiment. Mixtures of human genomic DNA and "spike-ins" comprised of nearly 100 human sequences at various concentrations were hybridized to four tiling array platforms by eight independent groups. Blind to the number of spike-ins, their locations, and the range of concentrations, each group made predictions of the spike-in locations. We found that microarray platform choice is not the primary determinant of overall performance. In fact, variation in performance between labs, protocols and algorithms within the same array platform was greater than the variation in performance between array platforms. However, each array platform had unique performance characteristics that varied with tiling resolution and the number of replicates, which have implications for cost versus detection power. Long oligonucleotide arrays were slightly more sensitive at detecting very low enrichment. On all platforms, simple sequence repeats and genome redundancy tended to result in false positives. LM-PCR and WGA, the most popular sample amplification techniques, reproduced relative enrichment levels with high fidelity. Performance among signal detection algorithms was heavily dependent on array platform. The spike-in DNA samples and the data presented here provide a stable benchmark against which future ChIP platforms, protocol improvements, and analysis methods can be evaluated. Keywords: ChIP-chip, competition, artificial DNA For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf DNA samples had spike-in DNA added to simulate peaks in ChIP-chip experiments. Same DNA samples used in the arrays in this Series; these are technical array replicates.

Dataset Information

A computational genomics approach to identify cis-regulatory modules - a case study using E2F1

Publications

A computational genomics approach to identify cis-regulatory modules from chromatin immunoprecipitation microarray data--a case study using E2F1.

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