Introduction

ChIP-Seq is used to analyze protein-DNA interactions and gene expression analysis. It is routinely employed to characterize transcription factors and other DNA binding protein, and study chromatin structure. Variations of ChIP-Seq are used to study protein/RNA interactions (e.g., CLIP-Seq).

ChIP-Seq data analysis requires a reference genome sequence.

Workflow

Following is a list of common analysis items for ChIP-Seq. One of our expert bioinformaticians will work closely with you to identify a custom analysis workflow most appropriate for your project.

1) Experiment design consultation

2) Data QC and clean up

3) Alignment to a reference with mapping statistics

4) Peaking calling with or without control samples

5) Gene assignment and peak annotation

6) Data clustering and visualization

7) Motif analysis

8) Pathway and network analysis

9) SNP discovery

10) Written project report with analysis methods, publication-ready graphics, and references

Turn-around Time

Upon data receipt, we usually finish a typical CHIP-Seq analysis project in 2-3 days. The actual turn-around time, however, is highly dependent on sample number, data amount, and project complexity.

Publications

Publications below are representative research or review papers that will help you understand how CHIP-Seq is employed in biomedical research.

• Johnson, DS. et al. (2007) Genome-wide mapping of in vivo protein–DNA interactions. Science 316: 1497–1502.
• Robertson, G. et al.(2007) Genome-wide profiles of STAT1 DNA association using chromatin immunoprecipitation and massively parallel sequencing. Nature Methods 4: 651–657.
• Sanford, JR. et al. (2009) Splicing facor SFRS1 recognizes a functionally diverse landscape of RNA transcripts. Genome Res. 19(3):381-94.

FAQ

What kind of reads should I use for my ChIP-Seq experiment?

Single-end 36-bp reads are mostly commonly used in ChIP-Seq experiment. Pair-end reads are often used in ChIP-Seq experiments.

How many reads do I need for my ChIP-Seq experiment?

For mammalian genomes, we recommend ~20M reads or more for each sample. We encourage you to Contact one of our expert bioinformaticians to discuss an optimal read requirement for your ChIP-Seq project.