Title |
ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia
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Published in |
Genome Research, September 2012
|
DOI | 10.1101/gr.136184.111 |
Pubmed ID | |
Authors |
Stephen G. Landt, Georgi K. Marinov, Anshul Kundaje, Pouya Kheradpour, Florencia Pauli, Serafim Batzoglou, Bradley E. Bernstein, Peter Bickel, James B. Brown, Philip Cayting, Yiwen Chen, Gilberto DeSalvo, Charles Epstein, Katherine I. Fisher-Aylor, Ghia Euskirchen, Mark Gerstein, Jason Gertz, Alexander J. Hartemink, Michael M. Hoffman, Vishwanath R. Iyer, Youngsook L. Jung, Subhradip Karmakar, Manolis Kellis, Peter V. Kharchenko, Qunhua Li, Tao Liu, X. Shirley Liu, Lijia Ma, Aleksandar Milosavljevic, Richard M. Myers, Peter J. Park, Michael J. Pazin, Marc D. Perry, Debasish Raha, Timothy E. Reddy, Joel Rozowsky, Noam Shoresh, Arend Sidow, Matthew Slattery, John A. Stamatoyannopoulos, Michael Y. Tolstorukov, Kevin P. White, Simon Xi, Peggy J. Farnham, Jason D. Lieb, Barbara J. Wold, Michael Snyder |
Abstract |
Chromatin immunoprecipitation (ChIP) followed by high-throughput DNA sequencing (ChIP-seq) has become a valuable and widely used approach for mapping the genomic location of transcription-factor binding and histone modifications in living cells. Despite its widespread use, there are considerable differences in how these experiments are conducted, how the results are scored and evaluated for quality, and how the data and metadata are archived for public use. These practices affect the quality and utility of any global ChIP experiment. Through our experience in performing ChIP-seq experiments, the ENCODE and modENCODE consortia have developed a set of working standards and guidelines for ChIP experiments that are updated routinely. The current guidelines address antibody validation, experimental replication, sequencing depth, data and metadata reporting, and data quality assessment. We discuss how ChIP quality, assessed in these ways, affects different uses of ChIP-seq data. All data sets used in the analysis have been deposited for public viewing and downloading at the ENCODE (http://encodeproject.org/ENCODE/) and modENCODE (http://www.modencode.org/) portals. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 8 | 32% |
Germany | 2 | 8% |
Spain | 2 | 8% |
United Kingdom | 1 | 4% |
Canada | 1 | 4% |
Japan | 1 | 4% |
Unknown | 10 | 40% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 16 | 64% |
Members of the public | 9 | 36% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 74 | 2% |
United Kingdom | 23 | <1% |
Germany | 17 | <1% |
France | 12 | <1% |
Spain | 10 | <1% |
Italy | 9 | <1% |
Netherlands | 7 | <1% |
China | 6 | <1% |
Mexico | 5 | <1% |
Other | 51 | 2% |
Unknown | 3078 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 895 | 27% |
Researcher | 792 | 24% |
Student > Master | 363 | 11% |
Student > Bachelor | 252 | 8% |
Student > Doctoral Student | 137 | 4% |
Other | 473 | 14% |
Unknown | 380 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 1407 | 43% |
Biochemistry, Genetics and Molecular Biology | 897 | 27% |
Medicine and Dentistry | 154 | 5% |
Computer Science | 145 | 4% |
Neuroscience | 55 | 2% |
Other | 200 | 6% |
Unknown | 434 | 13% |