The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Systematic evaluation of factors influencing ChIP-seq fidelity
Open accessAbstract
We evaluated how variations in sequencing depth and other parameters influence interpretation of chromatin immunoprecipitation–sequencing (ChIP-seq) experiments. Using Drosophila melanogaster S2 cells, we generated ChIP-seq data sets for a site-specific transcription factor (Suppressor of Hairy-wing) and a histone modification (H3K36me3). We detected a chromatin-state bias: open chromatin regions yielded higher coverage, which led to false positives if not corrected. This bias had a greater effect on detection specificity than any base-composition bias. Paired-end sequencing revealed that single-end data underestimated ChIP-library complexity at high coverage. Removal of reads originating at the same base reduced false-positives but had little effect on detection sensitivity. Even at mappable-genome coverage depth of ∼1 read per base pair, ∼1% of the narrow peaks detected on a tiling array were missed by ChIP-seq. Evaluation of widely used ChIP-seq analysis tools suggests that adjustments or algorithm improvements are required to handle data sets with deep coverage.
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Mapping and quantifying mammalian transcriptomes by RNA-Seq
Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., & Wold, B. (2008) · Nature Methods · doi:10.1038/nmeth.1226 · Cited by 13,696
Self-citationTandem repeats finder: a program to analyze DNA sequences
Benson, G. (1999) · Nucleic Acids Research · doi:10.1093/nar/27.2.573 · Cited by 9,374
High-Resolution Profiling of Histone Methylations in the Human Genome
Barski, A., Cuddapah, S., Cui, K., Roh, T.-Y., Schones, D. E., Wang, Z., Wei, G., Chepelev, I., & Zhao, K. (2007) · Cell · doi:10.1016/j.cell.2007.05.009 · Cited by 6,845
Genome-wide maps of chromatin state in pluripotent and lineage-committed cells
Mikkelsen, T. S., Ku, M., Jaffe, D. B., Issac, B., Lieberman, E., Giannoukos, G., Alvarez, P., Brockman, W., Kim, T.-K., Koche, R. P., et al. (2007) · Nature · doi:10.1038/nature06008 · Cited by 4,129
Self-citationRobertson, G., Hirst, M., Bainbridge, M., Bilenky, M., Zhao, Y., Zeng, T., Euskirchen, G., Bernier, B., Varhol, R., Delaney, A., et al. (2007) · Nature Methods · doi:10.1038/nmeth1068 · Cited by 1,454
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Ramírez, F., Ryan, D. P., Grüning, B., Bhardwaj, V., Kilpert, F., Richter, A. S., Heyne, S., Dündar, F., & Manke, T. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw257 · Cited by 8,096
Furey, T. S. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3306 · Cited by 835
H3K4me3 breadth is linked to cell identity and transcriptional consistency
Benayoun, B. A., Pollina, E. A., Ucar, D., Mahmoudi, S., Karra, K., Wong, E. D., Devarajan, K., Daugherty, A. C., Kundaje, A. B., Mancini, E., et al. (2014) · Cell · doi:10.1016/j.cell.2014.06.027 · Cited by 536
Mammalian heat shock response and mechanisms underlying its genome-wide transcriptional regulation
Mahat, D. B., Salamanca, H. H., Duarte, F. M., Danko, C. G., & Lis, J. T. (2016) · Molecular Cell · doi:10.1016/j.molcel.2016.02.025 · Cited by 426
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Lam, E. Y. N., Beraldi, D., Tannahill, D., & Balasubramanian, S. (2013) · Nature Communications · doi:10.1038/ncomms2792 · Cited by 455
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Wang, Y., An, R., Umanah, G. K., Park, H., Nambiar, K., Eacker, S. M., Kim, B., Bao, L., Harraz, M. M., Chang, C., et al. (2016) · Science · doi:10.1126/science.aad6872 · Cited by 421
Highly expressed loci are vulnerable to misleading ChIP localization of multiple unrelated proteins
Teytelman, L., Thurtle, D. M., Rine, J., & van Oudenaarden, A. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1316064110 · Cited by 389
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Carroll, T. S., Liang, Z., Salama, R., Stark, R., & de Santiago, I. (2014) · Frontiers in Genetics · doi:10.3389/fgene.2014.00075 · Cited by 254
Active promoters give rise to false positive ‘Phantom Peaks’ in ChIP-seq experiments
Jain, D., Baldi, S., Zabel, A., Straub, T., & Becker, P. B. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv637 · Cited by 156
Analytical tools and current challenges in the modern era of neuroepigenomics
Maze, I., Shen, L., Zhang, B., Garcia, B. A., Shao, N., Mitchell, A., Sun, H., Akbarian, S., Allis, C. D., & Nestler, E. J. (2014) · Nature Neuroscience · doi:10.1038/nn.3816 · Cited by 100
Non-targeted transcription factors motifs are a systemic component of ChIP-seq datasets
Worsley Hunt, R., & Wasserman, W. W. (2014) · Genome Biology · doi:10.1186/s13059-014-0412-4 · Cited by 73
The impact of endogenous content, replicates and pooling on genome capture from faecal samples
Hernandez‐Rodriguez, J., Arandjelovic, M., Lester, J., de Filippo, C., Weihmann, A., Meyer, M., Angedakin, S., Casals, F., Navarro, A., Vigilant, L., et al. (2018) · Molecular Ecology Resources · doi:10.1111/1755-0998.12728 · Cited by 44
Spiesschaert, B., Goldenbogen, B., Taferner, S., Schade, M., Mahmoud, M., Klipp, E., Osterrieder, N., & Azab, W. (2015) · Journal of Virology · doi:10.1128/jvi.01809-15 · Cited by 24
Metadata
- Authors
- Chen, Y., Negre, N., Li, Q., Mieczkowska, J. O., Slattery, M., Liu, T., Zhang, Y., Kim, T.-K., He, H. H., Zieba, J., Ruan, Y., Bickel, P. J., Myers, R. M., Wold, B. J., White, K. P., Lieb, J. D., & Liu, X. S.
- Venue
- Nature Methods
- Published
- 2012-04-22
- Volume
- 9
- Issue
- 6
- Pages
- 609-614
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- OpenAlex
- W2146303939
- Cited by
- 171
- References
- 5
- FWCI
- 8.25
- Type
- journal article
- Language
- en
- Open access
- green
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