The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Identifying ChIP-seq enrichment using MACS
Open accessAbstract
Model-based analysis of ChIP-seq (MACS) is a computational algorithm that identifies genome-wide locations of transcription/chromatin factor binding or histone modification from ChIP-seq data. MACS consists of four steps: removing redundant reads, adjusting read position, calculating peak enrichment and estimating the empirical false discovery rate (FDR). In this protocol, we provide a detailed demonstration of how to install MACS and how to use it to analyze three common types of ChIP-seq data sets with different characteristics: the sequence-specific transcription factor FoxA1, the histone modification mark H3K4me3 with sharp enrichment and the H3K36me3 mark with broad enrichment. We also explain how to interpret and visualize the results of MACS analyses. The algorithm requires ∼3 GB of RAM and 1.5 h of computing time to analyze a ChIP-seq data set containing 30 million reads, an estimate that increases with sequence coverage. MACS is open source and is available from http://liulab.dfci.harvard.edu/MACS/.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607
Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.
Langmead, B., Trapnell, C., Pop, M., & Salzberg, S. L. (2009) · Genome Biology · doi:10.1186/gb-2009-10-3-r25 · Cited by 21,849
The Human Genome Browser at UCSC
Kent, W. J., Sugnet, C. W., Furey, T. S., Roskin, K. M., Pringle, T. H., Zahler, A. M., & Haussler, A. D. (2002) · Genome Research · doi:10.1101/gr.229102 · Cited by 10,400
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
The ENCODE Project Consortium (2007) · Nature · doi:10.1038/nature05874 · Cited by 5,223
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
ChIP–seq: advantages and challenges of a maturing technology
Park, P. J. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2641 · Cited by 2,217
Robertson, 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
Fejes, A. P., Robertson, G., Bilenky, M., Varhol, R., Bainbridge, M., & Jones, S. J. M. (2008) · Bioinformatics · doi:10.1093/bioinformatics/btn305 · Cited by 272
Research works printed but not linked: 32
- Mardis, E.R. ChIP-seq: welcome to the new frontier. Nat. Methods 4, 613–614 (2007). · DOI
- Johnson, D.S., Mortazavi, A., Myers, R.M. & Wold, B. Genome-wide mapping of in vivo protein-DNA interactions. Science 316, 1497–1502 (2007). · DOI · Paper page
- Dohm, J.C., Lottaz, C., Borodina, T. & Himmelbauer, H. Substantial biases in ultra-short read data sets from high-throughput DNA sequencing. Nucleic Acids Res. 36, e105 (2008). · DOI · Paper page
- Rozowsky, J. et al. PeakSeq enables systematic scoring of ChIP-seq experiments relative to controls. Nat. Biotech. 27, 66–75 (2009). · DOI · Paper page
- Vega, V.B., Cheung, E., Palanisamy, N. & Sung, W.-K. Inherent signals in sequencing-based chromatin-immunoprecipitation control libraries. PLoS ONE 4, e5241 (2009). · DOI
- Liu, E.T., Pott, S. & Huss, M. Q&A: ChIP-seq technologies and the study of gene regulation. BMC Biol. 8, 56 (2010). · DOI
- Teytelman, L. et al. Impact of chromatin structures on DNA processing for genomic analyses. PLoS ONE 4, e6700 (2009). · DOI
- Nix, D.A., Courdy, S.J. & Boucher, K.M. Empirical methods for controlling false positives and estimating confidence in ChIP-seq peaks. BMC Bioinformatics 9, 523 (2008). · DOI
- Zhang, Y. et al. Model-based analysis of ChIP-seq (MACS). Genome Biol. 9, R137–R137 (2008). · DOI · Paper page
- Tavares, L. et al. RYBP-PRC1 complexes mediate H2A ubiquitylation at polycomb target sites independently of PRC2 and H3K27me3. Cell 148, 664–678 (2012). · DOI · Paper page
- Ulitsky, I., Shkumatava, A., Jan, C.H., Sive, H. & Bartel, D.P. Conserved function of lincRNAs in vertebrate embryonic development despite rapid sequence evolution. Cell 147, 1537–1550 (2011). · DOI · Paper page
- He, H.H. et al. Nucleosome dynamics define transcriptional enhancers. Nat. Genet. 42, 343–347 (2010). · DOI · Paper page
- Zheng, W., Zhao, H., Mancera, E., Steinmetz, L.M. & Snyder, M. Genetic analysis of variation in transcription factor binding in yeast. Nature 464, 1187–1191 (2010). · DOI
- Noordermeer, D. et al. The dynamic architecture of Hox gene clusters. Science 334, 222–225 (2011). · DOI · Paper page
- Welboren, W.-J. et al. ChIP-seq of ERα and RNA polymerase II defines genes differentially responding to ligands. EMBO J. 28, 1418–1428 (2009). · DOI · Paper page
- Liu, T. et al. Cistrome: an integrative platform for transcriptional regulation studies. Genome Biol. 12, R83 (2011). · DOI · Paper page
- Jothi, R., Cuddapah, S., Barski, A., Cui, K. & Zhao, K. Genome-wide identification of in vivo protein–DNA binding sites from ChIP-seq data. Nucleic Acids Res. 36, 5221–5231 (2008). · DOI · Paper page
- Ji, H. et al. An integrated software system for analyzing ChIP-chip and ChIP-seq data. Nat. Biotech. 26, 1293–1300 (2008). · DOI · Paper page
- Zang, C. et al. A clustering approach for identification of enriched domains from histone modification ChIP-seq data. Bioinformatics 25, 1952–1958 (2009). · DOI · Paper page
- Valouev, A. et al. Genome-wide analysis of transcription factor binding sites based on ChIP-seq data. Nat. Methods 5, 829–834 (2008). · DOI · Paper page
- Laajala, T.D. et al. A practical comparison of methods for detecting transcription factor binding sites in ChIP-seq experiments. BMC Genomics 10, 618 (2009). · DOI
- Wilbanks, E.G. & Facciotti, M.T. Evaluation of algorithm performance in ChIP-seq peak detection. PLoS ONE 5, e11471 (2010). · DOI · Paper page
- Pepke, S., Wold, B. & Mortazavi, A. Computation for ChIP-seq and RNA-seq studies. Nat. Methods 6, S22–S32 (2009). · DOI · Paper page
- Barski, A. & Zhao, K. Genomic location analysis by ChIP-seq. J. Cell Biochem. 107, 11–18 (2009). · DOI · Paper page
- Malone, B.M., Tan, F., Bridges, S.M. & Peng, Z. Comparison of four ChIP-seq analytical algorithms using rice endosperm H3K27 trimethylation profiling data. PLoS ONE 6, e25260 (2011). · DOI
- Chen, Y. et al. Systematic evaluation of factors influencing ChIP-seq fidelity. Nat. Methods 9, 609–614 (2012). · DOI
- Stitzel, M.L. et al. Global epigenomic analysis of primary human pancreatic islets provides insights into type 2 diabetes susceptibility loci. Cell Metab. 12, 443–455 (2010). · DOI · Paper page
- Sati, S. et al. High resolution methylome map of rat indicates role of intragenic DNA methylation in identification of coding region. PLoS ONE 7, e31621 (2012). · DOI
- Li, N. et al. Whole genome DNA methylation analysis based on high throughput sequencing technology. Methods 52, 203–212 (2010). · DOI · Paper page
- Salmon-Divon, M., Dvinge, H., Tammoja, K. & Bertone, P. PeakAnalyzer: genome-wide annotation of chromatin binding and modification loci. BMC Bioinformatics 11, 415 (2010). · DOI · Paper page
- Robinson, J.T. et al. Integrative genomics viewer. Nat. Biotech. 29, 24–26 (2011). · DOI · Paper page
- Nicol, J.W., Helt, G.A., Blanchard, S.G. Jr ., Raja, A. & Loraine, A.E. The integrated genome browser: free software for distribution and exploration of genome-scale datasets. Bioinformatics 25, 2730–2731 (2009). · DOI · Paper page
Cited by
deepTools2: a next generation web server for deep-sequencing data analysis
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
Genetic studies of body mass index yield new insights for obesity biology
Study, T. L. C., Locke, A. E., The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The, G. L. G. C., The, I. C. B. P., The MAGIC Investigators, The MuTHER Consortium, et al. (2015) · Nature · doi:10.1038/nature14177 · Cited by 4,534
In vivo genome editing using Staphylococcus aureus Cas9
Ran, F. A., Cong, L., Yan, W. X., Scott, D. A., Gootenberg, J. S., Kriz, A. J., Zetsche, B., Shalem, O., Wu, X., Makarova, K. S., et al. (2015) · Nature · doi:10.1038/nature14299 · Cited by 2,687
New genetic loci link adipose and insulin biology to body fat distribution
The ADIPOGen Consortium, Shungin, D., The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The GEFOS Consortium, The GENIE Consortium, The, G. L. G. C., The, I. C. B. P., The International Endogene Consortium, Study, T. L. C., et al. (2015) · Nature · doi:10.1038/nature14132 · Cited by 1,580
Activity-by-contact model of enhancer–promoter regulation from thousands of CRISPR perturbations
Fulco, C. P., Nasser, J., Jones, T. R., Munson, G., Bergman, D. T., Subramanian, V., Grossman, S. R., Anyoha, R., Doughty, B. R., Patwardhan, T. A., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0538-0 · Cited by 1,111
The cohesin release factor WAPL restricts chromatin loop extension
Haarhuis, J. H. I., van der Weide, R. H., Blomen, V. A., Yáñez-Cuna, J. O., Amendola, M., van Ruiten, M. S., Krijger, P. H. L., Teunissen, H., Medema, R. H., van Steensel, B., et al. (2017) · Cell · doi:10.1016/j.cell.2017.04.013 · Cited by 793
Inflammatory memory sensitizes skin epithelial stem cells to tissue damage
Naik, S., Larsen, S. B., Gomez, N. C., Alaverdyan, K., Sendoel, A., Yuan, S., Polak, L., Kulukian, A., Chai, S., & Fuchs, E. (2017) · Nature · doi:10.1038/nature24271 · Cited by 745
The histone H3.3K27M mutation in pediatric glioma reprograms H3K27 methylation and gene expression
Chan, K.-M., Fang, D., Gan, H., Hashizume, R., Yu, C., Schroeder, M., Gupta, N., Mueller, S., James, C. D., Jenkins, R., et al. (2013) · Genes & Development · doi:10.1101/gad.217778.113 · Cited by 707
A Single Oncogenic Enhancer Rearrangement Causes Concomitant EVI1 and GATA2 Deregulation in Leukemia
Gröschel, S., Sanders, M. A., Hoogenboezem, R., de Wit, E., Bouwman, B. A. M., Erpelinck, C., van der Velden, V. H. J., Havermans, M., Avellino, R., van Lom, K., et al. (2014) · Cell · doi:10.1016/j.cell.2014.02.019 · Cited by 687
Loss of epigenetic information as a cause of mammalian aging
Yang, J.-H., Hayano, M., Griffin, P. T., Amorim, J. A., Bonkowski, M. S., Apostolides, J. K., Salfati, E. L., Blanchette, M., Munding, E. M., Bhakta, M., et al. (2023) · Cell · doi:10.1016/j.cell.2022.12.027 · Cited by 643
Single-Molecule Dynamics of Enhanceosome Assembly in Embryonic Stem Cells
Chen, J., Zhang, Z., Li, L., Chen, B.-C., Revyakin, A., Hajj, B., Legant, W., Dahan, M., Lionnet, T., Betzig, E., et al. (2014) · Cell · doi:10.1016/j.cell.2014.01.062 · Cited by 602
Target analysis by integration of transcriptome and ChIP-seq data with BETA
Wang, S., Sun, H., Ma, J., Zang, C., Wang, C., Wang, J., Tang, Q., Meyer, C. A., Zhang, Y., & Liu, X. S. (2013) · Nature Protocols · doi:10.1038/nprot.2013.150 · Cited by 544
Self-citationH3K4me3 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
The structural basis for cohesin–CTCF-anchored loops
Li, Y., Haarhuis, J. H. I., Sedeño Cacciatore, Á., Oldenkamp, R., van Ruiten, M. S., Willems, L., Teunissen, H., Muir, K. W., de Wit, E., Rowland, B. D., et al. (2020) · Nature · doi:10.1038/s41586-019-1910-z · Cited by 459
Mostafavi, S., Gaiteri, C., Sullivan, S. E., White, C. C., Tasaki, S., Xu, J., Taga, M., Klein, H.-U., Patrick, E., Komashko, V., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-018-0154-9 · Cited by 509
The androgen receptor cistrome is extensively reprogrammed in human prostate tumorigenesis
Pomerantz, M. M., Li, F., Takeda, D. Y., Lenci, R., Chonkar, A., Chabot, M., Cejas, P., Vazquez, F., Cook, J., Shivdasani, R. A., et al. (2015) · Nature Genetics · doi:10.1038/ng.3419 · Cited by 470
A nuclease that mediates cell death induced by DNA damage and poly(ADP-ribose) polymerase-1
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
The Long Noncoding RNA RMST Interacts with SOX2 to Regulate Neurogenesis
Ng, S.-Y., Bogu, G. K., Soh, B. S., & Stanton, L. W. (2013) · Molecular Cell · doi:10.1016/j.molcel.2013.07.017 · Cited by 404
Absolute quantification of single-base m6A methylation in the mammalian transcriptome using GLORI
Liu, C., Sun, H., Yi, Y., Shen, W., Li, K., Xiao, Y., Li, F., Li, Y., Hou, Y., Lu, B., et al. (2023) · Nature Biotechnology · doi:10.1038/s41587-022-01487-9 · Cited by 386
Genetic dissection of the α-globin super-enhancer in vivo
Hay, D., Hughes, J. R., Babbs, C., Davies, J. O. J., Graham, B. J., Hanssen, L. L. P., Kassouf, M. T., Oudelaar, A. M., Sharpe, J. A., Suciu, M. C., et al. (2016) · Nature Genetics · doi:10.1038/ng.3605 · Cited by 385
Meng, J., Lu, Z., Liu, H., Zhang, L., Zhang, S., Chen, Y., Rao, M. K., & Huang, Y. (2014) · Methods · doi:10.1016/j.ymeth.2014.06.008 · Cited by 375
The RNA m6A reader YTHDC1 silences retrotransposons and guards ES cell identity
Liu, J., Gao, M., He, J., Wu, K., Lin, S., Jin, L., Chen, Y., Liu, H., Shi, J., Wang, X., et al. (2021) · Nature · doi:10.1038/s41586-021-03313-9 · Cited by 365
Heterogeneity in old fibroblasts is linked to variability in reprogramming and wound healing
Mahmoudi, S., Mancini, E., Xu, L., Moore, A., Jahanbani, F., Hebestreit, K., Srinivasan, R., Li, X., Devarajan, K., Prélot, L., et al. (2019) · Nature · doi:10.1038/s41586-019-1658-5 · Cited by 285
Pharmacological targeting of the Wdr5-MLL interaction in C/EBPα N-terminal leukemia
Grebien, F., Vedadi, M., Getlik, M., Giambruno, R., Grover, A., Avellino, R., Skucha, A., Vittori, S., Kuznetsova, E., Smil, D., et al. (2015) · Nature Chemical Biology · doi:10.1038/nchembio.1859 · Cited by 284
Super-Enhancer-Mediated RNA Processing Revealed by Integrative MicroRNA Network Analysis
Suzuki, H. I., Young, R. A., & Sharp, P. A. (2017) · Cell · doi:10.1016/j.cell.2017.02.015 · Cited by 284
Single-cell brain organoid screening identifies developmental defects in autism
Li, C., Fleck, J. S., Martins-Costa, C., Burkard, T. R., Themann, J., Stuempflen, M., Peer, A. M., Vertesy, Á., Littleboy, J. B., Esk, C., et al. (2023) · Nature · doi:10.1038/s41586-023-06473-y · Cited by 283
“6) (62) and combined in a common peak set before merging.”
BackgroundBroadly permissive intestinal chromatin underlies lateral inhibition and cell plasticity
Kim, T.-H., Li, F., Ferreiro-Neira, I., Ho, L.-L., Luyten, A., Nalapareddy, K., Long, H., Verzi, M., & Shivdasani, R. A. (2014) · Nature · doi:10.1038/nature12903 · Cited by 257
TP63-mediated enhancer reprogramming drives the squamous subtype of pancreatic ductal adenocarcinoma
Somerville, T. D. D., Xu, Y., Miyabayashi, K., Tiriac, H., Cleary, C. R., Maia-Silva, D., Milazzo, J. P., Tuveson, D. A., & Vakoc, C. R. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.10.051 · Cited by 225
A Platform for Rapid Exploration of Aging and Diseases in a Naturally Short-Lived Vertebrate
Harel, I., Benayoun, B. A., Machado, B., Singh, P. P., Hu, C.-K., Pech, M. F., Valenzano, D. R., Zhang, E., Sharp, S. C., Artandi, S. E., et al. (2015) · Cell · doi:10.1016/j.cell.2015.01.038 · Cited by 232
Ko, Y.-A., Mohtat, D., Suzuki, M., Park, A. S. D., Izquierdo, M. C., Han, S. Y., Kang, H. M., Si, H., Hostetter, T., Pullman, J. M., et al. (2013) · Genome Biology · doi:10.1186/gb-2013-14-10-r108 · Cited by 225
Determinants of Histone H3K4 Methylation Patterns
Soares, L. M., He, P. C., Chun, Y., Suh, H., Kim, T., & Buratowski, S. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.10.013 · Cited by 209
Gontier, G., Iyer, M., Shea, J. M., Bieri, G., Wheatley, E. G., Ramalho-Santos, M., & Villeda, S. A. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.02.001 · Cited by 197
Genome-wide characterization of the routes to pluripotency
Hussein, S. M. I., Puri, M. C., Tonge, P. D., Benevento, M., Corso, A. J., Clancy, J. L., Mosbergen, R., Li, M., Lee, D.-S., Cloonan, N., et al. (2014) · Nature · doi:10.1038/nature14046 · Cited by 197
Autophagy Regulation of Metabolism Is Required for CD8+ T Cell Anti-tumor Immunity
DeVorkin, L., Pavey, N., Carleton, G., Comber, A., Ho, C., Lim, J., McNamara, E., Huang, H., Kim, P., Zacharias, L. G., et al. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.03.037 · Cited by 185
Direct GR Binding Sites Potentiate Clusters of TF Binding across the Human Genome
Vockley, C. M., D’Ippolito, A. M., McDowell, I. C., Majoros, W. H., Safi, A., Song, L., Crawford, G. E., & Reddy, T. E. (2016) · Cell · doi:10.1016/j.cell.2016.07.049 · Cited by 182
Transcriptional response to stress is pre-wired by promoter and enhancer architecture
Vihervaara, A., Mahat, D. B., Guertin, M. J., Chu, T., Danko, C. G., Lis, J. T., & Sistonen, L. (2017) · Nature Communications · doi:10.1038/s41467-017-00151-0 · Cited by 164
Long-range single-molecule mapping of chromatin accessibility in eukaryotes
Shipony, Z., Marinov, G. K., Swaffer, M. P., Sinnott-Armstrong, N. A., Skotheim, J. M., Kundaje, A., & Greenleaf, W. J. (2020) · Nature Methods · doi:10.1038/s41592-019-0730-2 · Cited by 160
Independence of chromatin conformation and gene regulation during Drosophila dorsoventral patterning
Ing-Simmons, E., Vaid, R., Bing, X. Y., Levine, M., Mannervik, M., & Vaquerizas, J. M. (2021) · Nature Genetics · doi:10.1038/s41588-021-00799-x · Cited by 159
High-Resolution Epigenomic Atlas of Human Embryonic Craniofacial Development
Wilderman, A., VanOudenhove, J., Kron, J., Noonan, J. P., & Cotney, J. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.03.129 · Cited by 139
Knaupp, A. S., Buckberry, S., Pflueger, J., Lim, S. M., Ford, E., Larcombe, M. R., Rossello, F. J., de Mendoza, A., Alaei, S., Firas, J., et al. (2017) · Cell Stem Cell · doi:10.1016/j.stem.2017.11.007 · Cited by 127
STAT3-YAP/TAZ signaling in endothelial cells promotes tumor angiogenesis
Shen, Y., Wang, X., Liu, Y., Singhal, M., Gürkaşlar, C., Valls, A. F., Lei, Y., Hu, W., Schermann, G., Adler, H., et al. (2021) · Science Signaling · doi:10.1126/scisignal.abj8393 · Cited by 121
Pachano, T., Sánchez-Gaya, V., Ealo, T., Mariner-Faulí, M., Bleckwehl, T., Asenjo, H. G., Respuela, P., Cruz-Molina, S., Muñoz-San Martín, M., Haro, E., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00888-x · Cited by 116
Brazhnik, K., Sun, S., Alani, O., Kinkhabwala, M., Wolkoff, A. W., Maslov, A. Y., Dong, X., & Vijg, J. (2020) · Science Advances · doi:10.1126/sciadv.aax2659 · Cited by 114
Chromatin conformation remains stable upon extensive transcriptional changes driven by heat shock
Ray, J., Munn, P. R., Vihervaara, A., Lewis, J. J., Ozer, A., Danko, C. G., & Lis, J. T. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1901244116 · Cited by 109
A tissue injury sensing and repair pathway distinct from host pathogen defense
Liu, S., Hur, Y. H., Cai, X., Cong, Q., Yang, Y., Xu, C., Bilate, A. M., Gonzales, K. A. U., Parigi, S. M., Cowley, C. J., et al. (2023) · Cell · doi:10.1016/j.cell.2023.03.031 · Cited by 108
Bhlhe40 and Bhlhe41 Transcription Factors Regulate Alveolar Macrophage Self‐renewal and Identity
Rauschmeier, R., Gustafsson, C., Reinhardt, A., A‐Gonzalez, N., Tortola, L., Cansever, D., Subramanian, S., Taneja, R., Rossner, M. J., Sieweke, M. H., et al. (2019) · The EMBO Journal · doi:10.15252/embj.2018101233 · Cited by 102
McClatchy, J., Strogantsev, R., Wolfe, E., Lin, H. Y., Mohammadhosseini, M., Davis, B. A., Eden, C., Goldman, D., Fleming, W. H., Conley, P., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-43697-y · Cited by 95
Kang, Y., Kim, Y. W., Kang, J., & Kim, A. (2021) · The FASEB Journal · doi:10.1096/fj.202100488r · Cited by 93
AtrR Is an Essential Determinant of Azole Resistance in Aspergillus fumigatus
Paul, S., Stamnes, M., Thomas, G. H., Liu, H., Hagiwara, D., Gomi, K., Filler, S. G., & Moye-Rowley, W. S. (2019) · mBio · doi:10.1128/mbio.02563-18 · Cited by 91
Interconversion between Tumorigenic and Differentiated States in Acute Myeloid Leukemia
McKenzie, M. D., Ghisi, M., Oxley, E. P., Ngo, S., Cimmino, L., Esnault, C., Liu, R., Salmon, J. M., Bell, C. C., Ahmed, N., et al. (2019) · Cell Stem Cell · doi:10.1016/j.stem.2019.07.001 · Cited by 91
Targeted design of synthetic enhancers for selected tissues in the Drosophila embryo
de Almeida, B. P., Schaub, C., Pagani, M., Secchia, S., Furlong, E. E. M., & Stark, A. (2024) · Nature · doi:10.1038/s41586-023-06905-9 · Cited by 87
Transcription-dependent cohesin repositioning rewires chromatin loops in cellular senescence
Olan, I., Parry, A. J., Schoenfelder, S., Narita, M., Ito, Y., Chan, A. S. L., Slater, G. S. C., Bihary, D., Bando, M., Shirahige, K., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19878-4 · Cited by 76
UBR5 forms ligand-dependent complexes on chromatin to regulate nuclear hormone receptor stability
Tsai, J. M., Aguirre, J. D., Li, Y.-D., Brown, J., Focht, V., Kater, L., Kempf, G., Sandoval, B., Schmitt, S., Rutter, J. C., et al. (2023) · Molecular Cell · doi:10.1016/j.molcel.2023.06.028 · Cited by 68
Sahu, B., Pihlajamaa, P., Dubois, V., Kerkhofs, S., Claessens, F., & Jänne, O. A. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1401 · Cited by 66
BMP signaling: at the gate between activated melanocyte stem cells and differentiation
Infarinato, N. R., Stewart, K. S., Yang, Y., Gomez, N. C., Pasolli, H. A., Hidalgo, L., Polak, L., Carroll, T. S., & Fuchs, E. (2020) · Genes & Development · doi:10.1101/gad.340281.120 · Cited by 62
Profiling DNA break sites and transcriptional changes in response to contextual fear learning
Stott, R. T., Kritsky, O., & Tsai, L.-H. (2021) · PLOS ONE · doi:10.1371/journal.pone.0249691 · Cited by 62
Kim, S. S., Truong, B., Jagadeesh, K., Dey, K. K., Shen, A. Z., Raychaudhuri, S., Kellis, M., & Price, A. L. (2024) · Nature Communications · doi:10.1038/s41467-024-44742-0 · Cited by 56
Yuan, X., Song, M., Devine, P., Bruneau, B. G., Scott, I. C., & Wilson, M. D. (2018) · Nature Communications · doi:10.1038/s41467-018-07451-z · Cited by 51
HDAC3 functions as a positive regulator in Notch signal transduction
Ferrante, F., Giaimo, B. D., Bartkuhn, M., Zimmermann, T., Close, V., Mertens, D., Nist, A., Stiewe, T., Meier-Soelch, J., Kracht, M., et al. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa088 · Cited by 50
Common Regulatory Targets of NFIA, NFIX and NFIB during Postnatal Cerebellar Development
Fraser, J., Essebier, A., Brown, A. S., Davila, R. A., Harkins, D., Zalucki, O., Shapiro, L. P., Penzes, P., Wainwright, B. J., Scott, M. P., et al. (2020) · The Cerebellum · doi:10.1007/s12311-019-01089-3 · Cited by 46
Polycomb complexes redundantly maintain epidermal stem cell identity during development
Cohen, I., Bar, C., Liu, H., Valdes, V. J., Zhao, D., Galbo, P. M., Silva, J. M., Koseki, H., Zheng, D., & Ezhkova, E. (2021) · Genes & Development · doi:10.1101/gad.345363.120 · Cited by 45
Single-molecule states link transcription factor binding to gene expression
Doughty, B. R., Hinks, M. M., Schaepe, J. M., Marinov, G. K., Thurm, A. R., Rios-Martinez, C., Parks, B. E., Tan, Y., Marklund, E., Dubocanin, D., et al. (2024) · Nature · doi:10.1038/s41586-024-08219-w · Cited by 42
Upadhyaya, B., Larsen, T., Barwari, S., Louwagie, E., Baack, M., & Dey, M. (2017) · Nutrients · doi:10.3390/nu9040407 · Cited by 40
Hemming, M. L., Benson, M. R., Loycano, M. A., Anderson, J. A., Andersen, J. L., Taddei, M. L., Krivtsov, A. V., Aubrey, B. J., Cutler, J. A., Hatton, C., et al. (2022) · Cancer Discovery · doi:10.1158/2159-8290.cd-21-0646 · Cited by 39
3D hotspots of recurrent retroviral insertions reveal long-range interactions with cancer genes
Babaei, S., Akhtar, W., de Jong, J., Reinders, M., & de Ridder, J. (2015) · Nature Communications · doi:10.1038/ncomms7381 · Cited by 37
Cellular reprogramming in vivo initiated by SOX4 pioneer factor activity
Katsuda, T., Sussman, J. H., Ito, K., Katznelson, A., Yuan, S., Takenaka, N., Li, J., Merrell, A. J., Cure, H., Li, Q., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-45939-z · Cited by 33
“The H3K4me3+ regions were annotated with the nearest genes (output of MACS2), and then fi ltered with the list of hepatocyte-highly expressed genes.”
InfluentialErosion of the Epigenetic Landscape and Loss of Cellular Identity as a Cause of Aging in Mammals
Yang, J.-H., Griffin, P. T., Vera, D. L., Apostolides, J. K., Hayano, M., Meer, M. V., Salfati, E. L., Su, Q., Munding, E. M., Blanchette, M., et al. (2019) · doi:10.1101/808642 · Cited by 38
Genome-Wide Target Analyses of Otx2 Homeoprotein in Postnatal Cortex
Sakai, A., Nakato, R., Ling, Y., Hou, X., Hara, N., Iijima, T., Yanagawa, Y., Kuwano, R., Okuda, S., Shirahige, K., et al. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00307 · Cited by 30
Li, S., Yue, Z., & Tanaka, T. U. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.10.009 · Cited by 26
Cheung, K., Barter, M. J., Falk, J., Proctor, C. J., Reynard, L. N., & Young, D. A. (2020) · The FASEB Journal · doi:10.1096/fj.201902061rr · Cited by 23
Enrichment of schizophrenia heritability in both neuronal and glia cell regulatory elements
Tansey, K. E., & Hill, M. J. (2018) · Translational Psychiatry · doi:10.1038/s41398-017-0053-y · Cited by 21
Chromatin accessibility dynamics of myogenesis at single cell resolution
Pliner, H. A., Packer, J., McFaline-Figueroa, J. L., Cusanovich, D. A., Daza, R., Srivatsan, S., Qiu, X., Jackson, D., Minkina, A., Adey, A., et al. (2017) · doi:10.1101/155473 · Cited by 16
Stroynowska-Czerwinska, A. M., Klimczak, M., Pastor, M., Kazrani, A. A., Misztal, K., & Bochtler, M. (2023) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-022-04651-1 · Cited by 14
An allostatic epigenetic memory on chromatin footprints after double-hit acute stress
Caradonna, S. G., Paul, M. R., & Marrocco, J. (2022) · Neurobiology of Stress · doi:10.1016/j.ynstr.2022.100475 · Cited by 13
The SPARC complex defines RNAPII promoters in Trypanosoma brucei
Staneva, D. P., Bresson, S., Auchynnikava, T., Spanos, C., Rappsilber, J., Jeyaprakash, A. A., Tollervey, D., Matthews, K. R., & Allshire, R. C. (2022) · eLife · doi:10.7554/elife.83135 · Cited by 13
Williams, R. M., Taylor, G., Ling, I. T. C., Candido-Ferreira, I., Fountain, D. M., Mayes, S., Ateş-Kalkan, P. S., Haug, J. O., Price, A. J., McKinney, S. A., et al. (2024) · PLOS Biology · doi:10.1371/journal.pbio.3002786 · Cited by 12
Huang, Y., Ge, M.-X., Li, Y.-H., Li, J.-L., Yu, Q., Xiao, F.-H., Ao, H.-S., Yang, L.-Q., Li, J., He, Y., et al. (2022) · Aging and disease · doi:10.14336/ad.2022.1217 · Cited by 12
Łabędzka-Dmoch, K., Bui, T. H. D., Piątkowski, J., Dilling, M., Jagiełło, P., Kabza, W., & Golik, P. (2026) · Molecular Biology and Evolution · doi:10.1093/molbev/msag005 · Cited by 1
Metadata
- Authors
- Feng, J., Liu, T., Qin, B., Zhang, Y., & Liu, X. S.
- Venue
- Nature Protocols
- Published
- 2012-08-30
- Volume
- 7
- Issue
- 9
- Pages
- 1728-1740
- ISSN
- 1750-2799 (ISSN-L)
- 1754-2189
- OpenAlex
- W2093146349
- Cited by
- 1,870
- References
- 10
- FWCI
- 15.22
- Type
- journal article
- Language
- en
- Open access
- green
- Licence
- www.springer.com/tdm (tdm)
- www.springer.com/tdm (vor)
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
