Published May 22, 2020
| Version v3
Dataset
Open
Accompanied data files used in the paper "Analysis of chromatin organization and gene expression in T cells identifies functional genes for rheumatoid arthritis"
Authors/Creators
- 1. The University of Manchester
- 2. Florida State University
Description
lists of source file used in the paper "Analysis of chromatin organization and gene expression in T cells identifies functional genes for rheumatoid arthritis" by Jing Yang, Amanda McGovern, Paul Martin, Kate Duffus, Xiangyu Ge, Peyman Zarrineh, Andrew P Morris, Antony Adamson, Peter Fraser, Magnus Rattray & Stephen Eyre. The paper has been accepted by Nature Communications.
Notes
raw sequencing data available on https://www.ncbi.nlm.nih.gov/gds/?term=GSE138767
Files
T24H_rep1_40x80kb.PC1.txt
Files
(1.3 GB)
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md5:2a8b8acd17516cc254bdfa6c64fd595d
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35.0 kB | Download |
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md5:fd27f77506037c54dff929136f442568
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173.5 MB | Download |
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md5:18f6d30510b5c7533754b4ab061cc4e0
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650.1 kB | Download |
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md5:61458c8191e30b95bfb36113ba7c6a41
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22.6 MB | Download |
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md5:ee9d75287d6e528c595af5fb437a2351
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8.8 MB | Download |
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md5:4b53c6e3897ef278b067ca1c2c04b7c9
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182 Bytes | Download |
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md5:e3dd04d7d43a2e2f2866e0f94e13c8fc
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3.0 MB | Download |
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md5:190a5252ec20508892a1f363c8d342ca
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9.2 MB | Download |
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md5:9e1f3b26da3e4f3d9296c5e70511b3c3
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1.6 MB | Download |
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md5:55863d8834d926911484caa2738e087d
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6.5 kB | Download |
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md5:0872d06ea7487cf6a6e4366cbe4e4567
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10.1 MB | Download |
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md5:d951beff08327152fee4c0ef77ad88a9
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10.0 MB | Download |
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md5:0f2793eed97fedb5ab3d4cb278a610b4
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12.0 MB | Download |
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md5:bf85f61770b63d9dce0513a784208e1e
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5.5 MB | Download |
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md5:580d3b53f8568de1584c3ef12d4f2d5a
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32.3 MB | Download |
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md5:0f8639570b176344309c0bf402f47458
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10.2 MB | Download |
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md5:7ce652e79ebdef483527d7986e94ef5c
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3.7 MB | Download |
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md5:c441e0c5026f8e2a3ee4c39d07fc1817
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946.4 kB | Download |
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md5:2623c75aff7b9aac3304702606449e6a
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175.8 MB | Download |
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md5:30d2957d2decf56fa350ab6b4302bed3
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47.2 MB | Download |
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md5:f53bd1a05de6807c77a1cdb0e62a96e3
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10.2 kB | Download |
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md5:cec9be9ea1ad177d229811f757f17ed6
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1.2 kB | Download |
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md5:6423e1eb38a0d6ba49e737699bb4f45c
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10.2 kB | Download |
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md5:1e3476f65483825fc1c3f9eff704a305
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198.8 kB | Download |
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md5:1276481102f218c981e0324180bafd9f
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10.2 kB | Download |
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md5:03f71f4f26a78aeca926627ff3279e96
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4.1 MB | Preview Download |
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md5:4e4ba965700e8c179f5e42794ec75efd
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387.6 MB | Preview Download |
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md5:9e3bc299ce54a2a55418a048f6c8ea74
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387.6 MB | Preview Download |
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md5:1f9f2e27d5547ea43c6a9f8f9268cdd2
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4.1 MB | Preview Download |
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md5:bd8c4a9f58af6e10ed828733b391a973
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4.1 MB | Preview Download |
Additional details
Related works
- Is supplement to
- Working paper: https://github.com/ManchesterBioinference/IntegratingATAC-RNA-HiC.git (URL)
Funding
- UK Research and Innovation
- Integrating Capture-HiC with omic time course data to uncover the regulatory interactions modulated by genetic variation in disease MR/N00017X/1