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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
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Single-cell NTT-seq datasets

Authors: Stuart, Tim; Hao, Stephanie; Zhang, Bingjie; Mekerishvili, Levan; Landau, Dan; Maniatis, Silas; Satija, Rahul; +1 Authors

Single-cell NTT-seq datasets

Abstract

Note that the saved objects link to fragment files stored remotely on AWS servers. This enables running analyses without needing to download the entire fragment file and link it to the object locally. However, for users running more extensive analyses (re-quantifying genomic regions, for example) we recommend downloading the fragment files to your local computer and linking them to the object. For example: ``` Fragments(obj) <- NULL # remove fragment file information Fragments(obj) <- CreateFragmentObject(path = , cells = colnames(obj)) # add a new fragment object ```

These datasets were generated using single-cell NTT-seq. Please see the publication for a full description of methods: Stuart, Tim, Stephanie Hao, Bingjie Zhang, Levan Mekerishvili, Dan Landau, Silas Maniatis, Rahul Satija, and Ivan Raimondi. 2022. “Nanobody-Tethered Transposition Allows for Multifactorial Chromatin Profiling at Single-Cell Resolution.” bioRxiv. doi:10.1101/2022.03.08.483436. Associated fragment files can be found on NCBI GEO: GSE212588

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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