2 datasets found
  1. Z

    Training material for ChIP-seq analysis

    • data.niaid.nih.gov
    • data-staging.niaid.nih.gov
    Updated Jan 24, 2020
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    Freeberg, Mallory; Heydarian, Mohammad (2020). Training material for ChIP-seq analysis [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_197100
    Explore at:
    Dataset updated
    Jan 24, 2020
    Dataset provided by
    Johns Hopkins University
    Authors
    Freeberg, Mallory; Heydarian, Mohammad
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The data provided here are part of a Galaxy tutorial that analyzes ChIP-seq data from a study published by Wu et al., 2014 (DOI:10.1101/gr.164830.113). The goal of this study was to investigate "the dynamics of occupancy and the role in gene regulation of the transcription factor Tal1, a critical regulator of hematopoiesis, at multiple stages of hematopoietic differentiation." To this end, ChIP-seq experiments were performed in multiple mouse cell types including a G1E cell line and megakaryocytes, the two cell types represented here. The dataset contains biological replicate Tal1 ChIP-seq and input control experiments (*.fastqsanger files). Because of the long processing time for the large original files, we have downsampled the original raw data files to include only reads that align to chromosome 19 and a subset of interesting genomic loci (ChIPseq_regions_of_interest_v4.bed) pulled from the Wu et al. publication. Also included is a gene annotation file (RefSeq_gene_annotations_mm10.bed) with gene names added for viewing in a genome browser.

  2. Training data for ChIP-seq data analysis (Galaxy Training Material):...

    • zenodo.org
    • data.niaid.nih.gov
    bin
    Updated Jan 24, 2020
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    Bérénice Batut; Friederike Dündar; Anika Erxleben; Björn Grüning; Bérénice Batut; Friederike Dündar; Anika Erxleben; Björn Grüning (2020). Training data for ChIP-seq data analysis (Galaxy Training Material): Identification of the binding sites of the Estrogen receptor [Dataset]. http://doi.org/10.5281/zenodo.892432
    Explore at:
    binAvailable download formats
    Dataset updated
    Jan 24, 2020
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Bérénice Batut; Friederike Dündar; Anika Erxleben; Björn Grüning; Bérénice Batut; Friederike Dündar; Anika Erxleben; Björn Grüning
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The data provided here are part of a Galaxy Training Network tutorial that analyzes ChIP-seq data from a study published by Ross-Inness et al., 2012 (DOI:10.1038/nature10730) to identify the binding sites of the Estrogen receptor, a transcription factor known to be associated with different types of breast cancer.

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Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Freeberg, Mallory; Heydarian, Mohammad (2020). Training material for ChIP-seq analysis [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_197100

Training material for ChIP-seq analysis

Explore at:
Dataset updated
Jan 24, 2020
Dataset provided by
Johns Hopkins University
Authors
Freeberg, Mallory; Heydarian, Mohammad
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

The data provided here are part of a Galaxy tutorial that analyzes ChIP-seq data from a study published by Wu et al., 2014 (DOI:10.1101/gr.164830.113). The goal of this study was to investigate "the dynamics of occupancy and the role in gene regulation of the transcription factor Tal1, a critical regulator of hematopoiesis, at multiple stages of hematopoietic differentiation." To this end, ChIP-seq experiments were performed in multiple mouse cell types including a G1E cell line and megakaryocytes, the two cell types represented here. The dataset contains biological replicate Tal1 ChIP-seq and input control experiments (*.fastqsanger files). Because of the long processing time for the large original files, we have downsampled the original raw data files to include only reads that align to chromosome 19 and a subset of interesting genomic loci (ChIPseq_regions_of_interest_v4.bed) pulled from the Wu et al. publication. Also included is a gene annotation file (RefSeq_gene_annotations_mm10.bed) with gene names added for viewing in a genome browser.

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