ArticleMethods in molecular biology (Clifton, N.J.)2022
Visualizing and Annotating Hi-C Data.
Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- ppHiC: Interactive exploration of Hi-C results on the ProteinPaint web portal.Computational and structural biotechnology journal · 2024Article
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2 authors.
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Abstract
Epigenomics studies require the combined analysis and integration of multiple types of data and annotations to extract biologically relevant information. In this context, sophisticated data visualization techniques are fundamental to identify meaningful patterns in the data in relation to the genomic coordinates. Data visualization for Hi-C contact matrices is even more complex as each data point represents the interaction between two distant genomic loci and their three-dimensional positioning must be considered. In this chapter we illustrate how to obtain sophisticated plots showing Hi-C data along with annotations for other genomic features and epigenomics data. For the example code used in this chapter we rely on a Bioconductor package able to handle even high-resolution Hi-C datasets. The provided examples are explained in details and highly customizable, thus facilitating their extension and adoption by end users for other studies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.