Evidence map›Paper›PMID 33778492›Full record

ArticleNAR genomics and bioinformatics2021

3D reconstruction of genomic regions from sparse interaction data.

Julen Mendieta-Esteban, Marco Di Stefano, David Castillo, Irene Farabella, Marc A Marti-Renom

Abstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Julen Mendieta-EstebanCNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08028 Barcelona, Spain.
Marco Di StefanoCNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08028 Barcelona, Spain.ORCID https://orcid.org/0000-0001-6195-4754
David CastilloCNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08028 Barcelona, Spain.
Irene FarabellaCNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08028 Barcelona, Spain.ORCID https://orcid.org/0000-0002-7473-6227
Marc A Marti-RenomCNAG-CRG, Centre for Genomic Regulation (CRG), Barcelona Institute of Science and Technology (BIST), 08028 Barcelona, Spain.ORCID https://orcid.org/0000-0002-0151-4279

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chromosome conformation capture (3C) technologies measure the interaction frequency between pairs of chromatin regions within the nucleus in a cell or a population of cells. Some of these 3C technologies retrieve interactions involving non-contiguous sets of loci, resulting in sparse interaction matrices. One of such 3C technologies is Promoter Capture Hi-C (pcHi-C) that is tailored to probe only interactions involving gene promoters. As such, pcHi-C provides sparse interaction matrices that are suitable to characterize short- and long-range enhancer-promoter interactions. Here, we introduce a new method to reconstruct the chromatin structural (3D) organization from sparse 3C-based datasets such as pcHi-C. Our method allows for data normalization, detection of significant interactions and reconstruction of the full 3D organization of the genomic region despite of the data sparseness. Specifically, it builds, with as low as the 2-3% of the data from the matrix, reliable 3D models of similar accuracy of those based on dense interaction matrices. Furthermore, the method is sensitive enough to detect cell-type-specific 3D organizational features such as the formation of different networks of active gene communities.

Identifiers

PMID33778492
PMCPMC7985034

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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.