Evidence map›Paper›PMID 29360936›Full record

ArticleBioinformatics (Oxford, England)2018

Haystack: systematic analysis of the variation of epigenetic states and cell-type specific regulatory elements.

Luca Pinello, Rick Farouni, Guo-Cheng Yuan

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. TGFB1 Induces Fetal Reprogramming and Enhances Intestinal Regeneration.bioRxiv : the preprint server for biology · 2023
    Article
  9. Article
  10. Article
  11. Epigenetic Alterations in Keratinocyte Carcinoma.The Journal of investigative dermatology · 2021
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
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

3 authors.

Luca PinelloDepartment of Molecular Pathology, Massachusetts General Hospital, Boston, MA, USA.
Rick FarouniDepartment of Molecular Pathology, Massachusetts General Hospital, Boston, MA, USA.
Guo-Cheng YuanDana-Farber Cancer Institute, Boston, MA, USA.

Funding

A systems biology approach for dissecting enhancer hierarchyR01HG009663 · NHGRI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI YUAN, GUO-CHENG · 2017 to 2020
$2.8M
Discovering disease-causal variants by linking genetic and epigenetic variationR00HG008399 · NHGRI · MASSACHUSETTS GENERAL HOSPITAL · PI PINELLO, LUCA · 2017 to 2019
$747k
NHGRI NIH HHS R00 HG008399NHGRI NIH HHS R01 HG009663
6 · The paper itself

Abstract

Motivation: With the increasing amount of genomic and epigenomic data in the public domain, a pressing challenge is to integrate these data to investigate the role of epigenetic mechanisms in regulating gene expression and maintenance of cell-identity. To this end, we have implemented a computational pipeline to systematically study epigenetic variability and uncover regulatory DNA sequences. Results: Haystack is a bioinformatics pipeline to identify hotspots of epigenetic variability across different cell-types, cell-type specific cis-regulatory elements, and associated transcription factors. Haystack is generally applicable to any epigenetic mark and provides an important tool to investigate the mechanisms underlying epigenetic switches during development. This software is accompanied by a set of precomputed tracks, which may be used as a valuable resource for functional annotation of the human genome. Availability and implementation: The Haystack pipeline is implemented as an open-source, multiplatform, Python package called haystack_bio freely available at https://github.com/pinellolab/haystack_bio. Contact: lpinello@mgh.harvard.edu or gcyuan@jimmy.harvard.edu. Supplementary information: Supplementary data are available at Bioinformatics online.

Indexed as

Genome, HumanRegulatory Sequences, Nucleic AcidSoftwareEpigenomicsHumansOrgan Specificity

Identifiers

PMID29360936
PMCPMC5972612

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.