Evidence map›Paper›PMID 35662897›Full record

ArticlePEARC20 : Practice and Experience in Advanced Research Computing 2020 : Catch the wave : July 27-31, 2020, Portland, Or Virtual Conference. Practice and Experience in Advanced Research Computing (Conference) (2020 : Online)2020

PEGR: a management platform for ChIP-based next generation sequencing pipelines.

Danying Shao, Gretta Kellogg, Shaun Mahony, William Lai, B Franklin Pugh

Open access · greenAbstract read
In one paragraph

Article in PEARC20 : Practice and Experience in Advanced Research Computing 2020 : Catch the wave : July 27-31, 2020, Portland, Or Virtual Conference. Practice and Experience in Advanced Research Computing (Conference) (2020 : Online), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 46% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

5 authors at 1 institution in 1 country.

Danying ShaoPennsylvania State University, University Park, Pennsylvania.
Gretta KelloggPennsylvania State University, University Park, Pennsylvania.
Shaun MahonyPennsylvania State University, University Park, Pennsylvania.
William LaiPennsylvania State University, University Park, Pennsylvania.
B Franklin PughPennsylvania State University, University Park, Pennsylvania.
Pennsylvania State University · US

Funding

Promoter Regulation in Response to Environmental StressR01ES013768 · NIEHS · PENNSYLVANIA STATE UNIVERSITY, THE · PI PUGH, B FRANKLIN · 2007 to 2019
$4.9M
Genome-wide structural organization of proteins within human gene regulatory complexesR01GM125722 · NIGMS · PENNSYLVANIA STATE UNIVERSITY, THE · PI MAHONY, SHAUN AENGUS, PUGH, B FRANKLIN · 2018 to 2021
$1.5M
NIEHS NIH HHS R01 ES013768NIGMS NIH HHS R01 GM125722
6 · The paper itself

Abstract

There has been a rapid development in genome sequencing, including high-throughput next generation sequencing (NGS) technologies, automation in biological experiments, new bioinformatics tools and utilization of high-performance computing and cloud computing. ChIP-based NGS technologies, e.g. ChIP-seq and ChIP-exo, are widely used to detect the binding sites of DNA-interacting proteins in the genome and help us to have a deeper mechanistic understanding of genomic regulation. As sequencing data is generated at an unprecedented pace from the ChIP-based NGS pipelines, there is an urgent need for a metadata management system. To meet this need, we developed the Platform for Eukaryotic Genomic Regulation (PEGR), a web service platform that logs metadata for samples and sequencing experiments, manages the data processing workflows, and provides reporting and visualization. PEGR links together people, samples, protocols, DNA sequencers and bioinformatics computation. With the help of PEGR, scientists can have a more integrated understanding of the sequencing data and better understand the scientific mechanisms of genomic regulation. In this paper, we present the architecture and the major functionalities of PEGR. We also share our experience in developing this application and discuss the future directions.

Indexed as

next generation sequencing pipelinescience gatewayweb application

Identifiers

PMID35662897
PMCPMC9161112
OpenAlexW3044139896

What OpenQuestion holds

Textmetadata
LicenceTDM
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.