Evidence map›Paper›PMID 39533201›Full record

ArticleBMC bioinformatics2024

Closha 2.0: a bio-workflow design system for massive genome data analysis on high performance cluster infrastructure.

Gunhwan Ko, Pan-Gyu Kim, Byung-Ha Yoon, JaeHee Kim, Wangho Song, IkSu Byeon, JongCheol Yoon, Byungwook Lee, Young-Kuk Kim

Abstract read
In one paragraph

Article in BMC bioinformatics, 2024. 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
–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

2 citing papers in PubMed.

  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

9 authors.

Gunhwan Ko *Korean Bioinformation Center (KOBIC), KRIBB, 125 Gwahangno, Yuseong-gu, Daejeon, 34141, Korea.
Pan-Gyu Kim *Korean Bioinformation Center (KOBIC), KRIBB, 125 Gwahangno, Yuseong-gu, Daejeon, 34141, Korea.
Byung-Ha YoonKorean Bioinformation Center (KOBIC), KRIBB, 125 Gwahangno, Yuseong-gu, Daejeon, 34141, Korea.
JaeHee KimKorean Bioinformation Center (KOBIC), KRIBB, 125 Gwahangno, Yuseong-gu, Daejeon, 34141, Korea.
Wangho SongKorean Bioinformation Center (KOBIC), KRIBB, 125 Gwahangno, Yuseong-gu, Daejeon, 34141, Korea.
IkSu ByeonKorean Bioinformation Center (KOBIC), KRIBB, 125 Gwahangno, Yuseong-gu, Daejeon, 34141, Korea.
JongCheol YoonKorean Bioinformation Center (KOBIC), KRIBB, 125 Gwahangno, Yuseong-gu, Daejeon, 34141, Korea.
Byungwook LeeKorean Bioinformation Center (KOBIC), KRIBB, 125 Gwahangno, Yuseong-gu, Daejeon, 34141, Korea. bulee@kribb.re.kr.
Young-Kuk KimDepartment of Bio-AI Convergence, Chungnam National University, Daejeon, 34134, Korea. ykim@cnu.ac.kr.

Funding

Institute of Information & Communications Technology Planning & Evaluation (IITP) RS-2022-00155857Korean Ministry of Science and Technology 2020M3A9I6A01036057
6 · The paper itself

Abstract

backgroundThe explosive growth of next-generation sequencing data has resulted in ultra-large-scale datasets and significant computational challenges. As the cost of next-generation sequencing (NGS) has decreased, the amount of genomic data has surged globally. However, the cost and complexity of the computational resources required continue to be substantial barriers to leveraging big data. A promising solution to these computational challenges is cloud computing, which provides researchers with the necessary CPUs, memory, storage, and software tools.

resultsHere, we present Closha 2.0, a cloud computing service that offers a user-friendly platform for analyzing massive genomic datasets. Closha 2.0 is designed to provide a cloud-based environment that enables all genomic researchers, including those with limited or no programming experience, to easily analyze their genomic data. The new 2.0 version of Closha has more user-friendly features than the previous 1.0 version. Firstly, the workbench features a script editor that supports Python, R, and shell script programming, enabling users to write scripts and integrate them into their pipelines. This functionality is particularly useful for downstream analysis. Second, Closha 2.0 runs on containers, which execute each tool in an independent environment. This provides a stable environment and prevents dependency issues and version conflicts among tools. Additionally, users can execute each step of a pipeline individually, allowing them to test applications at each stage and adjust parameters to achieve the desired results. We also updated a high-speed data transmission tool called GBox that facilitates the rapid transfer of large datasets.

conclusionsThe analysis pipelines on Closha 2.0 are reproducible, with all analysis parameters and inputs being permanently recorded. Closha 2.0 simplifies multi-step analysis with drag-and-drop functionality and provides a user-friendly interface for genomic scientists to obtain accurate results from NGS data. Closha 2.0 is freely available at https://www.kobic.re.kr/closha2 .

Indexed as

Cloud ComputingGenomicsHigh-Throughput Nucleotide SequencingSoftwareWorkflowBioinformatics workflowClosha 2.0Cloud computingData transmission (GBox)Genomic data analysisHigh-performance computing (HPC)Next-generation sequencing (NGS)Single-cell RNA sequencing (scRNA-Seq)User-friendly interface

Identifiers

PMID39533201
PMCPMC11558834

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.