Evidence map›Paper›PMID 42164079›Full record

ArticleBioinformatics advances2026

BLIT: an R package for seamless integration of command-line bioinformatics tool universe.

Jia Ding, Yun Peng, Ruochen Wei, Boquan Wang, Jian-Guo Zhou, Shixiang Wang

Abstract read
In one paragraph

Article in Bioinformatics advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Jia DingDepartment of Biomedical Informatics, School of Life Sciences, Central South University, Changsha, 410013, P. R. China.ORCID https://orcid.org/0009-0002-2530-0897
Yun PengDepartment of Urology, Peking University People's Hospital, Beijing, 100044, P. R. China.
Ruochen WeiDepartment of Biomedical Informatics, School of Life Sciences, Central South University, Changsha, 410013, P. R. China.
Boquan WangDepartment of Biomedical Informatics, School of Life Sciences, Central South University, Changsha, 410013, P. R. China.
Jian-Guo ZhouDepartment of Oncology, The Second Affiliated Hospital of Zunyi Medical University, Zunyi, 563000, P. R. China.
Shixiang WangDepartment of Biomedical Informatics, School of Life Sciences, Central South University, Changsha, 410013, P. R. China.ORCID https://orcid.org/0000-0001-9855-7357

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motivation: Modern computational biology relies heavily on command-line tools that underpin analytical workflows, yet integrating these tools into R-based analyses poses substantial challenges for reproducibility, especially for researchers with limited computational expertise. While R excels at statistical analysis and visualization, its native capabilities for executing external commands remain rudimentary, lacking structured integration, environment management, and reliable cross-platform support. Results: To address these limitations, BLIT, an R package, provides a unified framework for seamless command-line integration within R, enabling R users to invoke external tools in an intuitive manner. Rather than positioning itself as yet another workflow manager, BLIT emphasizes the robust encapsulation and coordination of command-line tools, enabling users to construct reproducible analysis pipelines without leaving the R environment. BLIT encapsulates command-line programs as R6 objects with dynamic validation, Micromamba-based environment management, and native piping support. This makes BLIT a direct bridge between R scripts and heterogeneous command-line ecosystems, replacing fragile system() calls with a robust, standardized framework that supports conditional execution and single-machine parallel computing, with the capability to hand off constructed command workflows to HPC schedulers or workflow engines for large-scale execution. Although designed for bioinformatics, BLIT offers a general, platform-agnostic solution for constructing reproducible analytical pipelines within R. Availability and implementation: BLIT is available on CRAN (https://cran.r-project.org/package=blit) and on GitHub (https://github.com/WangLabCSU/blit).

Identifiers

PMID42164079
PMCPMC13183670

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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.