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A User-friendly and Powerful R Analysis of Large-scale Datasets

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Published on: November 4, 2025

Perl One-Liners: Bridging the Gap Between Large Data Sets and Analysis Tools.

Karsten Hokamp¹

¹School of Genetics and Microbiology, Smurfit Institute of Genetics, Trinity College Dublin, College Green, Dublin 2, Ireland. kahokamp@tcd.ie.

Methods in Molecular Biology (Clifton, N.J.)

|October 27, 2015

Summary

This summary is machine-generated.

Researchers can use Perl one-liners to efficiently reformat, filter, and merge large biological datasets. This approach overcomes bottlenecks caused by diverse and large data formats in computational biology analyses.

Keywords:

Bioinformatics Data formatting Data merging One-liners Perl Programming

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Area of Science:

Computational biology
Bioinformatics
Genomics

Background:

Biological data analysis relies on numerous tools but faces challenges with diverse and large data formats.
High-throughput analysis platforms generate large files that are difficult to process with standard software, creating bottlenecks.

Purpose of the Study:

To present Perl one-liners as a practical solution for biological data manipulation.
To demonstrate how to reformat, filter, and merge datasets for downstream analyses.

Main Methods:

Utilizing Perl one-liners for rapid data manipulation.
Providing adaptable code examples for common data processing tasks.

Main Results:

Perl one-liners effectively handle large datasets and diverse formats.
The proposed methods streamline data preparation for computational analyses.

Conclusions:

Perl one-liners offer a simple and powerful approach to overcome data format challenges in bioinformatics.
This method facilitates efficient data preprocessing, enhancing the overall analysis pipeline.