Linux in Bioinformatics: A Dominating collaboration
Modern Biological research finds bioinformatics essential as it demands the help of computational tools to direct, inspect and interpret the biological data. Powerful and flexible operating systems are the need to handle the size and complications of the data generated from biological studies. Linux being an open-source operating system, it provides the strong support and steadiness that is required by a bioinformatician to work efficiently.
Reasons for choosing Linux:[i][ii]
Linux is favored by bioinformaticians for following reasons:
Open Source: The fundamental reason to opt for Linux is its open-source identity as unlike other operating systems Linux permits its consumers to alter and enhance the software, these modifications in the absence of any limitations entitles researchers to create and convert their computational tools for research purposes.
Enduring Nature: Bioinformatics runs around streaming complex calculations and handling huge datasets which maybe resource demanding. Linux is well known for managing system resources with steadiness and effectiveness which makes it appropriate for the challenging piece of work. Tasks like genome assembly and sequence alignment can be efficiently concluded without any interruption in the system which makes Linux to gain the trust of a bioinformatician.
Favorable Characters: Linux environment includes vast display of bioinformatics libraries and tools which are readily accessible and can be customized making it ideal for the various applications of bioinformatics. Its Command Line interface (CLI) allows these tools to be automated and scripted according to need. Linux also provides considerable support and facilities for troubleshooting and its development.
Kick off with Linux in Bioinformatics:[iii]
Before using Linux, first decide which distribution of Linux you want to go with. Some admired options are CentOS, Ubuntu and Fedora. Next, know about some basic commands to start with Linux, that are:
Sail across the files: For navigating the file system, the essential commands are:
cd: it navigates or change to a directory.
ls: shows the lists of files or directories.
pwd: prints the directory which is in work process.
mkdir: helps creating a directory.
File Maintenance: It comprises renaming, copying, moving or removing of directories or files.
rm: It works to remove or undo a file.
cp: It is a command for copying files.
mv: It paves the way for dislocating a file.
Check and Revising files:
cat: It stands as concatenate and unveils the content of the file.
less: Displays the file content individually on a screen.
vi or nano: Edits file straight from the terminal.
Data Extracting:
grep: Hunts for require patterns in file.
awk: Processes and scans files
Favored Tools of Bioinformatics on Linux:
Several Bioinformatics tools are adapted to be used on Linux. The most notable ones are:
BLAST[iv](Basic Local Alignment Search Tool): This tool was established to compare and find similarities among nucleotide and protein sequences by using sequence databases.
ClustalW[v]: This tool stands out for its ability for multiple sequence alignment.
SAMtools[vi]: It interrelates with sequencing data and manipulates alignments in SAM format.
BEDtools[vii]: For the manipulation of genomic data, BEDtools is a potent tool for genome arithmetic.
Applications of Linux in Bioinformatics:
Sequence Analysis: Sequence analysis is elemental to bioinformatics, linked through identification and analogy of protein and nucleotide sequences. Linux is a reliable platform for the use of sequence analysis tools such as BLAST, Bowtie or BWA which are used for the alignment of minuscule DNA sequences with the reference genome. These tools are great help in managing large datasets while providing precise results.
Genome Fabrication: The procedure of reconstructing a genome by organizing fragments of DNA sequences of a specie is called genome assembly. SPAdes [viii]and Velvet being a Linux based tools which are specifically designed for genome assembly efficiently cater the large data with the collaboration of Linux that ensures that the tools run without interruption for desired period while providing outstanding genome assemblies.
Proteomics: Apart from genomics, Linux is also a helping hand for proteomics research. Proteomics is the domain which offers information about proteins, their functions and structures. Linux is used in this cause for scanning mass spectrometry data with quantification of proteins in biological samples and visualizing structures of biomolecules by the help of bioinformatics tools called MaxQuant and OpenMS. [ix]
Conclusion:
Linux has proved itself essential in the world of bioinformatics by offering an ecosystem which is stable for analyzing biological data. The open source nature, flexibility that it provides to its users and the environment for efficient use of bioinformatics tools are the captivating qualities of Linux which makes it an epitome of perfection for biological research.
References:
[i]Siever, E., Weber, A., Figgins, S., Love, R., & Robbins, A. (2005). Linux in a Nutshell. " O'Reilly Media, Inc.".
[ii]Rana, A., & Foscarini, F. Linux distributions for bioinformatics.
[iii]Carroll, H. D. (2016). Linux Commands.
[iv]Madden, T. (2013). The BLAST sequence analysis tool. The NCBI handbook, 2(5), 425-436.
[v]Thompson, J. D., Gibson, T. J., & Higgins, D. G. (2002). Multiple sequence alignment using ClustalW and ClustalX. Et al [Current Protocols in Bioinformatics], Chapter 2(1), Unit 2.3. doi:10.1002/0471250953.bi0203s00
[vi]Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., … 1000 Genome Project Data Processing Subgroup. (2009). The Sequence Alignment/Map format and SAMtools. Bioinformatics (Oxford, England), 25(16), 2078–2079. doi:10.1093/bioinformatics/btp352
[vii]Quinlan, A. R., & Hall, I. M. (2010). BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics (Oxford, England), 26(6), 841–842. doi:10.1093/bioinformatics/btq033
[viii]Bankevich, A., Nurk, S., Antipov, D., Gurevich, A. A., Dvorkin, M., Kulikov, A. S., … Pevzner, P. A. (2012). SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. Journal of Computational Biology: A Journal of Computational Molecular Cell Biology, 19(5), 455–477. doi:10.1089/cmb.2012.0021
[ix]Perez-Riverol, Y., & Moreno, P. (2020). Scalable data analysis in proteomics and metabolomics using BioContainers and workflows engines. Proteomics, 20(9), e1900147. doi:10.1002/pmic.201900147
