Computational Life Sciences

Opportunities and Challenges in Bioinformatics Software

Deciding between purchasing bioinformatics software or building your own pipeline? Check out the opportunities and challenges of each.

Jill Roughan, PhD

Jill Roughan, PhD

October 20, 2022

Opportunities and Challenges in Bioinformatics Software

Next-generation sequencing (NGS) and other high-throughput gene profiling techniques have generated vast amounts of biological data, presenting researchers with nearly endless opportunities to untangle complicated biological questions. Commercially available, easy-to-use bioinformatics software has made mining and analyzing this data much more straightforward, delivering the power of computational and data science to nearly any biologist with minimal bioinformatic experience. Yet many academic and industry scientists choose to navigate bioinformatics analysis using a “do-it-yourself” solution, assembling their pipeline using open-source packages, bioinformatics visualization tools, and the guidance of the bioinformatics community. Below, we discuss what bioinformatics software does, the applications it's used for, and weigh the pros and cons of using it compared to taking a Do-It-Yourself (DIY) approach. 

Here’s what we’ll discuss:

  • Bioinformatics Software and its Purpose
  • Applications of Bioinformatics Software
  • How to Decide Whether Bioinformatics Software is Right for You
  • Comparing DIY to Buy
  • Find the Best Bioinformatics Solution 
  • Bioinformatics Software FAQs

What is Bioinformatics Software and What is its Purpose?

The cost of generating biological data with genomics, transcriptomics, epigenomics, and other “omics” techniques has dropped massively over the past decade. As a result, biology researchers have become “omics-obsessed,” implementing and combining “omics” workflows and generating vast amounts of data. The European Bioinformatics Institute, for instance, reached more than 390 petabytes of raw data (1 petabyte = 1 million gigabytes) stored at the end of 2020.(1).

But lots of data doesn’t automatically translate into unique or fascinating biological insight. 

Premier bioinformatics software would enable a user (or users) to aggregate, organize, visualize, and share “omics” data with a simple and easy-to-use graphical user interface (GUI) and provide collaboration capabilities. Together, to help uncover meaningful insights from the chaotic, tangled mess of raw genomics, transcriptomics, proteomics, or other data. Much of the software used in bioinformatics streamlines analysis with cloud-based computing, expansive data storage.

Typical features include the ability to: (2)

  • Import, export, store, and organize raw data
  • Install and use proprietary or open-source plugins or applications in workflows
  • Download, query, and analyze public databases (i.e., GenBank, UniProt, etc.)
  • Rapidly perform an array of sequence, phylogenetic, and other standard analyses 
  • Visualize data in an easily customizable interface
  • Troubleshoot and customize with bioinformatics experts and customer support

Given these attractive factors, scientists in academia and industry use bioinformatics software and tools for many different applications. Bioinformatics software is typically used for discovery projects, pre-clinical research and development, or teaching in academia. In an industry setting, bioinformatics software may be used in more applied ways to drive drug discovery and development or manage and analyze data from clinical trials.

Applications of Bioinformatics Software

One of the most common bioinformatics software applications is to analyze NGS data. NGS has become ubiquitous over the past decade, enabling high-throughput sequencing of whole genomes, epigenomes, and transcriptomes. You can use bioinformatics software to assemble raw NGS data into contiguous sequences without using a reference genome, a process called de novo genome assembly. Bioinformatics software platforms also offer tools that align raw NGS data to reference genomes, enabling researchers to identify genetic differences between the reference and experimental sequence (i.e., variant calling) (4).

The same is true for transcriptome analysis: RNA-seq data can be aligned to a reference genome or transcriptome and used to quantify global gene expression, discover novel transcripts (i.e., fusion genes, alternative splice variants), profile active pathways and functions, and integrate with other data types (i.e., epigenomics, proteomics datasets) (5).

The bioinformatics software and tools you’re using may also offer other tools that complement your research tasks, including molecular cloning, primer design, CRISPR guide RNA design, RNA structure prediction, protein structure analysis, and phylogenetic analysis. Given these broadly applicable tools, bioinformatics software is used extensively in areas such as microbiome research, cell and gene therapy, personalized medicine, agriculture, and biotechnology (6).

How to Decide Whether Bioinformatics Software is Right for You

Many commercially-available bioinformatics software suites are available and have become an essential part of R&D laboratories, clinical programs, and classrooms. Despite their utility, ease of use for those with minimal computational experience, and powerful analytical tools, many scientists choose the DIY route, using open-source bioinformatics tools, programs, packages, and algorithms to solve their data analysis problems. 

So, how do you know if purchasing or building bioinformatics software is right for you? Let’s take a look at some of the opportunities and challenges.


No computational experience required

Due to the widespread nature of sequencing technology and bioinformatics analysis, many software platforms have been specially designed for researchers with minimal computational or coding background. You don’t need to learn to use a command-line terminal or code in R, Python, C++, or Java to get powerful insights or insightful visualizations. Many analyses can be done using a simple point-and-click GUI, a significant advantage if you don’t come from a computational background.

Excellent user experience and interface

The design is so good that even those with computational skills, from novices to experts, may choose to purchase bioinformatics software (7). Bioinformatics software can be easy and intuitive, which beats navigating multiple programming windows, languages, programs, applications, and operating systems to do your analysis. Bioinformatics is constantly evolving, and many suites also offer a portfolio of different plug-ins and version upgrades to expand capabilities, stay up to date with the latest research, and offer the best experience for users. 


When research groups with different skill sets collaborate, experimental details, results, and insights can get lost in translation. Bioinformatics software can help keep raw data organized, data visualization consistent, and provide access to the same analyses for all collaborators, whether or not they have bioinformatics experience. Most bioinformatics software platforms allow multiple users and cloud computing to facilitate collaboration and enable everyone to access and better understand the data as a team.

One-stop-shop for powerful insights

Most bioinformatics software platforms have many different primary sequence, phylogenetic analysis, and structure-function tools. In addition, you can introduce plug-ins, downloadable applications, and other open-source tools so you can do all of your research on one platform. You can also integrate different data sets (from public or private databases) and types, creating a full-service solution for your bioinformatics analysis and data visualization.

Finally, some platforms offer additional benefits, including excellent scalability as your data and team increase in size, improved security and regulatory compliance for dealing with sensitive data, and customer support for troubleshooting or debugging.


Cost of access

Bioinformatics software suites can be costly, ranging from hundreds to thousands of dollars for a yearly subscription. The price tag can vary significantly depending on whether you are in an academic or industry environment or how many users you want to use it simultaneously. You can incur additional costs should you wish to upgrade your subscription or add extra features. 

Not always easy to use

Learning how to use new software can be a challenge regardless of its function. While most platforms focus on creating a simple user interface, some bioinformatics software can take time to learn or not be intuitive to use. The more complicated software is to use, the higher the barrier to adoption.

Lots of options

Many commercial bioinformatics platforms vary in cost, quality, and usability

While having options is great, it gives you a lot of information to sift through as the user and potential buyer. You’ll have to get quotes, talk to salespeople and colleagues, and do research. Some platforms offer trial periods, which allow you to try out the software and experience for yourself how it fits into your research.

To DIY or Buy

As you weigh the pros and cons of buying commercial bioinformatics software, consider how that option stacks up against building your own analysis pipeline.

If your research group or company doesn’t have the budget for purchasing a bioinformatics solution that works out of the box, building a pipeline yourself may be the best option. There are many open-source tools and the collective intelligence of the highly-active and helpful bioinformatics community to support you. In addition, you may be able to lean on internal expertise to help you troubleshoot. 

The DIY solution may fit your budget in the short-term, but will it long-term? Scaling may be complex, and you may not have the flexibility to deal with other datasets or types. Bioinformatics software suites do incur a considerable upfront cost. But if you stack it up against the direct and indirect costs of building and maintaining your DIY pipeline, you may find that the software solution is the way to go.


Maintaining the integrity and quality of your bioinformatics pipeline is essential to delivering reproducible, high-quality results. Without careful attention to updates to your code, you can get stuck in endless troubleshooting loops. For commercial software, maintenance, upgrades, and customer support are typically covered in the monthly or annual cost, enabling easy access to the latest, greatest tools without the headache of debugging code or dealing with reproducibility issues.

Time & Resources

Many teams don’t have the luxury of internal bioinformatics experts, which means a lot of time spent training and extensive trial and error. In addition, managing and storing raw data can take massive amounts of storage space and computing power. To accommodate these needs, you may need to build the infrastructure from scratch or upgrade your current setup. With a bioinformatics software platform from a company, these details are handled.


During peak times of data generation and analysis, you may reach the limits of your processing and storage capabilities. Consider scalability early before hitting a wall when building your bioinformatics pipeline. Many software platforms perform cloud storage and computing, which can help you scale and improve reproducibility and speed with which specific analyses can be done.

Finding a Bioinformatics Solution That Suits You

There is a lot to consider when venturing down the path of bioinformatics analysis. Building a DIY pipeline may look unattractive if you take the long-term costs, learning time, and scale-up needs under consideration. If you’re looking for an alternative solution, purchasing a bioinformatics software platform can provide all the functions you need for data management, genomics, transcriptomics, and other “omics” workflows, collaboration, and scalability.

Bioinformatics Software FAQs

What exactly is bioinformatics software?

Bioinformatics software provides an all-in-one platform for analyzing genomics, transcriptomics, proteomics, epigenomics, multi-omics, and other biological data and extracting meaningful insights that advance our understanding of biology. 

What are the applications of bioinformatics software?

The major applications of bioinformatics software are for biotechnology, drug discovery and development, cell and gene therapy, microbiome research, agriculture, clinical research, personalized medicine, and many others.

What are the benefits of using bioinformatics software?

Purchasing bioinformatics software enables researchers access to a “one-stop-shop” for many different primary sequence, phylogenetic analysis, structure-function, multi-omics, and data visualization tools. In addition, many software suites are easy-to-use, have an excellent user experience and interface, don’t require the user to have a computational background, and enable collaboration.

Want to learn if Form is the right software for you?

Schedule Your Demo


  1. Cantelli G, Bateman A, Brooksbank C, et al. The European Bioinformatics Institute (EMBL-EBI) in 2021. Nucleic Acids Res. 50(D1):D11-D19 (2022). 
  2. Markowetz F. All biology is computational biology. PLoS Biol.15(3):e2002050 (2017).
  3. Shoaib M et al. A Comprehensive Study of De Novo Genome Assemblers: Current Challenges and Future Prospective. Evol Bioinform Online. 14 1176934318758650 (2018).
  4. Muzzey D, Evans EA, Lieber C. Understanding the Basics of NGS: From Mechanism to Variant Calling. Curr Genet Med Rep. 3(4):158-165 (2015). 
  5. Conesa A, Madrigal P, Tarazona S, et al. A survey of best practices for RNA-seq data analysis. Genome Biol.17:13 (2016). 
  6. Bioinformatics- Tools and Applications. ResearchGate website: Accessed May 10, 2022. Published April 29, 2021.
  7. Smith DR. Buying into bioinformatics: an introduction to commercial sequence analysis software. Brief Bioinform. 16(4):700-709 (2015). 

More to Explore