Illumina, PacBio Or Oxford Nanopore: Which One To Choose?
Illumina, PacBio, and Oxford Nanopore Technologies (ONT) are the most popular next-generation sequencing (NGS) technologies currently available. When deciding which one to choose for your project, there are a few considerations you should keep in mind. Let's discuss some of these factors to help you make an informed decision.
Cost When it comes to cost, Illumina is generally the most cost-effective NGS platform, with per Gb sequencing costs consistently below $100. PacBio and ONT, on the other hand, tend to cost around $2000 per Gb of sequencing data. It's worth noting that newer, higher-throughput ONT machines claim to be able to produce data at a cost closer to that of Illumina, but these models are not yet widely available.
Error rates Error rates are an important factor to consider when choosing an NGS platform. Illumina claims to have achieved a low error rate of around 0.1%, though some estimates put it closer to 0.2-0.5%. While this is still substantially lower than the 10-15% error rates often seen in PacBio and ONT data, it's worth noting that PacBio has developed the circular consensus sequencing (CCS) protocol to address this issue. CCS involves repeating the sequencing of the same regions multiple times and using consensus calling to produce so-called HIFI data with error rates similar to Illumina. However, this repeated sequencing does increase the cost. Currently, ONT does not have an effective way of reducing its high error rates.
Read lengths When it comes to read lengths, PacBio and ONT have significant advantages over Illumina. While some Illumina machines can produce 2X300bp reads (paired end, with both ends of the same DNA fragment sequenced), a "typical" Illumina sequencing experiment uses 2X150bp reads. In contrast, PacBio can produce reads up to 25,000 bp in length, and ONT can produce reads as long as 300,000 bp or even longer. This is an important consideration if you need longer reads for your project.
Applications When it comes to applications, Illumina has been around for over 15 years and has a strong track record of support from the research community. Many well-established NGS applications, such as whole exome sequencing (WES), RNA-seq, ChIP-seq, and 3C-seq/Hi-C, have been developed in conjunction with the Illumina technology. However, the short read lengths of Illumina can restrict some aspects of its application, such as whole genome sequencing (WGS) and applications requiring assembly. PacBio and ONT, as newer technologies, have been able to fill these gaps in application and also excel at certain improved or new applications due to their single-molecule sequencing, such as DNA modifications, RNA editing, and transcript isoforms. If your project involves well-established applications like "classical" WES, RNA-seq, or ChIP-seq, then Illumina may be a good choice. However, if your project requires sequence assembly or touches on some of the novel features of single-molecule sequencing, you should consider PacBio or ONT.
Bioinformatics Analysis When it comes to bioinformatics analysis, there are more tools available for Illumina data, but the development of tools for PacBio and ONT has been steadily increasing in recent years. Despite error rates over 10%, PacBio and ONT data are still usable thanks to the efforts of bioinformatics tool developers. Currently, routine mapping tasks (using tools like minimap2) and assembly tasks (using tools like canu and miniasm) can be performed on PacBio and ONT data just as easily as on Illumina data (using tools like bwa and AllPaths).
The main bioinformatics challenges in PacBio- or ONT-based projects often involve deciding on the appropriate steps to take and when to take them, rather than using specific tools. For example, should a mapping-based strategy or an assembly-based strategy be used? Should error correction be performed before or after mapping? How should adjustments be made if the results of the analysis are not as expected? While many bioinformaticians are comfortable making these decisions with Illumina data, they may still lack the necessary experience to make the best calls in many of these situations with PacBio or ONT data.
Other Considerations There are many other factors to consider when deciding which sequencing technology to use for your project. Accessibility to a sequencing core with the desired platform and good support is an important factor, and it's worth noting that the Illumina technology may have reached its ceiling and is not expected to change dramatically in the coming years. PacBio and ONT, on the other hand, are still in active development. It's worth noting that PacBio and ONT have not embraced the open development model as enthusiastically as Illumina did in its earlier years. For example, ONT frequently adjusts its protein pores and machine learning-based base-calling algorithm, making it difficult for third-party developers to play an active role. The PacBio system is also largely proprietary up to the point of base-call data generation. It's possible that after using PacBio or ONT in a project, you may find yourself in a position where support for your data becomes limited or even absent due to changes in the technology a few years down the line.
About the Author: Justin T. Li received his Ph.D. in Neurobiology from the University of Wisconsin-Madison in 2000 and his M.S. in Computer Science from the University of Houston in 2001. He served as an Assistant Professor in the Medical School at the University of Minnesota Twin Cities campus from 2004 to 2009, and as Chief Bioinformatics Officer at LC Sciences in Houston from 2009 to 2013. In June 2013, he joined AccuraScience as a Lead Bioinformatician. Justin has published more than 40 research articles in bioinformatics, computational biology, and related fields. More information about Justin can be found at https://www.accurascience.com/our_team.html.
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