Go is Now the Best Programming Languages for Full-fledged Bioinformatics - Really?

Go is Now the Best Programming Languages for Full-fledged Bioinformatics - Really?


Bioinformaticians writing in twitter appear considerably bemused by a new paper that appeared in biorxiv late Friday. Here is the abstract.

Background: elPrep is an established multi-threaded framework for preparing SAM and BAM files in sequencing pipelines. To achieve good performance, its software architecture makes only a single pass through a SAM/BAM file for multiple preparation steps, and keeps sequencing data as much as possible in main memory. Similar to other SAM/BAM tools, management of heap memory is a complex task in elPrep, and it became a serious productivity bottleneck in its original implementation language during recent further development of elPrep. We therefore investigated three alternative programming languages: Go and Java using a concurrent, parallel garbage collector on the one hand, and C++17 using reference counting on the other hand for handling large amounts of heap objects. We reimplemented elPrep in all three languages and benchmarked their runtime performance and memory use.

Results: The Go implementation performs best, yielding the best balance between runtime performance and memory use. While the Java benchmarks report a somewhat faster runtime than the Go benchmarks, the memory use of the Java runs is significantly higher. The C++17 benchmarks run significantly slower than both Go and Java, while using somewhat more memory than the Go runs. Our analysis shows that concurrent, parallel garbage collection is better at managing a large heap of objects than reference counting in our case.

Conclusions: Based on our benchmark results, we selected Go as our new implementation language for elPrep, and recommend considering Go as a good candidate for developing other bioinformatics tools for processing SAM/BAM data as well.

I must admit this is the most hilarious bioinformatics paper I have seen in a long-time. “Benchmarking” is a common practice for kits in biochemistry labs, because most of those commerical kits are black boxes. Some people took that concept to bioinformatics programs like genome assemblers and k-mer counting programs. Although such programs are not black boxes, an independent comparison serves useful purpose by discounting the claims of the authors. “Benchmarking” Java, C++ and Go takes that approach to a ridiculous level. What are you really benchmarking - your programming skills? Heng Li explained it the best - “If you use C++ like C, you get C-like performance. If you use C++ like python, you get python-like performance (unless you know C++ in and out). How to write C++ makes big differences.”.


Written by M. //

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