Re: They wrote the fastest parallelized BAM parser in D
I did some image processing work with D and didn't find the lack of specific D tools for visualization a big issue. There is some advantage to being able to perform visualization tasks in the same lanaguage as you do the data processing work, but I wouldn't this this would be a major obstacle. I personally prefer the model where I create a tool that takes some input and provides output in a suitable format that I can load to a proper statistical environment (R or Julia ) for visualisation and manipulation. Therefore I would rather write a tool that performs a single task optimally and pipes its output to a different tool for another task. This way I can use the tools and allow for flexible pipelines. rawdata -> clean -> QC –> to format Y –> to format X -> tool A -> tool B-> visualize George
Re: They wrote the fastest parallelized BAM parser in D
.NET actually already has a foothold in bioinformatics, specially in user facing software and steering of reading equipments and robots. So D's needs a story over C# and F# (alongside WPF for data visualization) use cases. -- Paulo Though when it comes to open source bioinformatics projects, Perl and Python have a large foothold among most most bioinformaticians. Most utilities that require speed are often written in C and C++ (BLAST, HMMER, SAMTOOLS etc). I think D stands a good chance as a language of choice for bioinformatics projects. George
They wrote the fastest parallelized BAM parser in D
http://bioinformatics.oxfordjournals.org/content/early/2015/02/18/bioinformatics.btv098.full.pdf+html and a feature http://google-opensource.blogspot.nl/2015/03/gsoc-project-sambamba-published-in.html?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed:+GoogleOpenSourceBlog+(Google+Open+Source+Blog) D may hold a sweet spot in bioinformatics where you often require quick turnaround (productivity) , raw speed and agility.
