Re: Variant Graph Support to BioD
On Wednesday, 29 May 2019 at 03:16:19 UTC, Nicholas Wilson wrote: On Tuesday, 28 May 2019 at 09:41:18 UTC, Njagi Mwaniki wrote: Hello I’m Njagi Mwaniki, I am part of the 2019 Google Summer of Code under the Open Bioinformatics Foundation with a project aimed to add variation graph support to BioD under mentors George Githinji and Pjotr Prins. Awsome! can you supply some links please? I don't have a lot of links but the D lib is here https://github.com/biod/biod I'm prototyping a bit of the data structures here in racket https://github.com/urbanslug/GSoC-experiments I plan on writing blog posts soon explaining the graph, it's implementation and progress as well.
Re: Variant Graph Support to BioD
On Tuesday, 28 May 2019 at 21:24:54 UTC, James Blachly wrote: On 5/28/19 5:41 AM, Njagi Mwaniki wrote: Hello I’m Njagi Mwaniki, I am part of the 2019 Google Summer of Code under the Open Bioinformatics Foundation with a project aimed to add variation graph support to BioD under mentors George Githinji and Pjotr Prins. ... VG is a set of tools that already implements variation graphs but which is a bit broad in its focus. In this project we are building upon the existing tools and knowledge from VG and looking for ways to improve its performance in terms of lookups and also its application with small genomes, specifically viruses and smaller mammals such as mice. This sounds like a great project. Be aware that the size of the organism (e.g. mouse) has naught to do with the size of its genome. Thank you. With regards to the complexity of the genome, we're starting with a very small virus dataset and building up from it https://github.com/urbanslug/GSoC-experiments/tree/master/data/RSV/refererence_and_vcf_file The mouse is a possible application area of the genome really and a good place to test the robustness of the tool.
Re: Variant Graph Support to BioD
On Tuesday, 28 May 2019 at 09:41:18 UTC, Njagi Mwaniki wrote: Hello I’m Njagi Mwaniki, I am part of the 2019 Google Summer of Code under the Open Bioinformatics Foundation with a project aimed to add variation graph support to BioD under mentors George Githinji and Pjotr Prins. Awsome! can you supply some links please?
Re: Variant Graph Support to BioD
On 5/28/19 5:41 AM, Njagi Mwaniki wrote: Hello I’m Njagi Mwaniki, I am part of the 2019 Google Summer of Code under the Open Bioinformatics Foundation with a project aimed to add variation graph support to BioD under mentors George Githinji and Pjotr Prins. ... VG is a set of tools that already implements variation graphs but which is a bit broad in its focus. In this project we are building upon the existing tools and knowledge from VG and looking for ways to improve its performance in terms of lookups and also its application with small genomes, specifically viruses and smaller mammals such as mice. This sounds like a great project. Be aware that the size of the organism (e.g. mouse) has naught to do with the size of its genome.
Variant Graph Support to BioD
Hello I’m Njagi Mwaniki, I am part of the 2019 Google Summer of Code under the Open Bioinformatics Foundation with a project aimed to add variation graph support to BioD under mentors George Githinji and Pjotr Prins. What are variation graphs? Well it’s sequence graph that is used to represent variation in a genome. Let me explain. A sequence graph also an alignment graph, breakpoint graph, or adjacency graph is a bidirected graph in which the vertices represent segments of DNA and the edges represent adjacency between segments in a genome. (from Wikipedia) Sequence graphs have long been proposed as a replacement for reference genomes which are linear structures/sequences of bases. A variation graph is a sequence graph together with a set of paths representing possible sequences from a population[1]. Despite these ideas being around for a long time we haven’t yet been able to use sequence graphs in real life bioinformatics applications such as sequence alignment or determining homology. This is what we hope to speed up. VG is a set of tools that already implements variation graphs but which is a bit broad in its focus. In this project we are building upon the existing tools and knowledge from VG and looking for ways to improve its performance in terms of lookups and also its application with small genomes, specifically viruses and smaller mammals such as mice. [1] Variation graph toolkit improves read mapping by representing genetic variation in the reference
