Sequencing your DNA with a USB dongle and open source code

• pestalotiopsis

  1 7 0.0 Python

  Assembly and phylogentic analysis pipeline for draft genome of a Pestalotiopsis fungi.

  

That's not true. I just did a high-quality sequence and assembly of a new species of fungus from my home lab using nanopore. You can see all my code used for assembly and analysis that will be referenced in a paper I plan to publish in Jan here: https://github.com/EverymanBio/pestalotiopsis

• TMAP

  1 49 10.0 C

  Torrent Mapping Alignment Program (by iontorrent)

  

bwa specifically performs a burrows wheeler transform of a 3GB string. other mapping algorithms usually rely on some sort of indexing of the genome. the program then loads this into memory and queries that index for each “read” (a dna fragment from the dna sequencer).

when i worked on https://github.com/iontorrent/tmap we thought it would be a good idea to do something like a “local alignment” (using https://en.wikipedia.org/wiki/Smith–Waterman_algorithm) after doing a lookup into a burrows wheeler transform on a substring of the “read.”

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

• Flye

  4 730 4.7 C

  De novo assembler for single molecule sequencing reads using repeat graphs

You totally should, it's a lot of fun. I'd suggest trying to find some bacterial genome sequencing (like E. coli) done on nanopore if you're interested in those data. I don't have a link to any handy right now, otherwise I'd post here, but assembling bacterial genomes is shockingly easy these days and doesn't need near as many resources as doing a human genome, so it's great for learning (I love the assembler Flye [1] for this).

And RE: home sequencing, honestly the hardest part for a beginner will likely be the sample prep, since that takes some combination of wet lab experience and expensive equipment. I really wish molecular biology was as simple to get hacking on as writing software. The lag time between doing an experiment and getting a result is so much longer than waiting for things to compile, it just makes improving your skills take longer.

[1] https://github.com/fenderglass/Flye

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