In standard blog fashion, i've gone silent with posts. My personal life and "workaphilia" has led me to focus my energies on other (analog) pursuits. I'm now out of industry and in the protective cocoon of academia. I start my doctorate in a week and have picked up a new project that will mesh with my sailing interests and , hopefully, eventually extend to my degree.
We have great electronics to give real-time stats and boat speed and heading through the velocitek and tactic. However, they are pretty closed and, hence, it is difficult to get data off of these tools. Furthermore, the senors have (at least at output) low sampling rate (gps is about 2 hz.) In addition, there isn't any software to be able to directly compare individual boat performances across a fleet.
Thus, I've sought to try to develop a low cost, open-source hardware to be able to measure various dynamic properties of the boat. I am currently focusing on boat position and axial orientation (gps and gyroscope.) My dream is to achieve two fold: a) to be able to empirically measure two-boat testing and eventually b) create enough data for a machine learning application. I still need to think of a name for my project...
In my first prototype, I've ordered the Arduino Uno, a triple-axis gyroscope, and a gps breakout. I'm excited to have great a gryo at ~30 kHz (!) and a gps at 10 Hz. These high sampling rates should allow me to do some smoothing and get accurate recordings. My brother is already proving to be an awesome asset, as he has already been playing around with an Uno, building a camera slider.
Quickly, I've gotten the gyro to talk to the Uno and produce output. I'm waiting for the arrival of my gps unit, but I have started developing a library to help keep my onboard software organized. Hopefully, I'll have all the hardware talking and logging by a week or two. I'm already thinking about adding wifi shields to get real time info out. From there, I'll build a second sensor nest.
Our sailing season ends in 2 months, so I'll be on a crunch to getting something out. In mid-september, I'll be very happy to have to have two devices talking to a android device. Then, I can start writing higher level api (android side) to start making two-boat comparisons!
Monday, August 20, 2012
Saturday, February 25, 2012
AGBT 2012
Like half of all blog posts on the internet, I have to start by apologizing for neglecting to update the blog regularly. No reason to get into details, so I'll go straight to the post.
Last week, while I was learning to tango in Buenos Aires, my colleagues presented a poster we put together detailing the many hours we've put into establishing a procedure for doing hybrid de novo assemblies with Illumina and 454 sequencing data. The experience was great and perhaps my first front-to-back computational research project. We achieved some synergistic results and have since included the procedures into our own analysis offerings. We are receiving some flattering attention from the BROAD institute as well as from everywhere across the web-sphere. Below is the abstract and here is the poster.
Evaluation of Strategies for De Novo Assembly of Genomes and Transcriptomes Using Combined Illumina and Roche 454 Sequencing Data.
Jon R. Armstrong, Jarret I. Glasscock, Ian Schillebeeckx, and Navish Dadighat.
Cofactor Genomics, St. Louis, MO
The emergence of next-generation sequencing platforms has made low-cost sequencing an attractive approach for de novo assembly of genomes and transcriptomes. The two most widely used next-generation platforms for de novo assembly are the Illumina and Roche 454 and each system has particular strengths and weaknesses. The Illumina generates short reads (100 bp) while the Roche 454 FLX+ produces read lengths close to Sanger (800 bp), however the price per base on the Roche 454 machine is approximately 50x more costly than the Illumina platform. Few studies exist which employ assembly of both read types [1, 2], and the methods used are not explicitly described. If strategies were determined to assemble data from both platforms, and capitalize on the strengths of each system while minimizing the weaknesses and cost, researchers could apply them during future de novo assembly projects. To this end, we evaluated multiple strategies for de novo assembly of combined Illumina and Roche 454 sequencing data, originating from several genomes and transcriptomes of varying size and origin. Our analysis shows that assembly of the Roche 454 reads, prior to combining with Illumina raw reads, produces the best assembly metrics for genomes and transcriptomes, however, depending on the type of assembly it may be detrimental to assemble Illumina reads prior to combining with Roche 454 data. We will also present the types of assemblers used and workflows specific to genome and transcriptome assemblies.
1. Reinhardt JA, Baltrus DA, Nishimura MT, Jeck WR, Jones CD, Dangl JL. De novo assembly using low-coverage short read sequence data from the rice pathogen Pseudomonas syringae pv. oryzae. Genome Res. 2009 February; 19(2): 294–305.
2. Nowrousian M, Stajich JE, Chu M, Engh I, Espagne E, Halliday K, Kamerewerd J, Kempken F, Knab B, Kuo HC, Osiewacz HD, Pöggeler S, Read ND, Seiler S, Smith KM, Zickler D, Kück U, Freitag M. De novo assembly of a 40 Mb eukaryotic genome from short sequence reads: Sordaria macrospora, a model organism for fungal morphogenesis. PLoS Genet. 2010 Apr 8;6(4):e1000891.
Evaluation of Strategies for De Novo Assembly of Genomes and Transcriptomes Using Combined Illumina and Roche 454 Sequencing Data.
Jon R. Armstrong, Jarret I. Glasscock, Ian Schillebeeckx, and Navish Dadighat.
Cofactor Genomics, St. Louis, MO
The emergence of next-generation sequencing platforms has made low-cost sequencing an attractive approach for de novo assembly of genomes and transcriptomes. The two most widely used next-generation platforms for de novo assembly are the Illumina and Roche 454 and each system has particular strengths and weaknesses. The Illumina generates short reads (100 bp) while the Roche 454 FLX+ produces read lengths close to Sanger (800 bp), however the price per base on the Roche 454 machine is approximately 50x more costly than the Illumina platform. Few studies exist which employ assembly of both read types [1, 2], and the methods used are not explicitly described. If strategies were determined to assemble data from both platforms, and capitalize on the strengths of each system while minimizing the weaknesses and cost, researchers could apply them during future de novo assembly projects. To this end, we evaluated multiple strategies for de novo assembly of combined Illumina and Roche 454 sequencing data, originating from several genomes and transcriptomes of varying size and origin. Our analysis shows that assembly of the Roche 454 reads, prior to combining with Illumina raw reads, produces the best assembly metrics for genomes and transcriptomes, however, depending on the type of assembly it may be detrimental to assemble Illumina reads prior to combining with Roche 454 data. We will also present the types of assemblers used and workflows specific to genome and transcriptome assemblies.
1. Reinhardt JA, Baltrus DA, Nishimura MT, Jeck WR, Jones CD, Dangl JL. De novo assembly using low-coverage short read sequence data from the rice pathogen Pseudomonas syringae pv. oryzae. Genome Res. 2009 February; 19(2): 294–305.
2. Nowrousian M, Stajich JE, Chu M, Engh I, Espagne E, Halliday K, Kamerewerd J, Kempken F, Knab B, Kuo HC, Osiewacz HD, Pöggeler S, Read ND, Seiler S, Smith KM, Zickler D, Kück U, Freitag M. De novo assembly of a 40 Mb eukaryotic genome from short sequence reads: Sordaria macrospora, a model organism for fungal morphogenesis. PLoS Genet. 2010 Apr 8;6(4):e1000891.
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