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project:openfooddna [2015/06/06 12:05] – [Team] heluc | project:openfooddna [2015/06/06 16:30] (current) – heluc | ||
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===== Open Food DNA ===== | ===== Open Food DNA ===== | ||
- | (screenshots or sketches up here) | + | The basic idea is to carry out a citizen science project to compile an open dataset of DNA information about food and beverages. |
- | Brief description goes here. Add sections below if you need more room. | + | Many more details about the project on the dedicated wiki [[http:// |
- | Include links to your demo and/or source code. | + | Take beer. The assumption is that the DNA content (genetic |
- | ===== Data ===== | + | Somebody else (working for a [[http:// |
- | + | ||
- | * List and link your actual and ideal data sources. | + | |
===== Team ===== | ===== Team ===== | ||
Line 17: | Line 15: | ||
* Soraia Binz, designer [[https:// | * Soraia Binz, designer [[https:// | ||
* [[user: | * [[user: | ||
- | | + | |
+ | Disclaimer: Luc Henry and Gianpaolo Rando run the BeerDeCoded project at the open laboratory Hackuarium in Renens and came to get input about data analysis. | ||
+ | |||
+ | ===== Data ===== | ||
+ | |||
+ | In this project, genetic data will initially be qualitative sequencing data. The idea is to transform this sequencing data into binary data about the presence=1/ | ||
+ | |||
+ | ==== Random data generation ==== | ||
+ | |||
+ | Since we do not have data yet, we generated a random dataset using this Octave/ | ||
+ | (generates a table containing random binary data for 10 samples and 30 parameters and calculate the euclidian distance matrix) | ||
+ | |||
+ | < | ||
+ | # | ||
+ | % lines : beer samples | ||
+ | li = 10; | ||
+ | % columns : species and sub species | ||
+ | co = 30; | ||
+ | M = round(rand(li, | ||
+ | O = zeros(li); | ||
+ | for i = 1:li | ||
+ | for j = 1:i | ||
+ | O(i,j) = norm( M(:, | ||
+ | endfor | ||
+ | endfor | ||
+ | O | ||
+ | </ | ||
+ | |||
+ | We did not plot this data yet. | ||
+ | |||
+ | ==== Metadata ==== | ||
+ | |||
+ | We searched for metadata to add to the data generated and making it look more real. Few of our findings: | ||
+ | |||
+ | | ||
+ | |||
+ | Webpage of [[http:// | ||
+ | |||
+ | Download data [[http:// | ||
+ | |||
+ | ==== Workflow ==== | ||
+ | |||
+ | Starting from a table containing m samples (S1-Sm) and a [m x n] matrix of binary data (D1-Dn species are either present or not) for each sample, we can build a [m x m] matrix of Euclidian distances between the samples. | ||
+ | |||
+ | {{ : | ||
+ | |||
+ | The metadata entries (M1-Mn) can be attached to this matrix and used to generate a plot that contains sample points with associated characteristics. This plot contains every single sample present in the database. | ||
+ | |||
+ | A user friendly interface has to be built in order for the beer lover to choose the beers they know, and compare this " | ||
+ | |||
+ | {{ : | ||
+ | |||
+ | ===== Prototype ===== | ||
+ | |||
+ | We " | ||
+ | |||
+ | We have a main display with three visualisation types you can switch from: Plot (display beer samples based on Euclidian distance), Tree (same but in a tree fashion), Rank (forget distances | ||
+ | |||
+ | Here is the Plot: | ||
+ | |||
+ | {{ : | ||
+ | |||
+ | Here is the Tree (can switch from linear to circular representation): | ||
+ | |||
+ | {{ : | ||
+ | |||
+ | Here is the Plot being transformed into a Rank: | ||
+ | |||
+ | {{ : | ||
+ | |||
+ | Transformation from Plot to Rank was taken from the following example: | ||
+ | http:// | ||
===== Links ===== | ===== Links ===== | ||
+ | The original pad where we worked is here (many more info from web searches) | ||
* https:// | * https:// | ||
- | * Relevant documentation ... | ||
- | * Blog or forum posts ... | ||
- | * Tools you used ... | ||
- | | ||
- | {{tag> | ||
+ | The kickstarter campaign of the BeerDeCoded project is here: | ||
+ | * https:// | ||
+ | |||
+ | The wiki of the DIY biology Hackuarium association is here: | ||
+ | * http:// | ||
+ | |||
+ | {{tag> |