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| we first scan for 'A', 'C', then 'G' and 'T', | ||
| so the final consensus string will be biased towards more A's, then C's, G's and T's. | ||
| This simply based on which nucleotide counts it will encounter first in the profile matrix. | ||
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I may add some examples of multiple consensus strings. I may also add another solution that returns all consensus strings.
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Added an example, but I will pass on adding another solution. I think time will be better spent on the BioPython recipes.
docs/src/rosalind/10-cons.md
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| # make profile matrix | ||
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| ## Is it possible to do this in a more efficient vectorized way? I wanted to see if we could do countmap() for each column in a simple way that would involve looping over each column. I think this ended up being more efficient since we are just looping over each of the nucleotides |
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Is it possible to do this in a more efficient vectorized way? I wanted to see if we could do countmap() for each column in a simple way that would involve looping over each column. I think this ended up being more efficient since we are just looping over each of the nucleotides
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Preview at https://biojulia.github.io/BioTutorials/20 |
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Preview at https://biojulia.github.io/BioTutorials/20 |
Hey nice, this works! |
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Preview at https://biojulia.github.io/BioTutorials/20 |
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Preview at https://biojulia.github.io/BioTutorials/20 |
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Going to delete this branch and open up a new PR that is on top of |
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