Analyzing the Operational RNA Code for Amino Acids - Using R Read / - - PowerPoint PPT Presentation

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analyzing the operational rna code for amino acids using r
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Analyzing the Operational RNA Code for Amino Acids - Using R Read / - - PowerPoint PPT Presentation

Aug 28, 2023 154 likes •580 views

Analyzing the Operational RNA Code for Amino Acids - Using R Read / Contact me: Read / Contact me: R-statistics.com Tal Galili [1] , Shaul Shaul [2] , Dror Berel [3] , Yoav Benjamini [4] [1] Department of Statistics and Operations Research, Tel

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Analyzing the Operational RNA Code for Amino Acids - Using R

Read / Contact me:

Tal Galili[1], Shaul Shaul[2], Dror Berel [3], Yoav Benjamini [4]

[1] Department of Statistics and Operations Research, Tel Aviv University, Israel. [2] Department of Zoology, Tel Aviv University, Israel. [3] Cedars-Sinai Medical Center. [4] Department of Statistics and Operations Research, Tel Aviv University, Israel.

Read / Contact me: R-statistics.com

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Story

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ATP

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Data

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Data source

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55 Archaea tRNA sequences

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55 Archaea tRNA sequences

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Visualize

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2342 2342 Data rows

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Mosaic plot: nucleotide distribution in tRNA acceptor stem

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Sequence logo plot

(Schneider and Stephens - 1990)

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Title ? Colors? X labels? Colors?

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  • > “grid“ graphics….
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Title ? Colors? X labels? Colors?

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Codon distribution, per location, per Amino Acid

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Analyze

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CART

(Classification and regression trees)

  • Goal predict target variable
  • Method: recursively partition

explanatory variables

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CART

(Classification and regression trees)

  • !"
  • - “The Blind Men and the Elephant” by John Godfrey Saxe (1816-1887)
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CART

with default values

Library(rpart)

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CART

Predictive success ? (use.n = T)

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CART

Percent of success in prediction

Red = bellow 60% fit

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Cross validation – Relative error

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Cross validation – Misclassification rate

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Bigger tree?

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Bigger tree?

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Cross validation – Misclassification rate

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Relative importance for each letter in the model

(Sum of information gain in the use of each letter in the model)

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Relative importance for each letter in the model

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Results

  • 20% misclassification in prediction
  • Same acceptor stem RNA can code for for different Amino Acids
  • In different Archaeas
  • In the same Archaea

Conclusions Conclusions

  • There is code in the acceptor stem
  • It is not enough
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Read / Contact me:

Thank you !

Read / Contact me: R-statistics.com

Tal Galili[1], Shaul Shaul[2], Yoav Benjamini [3], Dror Berel [4]

[1] Department of Statistics and Operations Research, Tel Aviv University, Israel. [2] Department of Zoology, Tel Aviv University, Israel. [3] Department of Statistics and Operations Research, Tel Aviv University, Israel. [4] Cedars-Sinai Medical Center.