View source: R/evaluate_bias.R

evaluate_bias | R Documentation |

This function will perform a series of leave-one-out regressions to evaluate the contribution of individual positions to overall RPF count.

evaluate_bias( dat, which_column = "count", transcripts_fa_fname, transcripts_length_fname, trunc5 = 20, trunc3 = 20, num_f5_codons = 6, num_f3_codons = 6, type = "codon", metric = "corr" )

`dat` |
data frame containing regression predictors and column of RPF counts |

`which_column` |
character; name of column containing counts |

`transcripts_fa_fname` |
character; file path to transcriptome .fasta file |

`transcripts_length_fname` |
character; file path to transcriptome lengths file |

`trunc5` |
integer; number of codons (starting at start codon) to omit in codon correlation regression |

`trunc3` |
integer; number of codons (starting at stop codon) to omit in codon correlation regression |

`num_f5_codons` |
integer; number of codons 5' of A site to include in regression |

`num_f3_codons` |
integer; number of codons 3' of A site to include in regression |

`type` |
character; one of 'codon' or 'nt' |

`metric` |
character; one of 'corr' or 'norm' |

A named numeric vector of positional contributions to RPF count. Values will correspond to either the decrease in correlation between predicted and true RPF counts in the leave-one-out model (as computed in the 'iXnos' model), or the norm of regression coefficients at that position.

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