type: gene_score
filename: LOEUF_scores.csv.gz
scores:
  - id: LOEUF
    desc: "90% upper bound for the confidence interval for observed/expected pLoF variation ratio"
    histogram:
      type: number
      number_of_bins: 100
      view_range:
        min: 0
        max: 2
      x_log_scale: false
      y_log_scale: false
    small_values_desc: "intolerant to pLoF variation"
    large_values_desc: "tolerant to pLoF variation"


  - id: LOEUF_rank
    desc: "Gene ranks after sorting by LOEUF scores"
    histogram:
      type: number
      number_of_bins: 100
      view_range:
        min: 0
        max: 20000
      x_log_scale: false
      y_log_scale: false
    small_values_desc: "intolerant to pLoF variation"
    large_values_desc: "tolerant to pLoF variation"



meta:
  summary: |
    Degree of intolerance to predicted Loss-of-Function (pLoF) variation
  description: |
    #### Introduction
    Degree of intolerance to pLoF variation in each gene is assessed using the continuous metric of the observed/expected ratio. A confidence interval is estimated around the ratio. The loss-of-function observed/expected upper bound fraction (LOEUF) is the 90% upper bound of this confidence interval.  
    #### Score definitions
    Low scores or ranks indicate intolerance to loss of function mutations.

    #####Processing Details
    Supplementary Data, Table 11 downloaded on 2024 May 5 from [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334197/#MOESM1](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334197/#MOESM1).

    DataPrep.py utilizes only scores for canonical transcripts (column canonical = TRUE). The 'oe\_lof\_upper' column in the downloaded file is used for LOEUF scores. LOEUF_ranks are calculated based on LOEUF scores. Resulting file LOEUF\_scores.csv.gz has 3 columns: gene, LOEUF score, LOEUF rank.

