biofold/phd-snpg repository overview

  Emidio Capriotti, 2016.
  Scripts are licensed under the Creative Commons by NC-SA license.
  PhD-SNPg is a program for the annotation of single nucleotide variants that uses data and tools from the UCSC repository.

    PhD-SNPg can take in input a single variation or a file containing multiple single nucleotide variants.
    For web installation append --web at the of all commands.

  - For single variants use the option -c:
    python predict_variants.py chr7,158715219,A,G -g hg19 -c

  - For input file the input can be either:

    plain tab separated file with 4 columns: chr, position, ref, alt
    python predict_variants.py test/test_variants_hg38.tsv -g hg38

    vcf file with in the firt 5 columns: chr, position, rsid, ref, alt
    python predict_variants.py test/test_variants_hg19.vcf.gz --vcf -g hg19

    PhD-SNPg returns in output:

    PREDICTION: Pathogenic or Benign
    SCORE: a probabilistic score between 0 and 1. If the score is >0.5 the variants is predicted to be Pathogenic.
    FDR: The false discovery rate associated to higher/lower SCORE.
    PhyloP100: PhyloP100 in the mutated position.
    AvgPhyloP100: Average value of PhyloP100 in a 7-nucleotide window around the mutated position.

    The scores added as extra columns to the input file. An example of output is reported below.

    #CHROM  POS     REF     ALT     CODING  PREDICTION      SCORE   FDR   PhyloP100       AvgPhyloP100
    1       45331676        G       A       Yes     Pathogenic      0.990   0.022   7.723   3.313
    1       237634938       G       T       Yes     Benign  0.005   0.011   -4.248  5.939
    2       26461838        G       A       Yes     Benign  0.011   0.022   -0.064  6.116
    2       166009835       A       G       Yes     Benign  0.176   0.072   0.591   4.188
    2       174753570       G       C       Yes     Pathogenic      0.777   0.087   -1.937  5.439
    5       44305045        G       A       Yes     Pathogenic      0.985   0.026   1.655   3.964
    python predict_variants.py test/test_variants_hg19.vcf.gz --vcf -g hg19