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SNP Identification using Probability of Every Read

eagle-i ID

http://eagle-i.itmat.upenn.edu/i/0000013a-bd6f-ac79-d69a-d90d80000000

Resource Type

  1. Algorithmic software component

Properties

  1. Resource Description
    "Sniper is a Bayesian probabilistic model that enables SNP discovery in both unique and repetitive regions of a genome by utilizing the information from multiply-mapped sequence reads." "Sniper can perform all steps of analysis, including read map generation, organization of read maps into singly mapped and multiply mapped partitions, and SNP calling. Although Sniper is designed to use Bowtie for read alignment, any alignment program can be specified, as long as the read map output is stored in a SAM-formatted file."
  2. Additional Name
    Sniper
  3. Used by
    Kim Laboratory: Computational Evolutionary Biology
  4. Version
    1.6.4
  5. Operating System
    Unix
  6. Data Input
    Raw sequence files
  7. Data Input
    Map file
  8. Data Input
    Reference genome
  9. Data Output
    SNP calls
  10. Related Publication or Documentation
    Sniper: improved SNP discovery by multiply mapping deep sequenced reads
  11. Website(s)
    http://kim.bio.upenn.edu/software/sniper.shtml
  12. Related Technique
    Single-nucleotide polymorphism analysis
  13. Related Technique
    Next generation DNA sequencing
  14. Related Technique
    Genotyping assay
  15. Developed by
    Kim, Junhyong, Ph.D.
  16. Developed by
    Simola, Daniel F., Ph.D.
  17. Software license
    Academic software license
  18. Algorithm used
    Burrows-Wheeler technique
  19. Algorithm used
    Bayesian Model
  20. Coded in
    Python
 
RDFRDF
 
Provenance Metadata About This Resource Record
  1. workflow state
    Published
  2. contributor
    fcoldren
  3. created
    2012-11-01T15:28:00.326-04:00
  4. creator
    fcoldren
  5. modified
    2013-04-02T12:39:37.406-04:00

Copyright © 2016 by the President and Fellows of Harvard College
The eagle-i Consortium is supported by NIH Grant #5U24RR029825-02 / Copyright 2016