LS-SNP: large-scale annotation of coding non-synonymous SNPs based on multiple information sources

Bioinformatics. 2005 Jun 15;21(12):2814-20. doi: 10.1093/bioinformatics/bti442. Epub 2005 Apr 12.


Motivation: The NCBI dbSNP database lists over 9 million single nucleotide polymorphisms (SNPs) in the human genome, but currently contains limited annotation information. SNPs that result in amino acid residue changes (nsSNPs) are of critical importance in variation between individuals, including disease and drug sensitivity.

Results: We have developed LS-SNP, a genomic scale software pipeline to annotate nsSNPs. LS-SNP comprehensively maps nsSNPs onto protein sequences, functional pathways and comparative protein structure models, and predicts positions where nsSNPs destabilize proteins, interfere with the formation of domain-domain interfaces, have an effect on protein-ligand binding or severely impact human health. It currently annotates 28,043 validated SNPs that produce amino acid residue substitutions in human proteins from the SwissProt/TrEMBL database. Annotations can be viewed via a web interface either in the context of a genomic region or by selecting sets of SNPs, genes, proteins or pathways. These results are useful for identifying candidate functional SNPs within a gene, haplotype or pathway and in probing molecular mechanisms responsible for functional impacts of nsSNPs.

Availability: CONTACT:

Supplementary information:

Publication types

  • Evaluation Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Algorithms
  • Chromosome Mapping / methods*
  • Database Management Systems
  • Databases, Genetic*
  • Information Storage and Retrieval / methods
  • Open Reading Frames / genetics
  • Polymorphism, Single Nucleotide / genetics*
  • Proteins / analysis
  • Proteins / chemistry*
  • Proteins / genetics*
  • Sequence Alignment / methods
  • Sequence Analysis, DNA / methods*
  • Sequence Analysis, Protein / methods*
  • Software*
  • Systems Integration


  • Proteins