Tag: SNP

EM-SNP – Allele Frequency Estimation, SNP Detection and Association Studies

EM-SNP

:: DESCRIPTION

EM-SNP is an unified approach for allele frequency estimation, SNP detection and association studies based on pooled sequencing data using EM algorithms

::DEVELOPER

Fengzhu Sun

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX
  • R

:: DOWNLOAD

  EM-SNP

:: MORE INFORMATION

Citation

Quan Chen and Fengzhu Sun (2013):
A unified approach for allele frequency estimation, SNP detection and association studies on pooled sequencing data using EM algorithms.
BMC Genomics. 2013;14 Suppl 1:S1. doi: 10.1186/1471-2164-14-S1-S1.

SnipViz – A SNP Visualizer

SnipViz

:: DESCRIPTION

SnipViz is a client-side software tool designed to disseminate multiple versions of related gene and protein sequences on web sites.

::DEVELOPER

SnipViz team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • JavaScript

:: DOWNLOAD

 SnipViz

:: MORE INFORMATION

Citation

BMC Res Notes. 2014 Jul 23;7:468. doi: 10.1186/1756-0500-7-468.
SnipViz: a compact and lightweight web site widget for display and dissemination of multiple versions of gene and protein sequences.
Jaschob D, Davis TN, Riffle M

SNPLINK – Multipoint Linkage analysis of Densely Distributed SNP data

SNPLINK

:: DESCRIPTION

SNPLINK is a Perl script that performs full genome linkage analysis of high-density single nucleotide polymorphism (SNP) marker sets. It first removes unlikely genotypes and performs parametric and non-parametric linkage analysis in a fully automated fashion. The presence of linkage disequilibrium (LD) between closely spaced SNP markers can falsely inflate linkage statistics. SNPLINK removes LD from the marker sets in an automated fashion and then carries out linkage analysis after LD has been removed. SNPLINK can compute both parametric and non-parametric statistics, utilising the freely available ALLEGRO and MERLIN software. Graphical outputs of whole genome multipoint linkage statistics are provided allowing comparison of results before and after the removal of LD

::DEVELOPER

Emily Webb, Professor Richard Houlston

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

SNPLINK

:: MORE INFORMATION

Citation

Webb et al. (2005)
SNPLINK: multipoint linkage analysis of densely distributed SNP data incorporating automated linkage disequilibrium removal.
Bioinformatics.21 (13): 3060-3061.

SegCNV – Detect Germline Copy Number Variations in SNP Array data

SegCNV

:: DESCRIPTION

SegCNV is a software package, implemented in C++, to detect germline copy number variations in SNP array data. Currently, SegCNV supports Illumina 550K and 610K genotyping platforms

::DEVELOPER

 DCEG

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • C++ compiler

:: DOWNLOAD

 SegCNV

:: MORE INFORMATION

Citation

Genet Epidemiol. 2012 May;36(4):373-83. doi: 10.1002/gepi.21631.
An integrative segmentation method for detecting germline copy number variations in SNP arrays.
Shi J, Li P.

CRaVe 0.0.2 – Association Tests between sets of SNPs and a Phenotype

CRaVe 0.0.2

:: DESCRIPTION

CRaVe is a free, open source, software package designed to perform a range of association tests between sets of SNPs and a phenotype.

::DEVELOPER

 DCEG

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • R package

:: DOWNLOAD

 CRaVe

:: MORE INFORMATION

Citation

Eur J Hum Genet. 2013 Jun;21(6):680-6. doi: 10.1038/ejhg.2012.220. Epub 2012 Oct 24.
Statistical tests for detecting associations with groups of genetic variants: generalization, evaluation, and implementation.
Ferguson J, Wheeler W, Fu Y, Prokunina-Olsson L, Zhao H, Sampson J.

SNPAAMapperT2K – Genome-wide SNP Downstream Analysis and Annotation Pipeline

SNPAAMapperT2K

:: DESCRIPTION

SNPAAMapperT2K is a genome-wide SNP downstream analysis and annotation pipeline for species annotated with NCBI .tbl data files (e.g. Arabidopsis).

::DEVELOPER

Computational Biology Lab at Indiana State University

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • PErl

:: DOWNLOAD

 SNPAAMapperT2K

:: MORE INFORMATION

Citation

Bioinformation. 2014 Nov 27;10(11):711-5. doi: 10.6026/97320630010711. eCollection 2014.
SNPAAMapperT2K: A genome-wide SNP downstream analysis and annotation pipeline for species annotated with NCBI.tbl data files.
Bai Y

TAGOOS 0.2.1 – Associated Tag SNP Boosting

TAGOOS 0.2.1

:: DESCRIPTION

TAGOOS  (TAG SNP bOOSting) is a nucleotide scoring tool for non-coding (Intronic and intergenic) regions.

::DEVELOPER

The TAGC Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

TAGOOS 

:: MORE INFORMATION

Citation:

González A, Artufel M, Rihet P.
TAGOOS: genome-wide supervised learning of non-coding loci associated to complex phenotypes.
Nucleic Acids Res. 2019 Aug 22;47(14):e79. doi: 10.1093/nar/gkz320. PMID: 31045203; PMCID: PMC6698643.

SNPAAMapper 2.0 – A SNP Amino Acid Mapping tool

SNPAAMapper 2.0

:: DESCRIPTION

SNPAAMapper is a downstream variant annotation program that can effectively classify variants by region (e.g. exon, intron, etc), predict amino acid change type (e.g. synonymous, non-synonymous mutation, etc), and prioritize mutation effects (e.g. CDS versus 5’UTR, etc).

::DEVELOPER

Computational Biology Lab at Indiana State University

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • PErl

:: DOWNLOAD

  SNPAAMapper

:: MORE INFORMATION

Citation

Bioinformation. 2013 Oct 16;9(17):870-2. doi: 10.6026/97320630009870. eCollection 2013.
SNPAAMapper: An efficient genome-wide SNP variant analysis pipeline for next-generation sequencing data.
Bai Y1, Cavalcoli J.

fastStructure 1.0 – Inferring Population Structure from SNP Genotype data

fastStructure 1.0

:: DESCRIPTION

fastStructure is an algorithm for inferring population structure from large SNP genotype data.

::DEVELOPER

Pritchard Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / Mac OsX
  • Python
  • Numpy
  • Scipy
  • Cython
  • GNU Scientific Library

:: DOWNLOAD

 fastStructure

:: MORE INFORMATION

Citation

fastSTRUCTURE: variational inference of population structure in large SNP data sets.
Raj A, Stephens M, Pritchard JK.
Genetics. 2014 Jun;197(2):573-89. doi: 10.1534/genetics.114.164350