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http://www.niehs.nih.gov/research/resources/software/biostatistics/art/

A set of simulation tools to generate synthetic next-generation sequencing reads. ART simulates sequencing reads by mimicking real sequencing process with empirical error models or quality profiles summarized from large recalibrated sequencing data. ART can also simulate reads using user own read error model or quality profiles. ART supports simulation of single-end, paired-end/mate-pair reads of three major commercial next-generation sequencing platforms: Illumina''''s Solexa, Roche''''s 454 and Applied Biosystems'''' SOLiD. ART can be used to test or benchmark a variety of method or tools for next-generation sequencing data analysis, including read alignment, de novo assembly, SNP and structure variation discovery. ART is implemented in C++ with optimized algorithms and is highly efficient in read simulation. ART outputs reads in the FASTQ format, and alignments in the ALN format. ART can also generate alignments in the SAM alignment or UCSC BED file format.

Proper citation: ART (RRID:SCR_006538) Copy   

•   Source: SciCrunch Registry

http://www.niehs.nih.gov/research/resources/software/biostatistics/eagleview/

An information-rich viewer for next-generation genome assembles with data integration capability. EagleView can display a dozen different types of information including base qualities, machine specific trace signals, and genome feature annotations. It provides an easy way for inspecting visually the quality of a genome assembly and validating polymorphism candidate sites (e.g., SNPs) reported by polymorphism discovery tools. It can also facilitate data interpretation and hypothesis generation. EagleView is a multi-platform application developed with C++ and is available for all three major platforms: Windows, Linux, and Mac OS.

Proper citation: EagleView (RRID:SCR_006859) Copy   

•   Source: SciCrunch Registry

http://snpinfo.niehs.nih.gov/

SNPinfo Web Server is a set of freely available web-based SNP selection tools where investigators can specify genes or linkage regions and select SNPs based on GWAS results, linkage disequilibrium (LD), and predicted functional characteristics of both coding and non-coding SNPs. The algorithm uses GWAS SNP P-value data and finds all SNPs in high LD with GWAS SNPs, so that selection is from a much larger set of SNPs than the GWAS itself. The program can also identify and choose tag SNPs for SNPs not in high LD with any GWAS SNP. We incorporate functional predictions of protein structure, gene regulation, splicing and miRNA binding, and consider whether the alternative alleles of a SNP are likely to have differential effects on function. Users can assign weights for different functional categories of SNPs to further tailor SNP selection. The program accounts for LD structure of different populations so that a GWAS study from one ethnic group can be used to choose SNPs for one or more other ethnic groups. SNP Selection and Functional Information *Candidate Gene SNP Selection (GenePipe):SNP selection for candidate genes based on Genome Wide Association Study (GWAS) results, functional SNP prediction and Linkage Disequilibrium (LD) information. *GWAS Functional SNP Selection (GenomePipe):Functional SNP selection from SNPs that are in high LD with GWAS SNPs *GWAS SNP Selection in Linkage Loci (LinkagePipe):GWAS SNP selection in candidate genomic regions (such as linkage loci) *LD TAG SNP Selection (TagSNP):LD tag SNP selection and visualization for single or multiple populations. Finalization of SNP list from various queries. *SNP Function Prediction (FuncPred): Querying SNP function predictions and ethnic-specific allele frequencies. *SNP Information in DNA Sequence (SNPseq):Visualization of SNP related information in the context of DNA sequence. Preparing DNA Sequence for PCR Primer Design considering SNP information. Detailed information of CpG region.

Proper citation: SNPinfo Web Server (RRID:SCR_010589) Copy   

•   Source: SciCrunch Registry