• Aucun résultat trouvé

SNiPlay: a web-based tool for detection, management and analysis of SNP (C900)

N/A
N/A
Protected

Academic year: 2021

Partager "SNiPlay: a web-based tool for detection, management and analysis of SNP (C900)"

Copied!
2
0
0

Texte intégral

(1)

PAG-XIX(C900) SNiPlay: A Web-Based Tool For Detection, Management And Analysis Of SNP.

Plant & Animal Genomes XIX Conference

January 15-19, 2011

Town & Country Convention Center

San Diego, CA

C900: Poster and Demo

SNiPlay: A Web-Based Tool For Detection, Management And Analysis Of SNP.

Alexis Dereeper

1

, Stéphane Nicolas

1

, Gregory Carrier

1

, Loic Le Cunff

1

, Roberto Bacilieri

1

, Agnès

Doligez

1

, Jean-Pierre Peros

1

, Patrice This

1

, Manuel Ruiz

2

1 Diversity, Genetics and Genomics of grapevine UMR DIAPC 1097 INRA place Viala 34000 Montpellier France

2 Integration of Data avenue agropolis CIRAD 34000 Montpellier France

The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine genetic data with the genome’s structure and with external data available.

In this context, we developed SNiPlay, a flexible, user-friendly and integrative web-based tool dedicated to polymorphism discovery and analysis. It integrates:

1) a pipeline, freely accessible through the internet, combining existing software with new tools to detect SNPs and to compute different kinds of statistical indices and graphical layouts for SNP data. From Sanger sequencing traces, multiple sequence alignments or genotyping data given as input, SNiPlay detects SNPs and insertion/deletion events. In a second time, it sends sequences and genotyping data into a series of modules in charge of various post-processes: physical mapping to a reference genome, annotation (genomic position, intron/exon location, synonymous/non-synonymous substitutions), SNP frequency determination in user-defined groups, haplotype reconstruction and networking, linkage disequilibrium evaluation, and diversity analysis (Pi, Watterson’s Theta, Tajima’s D).

2) a database storing polymorphisms, genotyping data and sequences of grapevine produced by nationally-funded public projects. It allows one to retrieve SNPs using various filters (such as genomic position, missing data, polymorphism type, allele frequency), to compare SNP patterns between populations, and to export genotyping data or sequences in various formats.

(2)

PAG-XIX(C900) SNiPlay: A Web-Based Tool For Detection, Management And Analysis Of SNP. SNiPlay is available at: http://www.sniplay.cirad.fr/.

Return to the Intl-PAG home page.

For further assistance, e-mail help19@intl-pag.org

Références

Documents relatifs

We provide a short introduction to the laboratory work required and then describe the possible steps in data processing for the detection of plant viruses, including quality control

Using a self-progeny of Calcutta4 genotyped by GBS and large insert paired reads mapped on the reference genome, we characterized two large structural variations in the

Keywords: Monte-Carlo method, simulation of Brownian motion exit time, double porosity model, fractured porous media.. AMS Classification: 76S05

Thus, the genetic dis- tances generated a network (Fig.  3) that places Asian mouflons close to the center of the network near the Pramenka, Greek and fat-tailed sheep, but

Background: High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide

Genotyping-by-sequencing reveals the effects of riverscape, climate and interspecific introgression on the genetic diversity and local adaptation of the endangered Mexican golden

The objectives of the work presented here are (1) to use SNPs previously identified in maize to develop a first reliable and standardized large scale SNP genotyping array; (2)

• compare EnrichNet against classical over-representation analysis using benchmark datasets from the Broad Institute of MIT and Harvard (5 gene expression datasets and 2