Association Cluster Detector: a tool for heuristic detection of significance clusters in whole-genome scans

نویسندگان

  • Tomàs Marquès-Bonet
  • Oscar Lao
  • Robert Goertsches
  • Manuel Comabella
  • Xavier Montalban
  • Arcadi Navarro
چکیده

UNLABELLED Whole genome scans analyze large sets of genetic markers, mainly single nucleotide polymorphisms, over the entire genome in order to find variants and regions associated with complex traits so these can be further investigated. Analyzing the results of such scans becomes difficult due to multiple testing problems and to the genomic distributions of recombination, linkage disequilibrium and true associations, which generate an extremely complex network of dependences between markers. Here we present Association Cluster Detector (ACD), a simple tool aiming to ease the analysis of the results of whole genome scans. ACD facilitates correction for multiple tests using several standard procedures and implements a sliding-window heuristic method that helps in detecting potentially interesting candidate regions by exploiting the property of non-random distribution of significantly associated markers. AVAILABILITY The tool can be downloaded from http://www.upf.es/cexs/recerca/bioevo/softanddata.htm

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

ارائه یک الگو ترکیبی داده کاوی با استفاده از قواعد انجمنی و خوشه بندی برای تعیین استراتژی تخفیف دهی، مطالعه موردی شرکت پخش پگاه

Sales promotion is important issue in most of sales and distribution companies and finding the most appropriate strategy for this subject is marketers’ challenge. Discounting (offering) is one of sales promotion strategies. Using the fixed and constant discounting strategy for all customers and on all goods reduces chance for success. Discounting strategy needs a model for providing best ...

متن کامل

A FUZZY DIFFERENCE BASED EDGE DETECTOR

In this paper, a new algorithm for edge detection based on fuzzyconcept is suggested. The proposed approach defines dynamic membershipfunctions for different groups of pixels in a 3 by 3 neighborhood of the centralpixel. Then, fuzzy distance and -cut theory are applied to detect the edgemap by following a simple heuristic thresholding rule to produce a thin edgeimage. A large number of experime...

متن کامل

The Statistical Significance of Max-Gap Clusters

Identifying gene clusters, genomic regions that share local similarities in gene organization, is a prerequisite for many different types of genomic analyses, including operon prediction, reconstruction of chromosomal rearrangements, and detection of whole-genome duplications. A number of formal definitions of gene clusters have been proposed, as well as methods for finding such clusters and/or...

متن کامل

Graph Clustering by Hierarchical Singular Value Decomposition with Selectable Range for Number of Clusters Members

Graphs have so many applications in real world problems. When we deal with huge volume of data, analyzing data is difficult or sometimes impossible. In big data problems, clustering data is a useful tool for data analysis. Singular value decomposition(SVD) is one of the best algorithms for clustering graph but we do not have any choice to select the number of clusters and the number of members ...

متن کامل

Unveiling the genetic loci for a panicle developmental trait using genome-wide association study in rice

Panicle size has a high correlation with grain yield in rice. There is a bottleneck to identify the additional quantitative trait loci (QTL) for panicle size due to the conventional traits used for QTL mapping. To identify more genetic loci for panicle size, a panicle developmental trait (LNTB, the length from panicle neck-knot to the first primary branch in the rachis) related to panicle size ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Bioinformatics

دوره 21 Suppl 2  شماره 

صفحات  -

تاریخ انتشار 2005