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Highly penetrant cancer syndromes account for less than 5% of all cases with familial colorectal cancer (CRC), and other genetic contribution explains the majority of the genetic contribution to CRC. A CRC susceptibility locus on chromosome 9q has been suggested. In this study, families where risk of CRC was linked to the region, were used to search for predisposing mutations in all genes in the region. No disease-causing mutation was found. Next, haplotype association studies were performed in the region, comparing Swedish CRC cases (2664) and controls (4782). Two overlapping haplotypes were suggested. One 10-SNP haplotype was indicated in familial CRC (OR 1.4, p = 0.00005) and one 25-SNP haplotype was indicated in sporadic CRC (OR 2.2, p = 0.0000012). The allele frequencies of the 10-SNP and the 25-SNP haplotypes were 13.7% and 2.5% respectively and both included one RNA, RP11-332M4.1 and RP11-l80l4.2, in the non-overlapping regions. The sporadic 25-SNP haplotype could not be studied further, but the familial 10-SNP haplotype was analyzed in 61 additional CRC families, and 6 of them were informative for all markers and had the risk haplotype. Targeted sequencing of the 10-SNP region in the linked families identified one variant in RP11-332M4.1, suggestive to confer the increased CRC risk on this haplotype. Our results support the presence of two loci at 9q22.32, each with one RNA as the putative cause of increased CRC risk. These RNAs could exert their effect through the same, or different, genes/pathways, possibly through the regulation of neighboring genes, such as PTCH1, FANCC, DKFZP434H0512, ERCC6L2 or the processed transcript LINC00046.
Pubmed ID: 29541405
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Commercial vendor and service provider of laboratory reagents and antibodies. Supplier of scientific instrumentation, reagents and consumables, and software services.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023. An aggregated data platform for genome sequencing data created by a coalition of investigators seeking to aggregate and harmonize exome sequencing data from a variety of large-scale sequencing projects, and to make summary data available for the wider scientific community. The data set provided on this website spans 61,486 unrelated individuals sequenced as part of various disease-specific and population genetic studies. They have removed individuals affected by severe pediatric disease, so this data set should serve as a useful reference set of allele frequencies for severe disease studies. All of the raw data from these projects have been reprocessed through the same pipeline, and jointly variant-called to increase consistency across projects. They ask that you not publish global (genome-wide) analyses of these data until after the ExAC flagship paper has been published, estimated to be in early 2015. If you''re uncertain which category your analyses fall into, please email them. The aggregation and release of summary data from the exomes collected by the Exome Aggregation Consortium has been approved by the Partners IRB (protocol 2013P001477, Genomic approaches to gene discovery in rare neuromuscular diseases).
View all literature mentionsPortal to interactively visualize genomic data. Provides reference sequences and working draft assemblies for collection of genomes and access to ENCODE and Neanderthal projects. Includes collection of vertebrate and model organism assemblies and annotations, along with suite of tools for viewing, analyzing and downloading data.
View all literature mentionsJava toolset for working with next generation sequencing data in the BAM format.
View all literature mentionsOpen source whole genome association analysis toolset, designed to perform range of basic, large scale analyses in computationally efficient manner. Used for analysis of genotype/phenotype data. Through integration with gPLINK and Haploview, there is some support for subsequent visualization, annotation and storage of results. PLINK 1.9 is improved and second generation of the software.
View all literature mentionsSoftware package that creates genomic builds, calls SNPs, detects indels, and counts reads from data generated from one or more sequencing runs. In addition, CASAVA automatically generates a range of statistics, such as mean depth and percentage chromosome coverage, to enable comparison with previous builds or other samples. CASAVA analyzes sequencing reads in three stages: * FASTQ file generation and demultiplexing * Alignment to a reference genome * Variant detection and counting
View all literature mentionsA software package to analyze next-generation resequencing data. The toolkit offers a wide variety of tools, with a primary focus on variant discovery and genotyping as well as strong emphasis on data quality assurance. Its robust architecture, powerful processing engine and high-performance computing features make it capable of taking on projects of any size. This software library makes writing efficient analysis tools using next-generation sequencing data very easy, and second it's a suite of tools for working with human medical resequencing projects such as 1000 Genomes and The Cancer Genome Atlas. These tools include things like a depth of coverage analyzers, a quality score recalibrator, a SNP/indel caller and a local realigner. (entry from Genetic Analysis Software)
View all literature mentionsOriginal SAMTOOLS package has been split into three separate repositories including Samtools, BCFtools and HTSlib. Samtools for manipulating next generation sequencing data used for reading, writing, editing, indexing,viewing nucleotide alignments in SAM,BAM,CRAM format. BCFtools used for reading, writing BCF2,VCF, gVCF files and calling, filtering, summarising SNP and short indel sequence variants. HTSlib used for reading, writing high throughput sequencing data.
View all literature mentionsA dataset containing the full genomic sequence of 1,700 individuals, freely available for research use. The 1000 Genomes Project is an international research effort coordinated by a consortium of 75 companies and organizations to establish the most detailed catalogue of human genetic variation. The project has grown to 200 terabytes of genomic data including DNA sequenced from more than 1,700 individuals that researchers can now access on AWS for use in disease research free of charge. The dataset containing the full genomic sequence of 1,700 individuals is now available to all via Amazon S3. The data can be found at: http://s3.amazonaws.com/1000genomes The 1000 Genomes Project aims to include the genomes of more than 2,662 individuals from 26 populations around the world, and the NIH will continue to add the remaining genome samples to the data collection this year. Public Data Sets on AWS provide a centralized repository of public data hosted on Amazon Simple Storage Service (Amazon S3). The data can be seamlessly accessed from AWS services such Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Elastic MapReduce (Amazon EMR), which provide organizations with the highly scalable compute resources needed to take advantage of these large data collections. AWS is storing the public data sets at no charge to the community. Researchers pay only for the additional AWS resources they need for further processing or analysis of the data. All 200 TB of the latest 1000 Genomes Project data is available in a publicly available Amazon S3 bucket. You can access the data via simple HTTP requests, or take advantage of the AWS SDKs in languages such as Ruby, Java, Python, .NET and PHP. Researchers can use the Amazon EC2 utility computing service to dive into this data without the usual capital investment required to work with data at this scale. AWS also provides a number of orchestration and automation services to help teams make their research available to others to remix and reuse. Making the data available via a bucket in Amazon S3 also means that customers can crunch the information using Hadoop via Amazon Elastic MapReduce, and take advantage of the growing collection of tools for running bioinformatics job flows, such as CloudBurst and Crossbow.
View all literature mentionsMarkov chain Monte Carlo program for association in two-dimensional contingency tables, and for testing Hardy-Weinberg equilibrium. (entry from Genetic Analysis Software)
View all literature mentionsVisualize and analyze data generated by all of Illumina''s platforms.
View all literature mentionsFounded by Professor Ed Southern, Oxford Gene Technology (OGT) provides a range of high-quality genomics services, including next generation sequencing (whole exome, pre-designed panels, custom panels, RNA-Seq) and microarray processing (aCGH-CNV, miRNA, gene expression).
View all literature mentionsAn efficient software tool to utilize update-to-date information to functionally annotate genetic variants detected from diverse genomes (including human genome hg18, hg19, as well as mouse, worm, fly, yeast and many others). Given a list of variants with chromosome, start position, end position, reference nucleotide and observed nucleotides, ANNOVAR can perform: 1. gene-based annotation. 2. region-based annotation. 3. filter-based annotation. 4. other functionalities. (entry from Genetic Analysis Software)
View all literature mentionsNext generation sequencing and genotyping services provided to investigators working to discover genes that contribute to disease. On-site statistical geneticists provide insight into analysis issues as they relate to study design, data production and quality control. In addition, CIDR has a consulting agreement with the University of Washington Genetics Coordinating Center (GCC) to provide statistical and analytical support, most predominantly in the areas of GWAS data cleaning and methods development. Completed studies encompass over 175 phenotypes across 530 projects and 620,000 samples. The impact is evidenced by over 380 peer-reviewed papers published in 100 journals. Three pathways exist to access the CIDR genotyping facility: * NIH CIDR Program: The CIDR contract is funded by 14 NIH Institutes and provides genotyping and statistical genetic services to investigators approved for access through competitive peer review. An application is required for projects supported by the NIH CIDR Program. * The HTS Facility: The High Throughput Sequencing Facility, part of the Johns Hopkins Genetic Resources Core Facility, provides next generation sequencing services to internal JHU investigators and external scientists on a fee-for-service basis. * The JHU SNP Center: The SNP Center, part of the Johns Hopkins Genetic Resources Core Facility, provides genotyping to internal JHU investigators and external scientists on a fee-for-service basis. Data computation service is included to cover the statistical genetics services provided for investigators seeking to identify genes that contribute to human disease. Human Genotyping Services include SNP Genome Wide Association Studies, SNP Linkage Scans, Custom SNP Studies, Cancer Panel, MHC Panels, and Methylation Profiling. Mouse Genotyping Services include SNP Scans and Custom SNP Studies.
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