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International collaboration producing an extensive public catalog of human genetic variation, including SNPs and structural variants, and their haplotype contexts, in an effort to provide a foundation for investigating the relationship between genotype and phenotype. The genomes of about 2500 unidentified people from about 25 populations around the world were sequenced using next-generation sequencing technologies. Redundant sequencing on various platforms and by different groups of scientists of the same samples can be compared. The results of the study are freely and publicly accessible to researchers worldwide. The consortium identified the following populations whose DNA will be sequenced: Yoruba in Ibadan, Nigeria; Japanese in Tokyo; Chinese in Beijing; Utah residents with ancestry from northern and western Europe; Luhya in Webuye, Kenya; Maasai in Kinyawa, Kenya; Toscani in Italy; Gujarati Indians in Houston; Chinese in metropolitan Denver; people of Mexican ancestry in Los Angeles; and people of African ancestry in the southwestern United States. The goal Project is to find most genetic variants that have frequencies of at least 1% in the populations studied. Sequencing is still too expensive to deeply sequence the many samples being studied for this project. However, any particular region of the genome generally contains a limited number of haplotypes. Data can be combined across many samples to allow efficient detection of most of the variants in a region. The Project currently plans to sequence each sample to about 4X coverage; at this depth sequencing cannot provide the complete genotype of each sample, but should allow the detection of most variants with frequencies as low as 1%. Combining the data from 2500 samples should allow highly accurate estimation (imputation) of the variants and genotypes for each sample that were not seen directly by the light sequencing. All samples from the 1000 genomes are available as lymphoblastoid cell lines (LCLs) and LCL derived DNA from the Coriell Cell Repository as part of the NHGRI Catalog. The sequence and alignment data generated by the 1000genomes project is made available as quickly as possible via their mirrored ftp sites. ftp://ftp.1000genomes.ebi.ac.uk ftp://ftp-trace.ncbi.nlm.nih.gov/1000genomes
Proper citation: 1000 Genomes: A Deep Catalog of Human Genetic Variation (RRID:SCR_006828) Copy
http://code.google.com/p/mosaik-aligner/
A reference-guided assembler comprising of two main modular programs: MosaikBuild and MosaikAligner. MosaikBuild converts various sequence formats into Mosaik?s native read format. MosaikAligner pairwise aligns each read to a specified series of reference sequences and produces BAMs as outputs. At this time, the workflow consists of supplying sequences in FASTA, FASTQ, Illumina Bustard & Gerald, or SRF file formats and producing results in the BAM format. Unlike many current read aligners, MOSAIK produces gapped alignments using the Smith-Waterman algorithm. MOSAIK is written in highly portable C++ and currently targetted for the following platforms: Microsoft Windows, Apple Mac OS X, FreeBSD, and Linux operating systems. Other platforms can easily be supported upon request. MOSAIK is multithreaded. If you have a machine with 8 processors, you can use all 8 processors to align reads faster while using the same memory footprint as when using one processor. MOSAIK supports multiple sequencing technologies. In addition to legacy technologies such as Sanger capillary sequencing, our program supports next generation technologies such as Roche 454, Illumina, AB SOLiD, and experimental support for the Helicos Heliscope.
Proper citation: MOSAIK (RRID:SCR_005486) Copy
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
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