데이터셋 상세
미국
A rapid method to map mutations in
Background Genetic screens in Drosophila have provided a wealth of information about a variety of cellular and developmental processes. It is now possible to screen for mutant phenotypes in virtually any cell at any stage of development by performing clonal screens using the flp/FRT system. The rate-limiting step in the analysis of these mutants is often the identification of the mutated gene, however, because traditional mapping strategies rely mainly on genetic and cytological markers that are not easily linked to the molecular map. Results Here we describe the development of a single-nucleotide polymorphism (SNP) map for chromosome arm 3R. The map contains 73 polymorphisms between the standard FRT chromosome, and a mapping chromosome that carries several visible markers (rucuca), at an average density of one SNP per 370 kilobases (kb). Using this collection, we show that mutants can be mapped to a 400 kb interval in a single meiotic mapping cross, with only a few hundred SNP detection reactions. Discovery of further SNPs in the region of interest allows the mutation to be mapped with the same recombinants to a region of about 50 kb. Conclusion The combined use of standard visible markers and molecular polymorphisms in a single mapping strategy greatly reduces both the time and cost of mapping mutations, because it requires at least four times fewer SNP detection reactions than a standard approach. The use of this map, or others developed along the same lines, will greatly facilitate the identification of the molecular lesions in mutants from clonal screens.
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NIST Cell Image Database - SRD 165
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This database provides reference data on controlled cell image experiments. The database contains cell images of A-10 rat smooth muscle and NIH-3T3 mouse fibroblasts. A novel rule and root based method is used to create experimental metadata as described in About Us page.
NIST Cell Image Database - SRD 165
공공데이터포털
This database provides reference data on controlled cell image experiments. The database contains cell images of A-10 rat smooth muscle and NIH-3T3 mouse fibroblasts. A novel rule and root based method is used to create experimental metadata as described in About Us page.
VecScreen
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Quickly identifying segments of a nucleic acid sequence that may be of vector origin.
Evaluation of DNA yield from various sources for use in single nucleotide polymorphism panels
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Genetics studies are used by wildlife managers and researchers to gain inference into a population of a species of interest. To gain these insights, micro-satellites have been the primary method, however, there currently is a shift from micro-satellites to single nucleotide polymorphisms (SNPs). With the DNA requirements being different, an investigation into which samples can provide adequate DNA yield is warranted. Using samples that were collected from previous genetic projects from regions in the USA from 2014 to 2021, we investigated the DNA yield of eight sample categories to gain insights into which provided adequate DNA to be used in various panels. We found four sample categories that met the DNA requirements for use in all three panels, three sample categories that only met the DNA requirements for two panels, and one sample category that did not meet any of the three panels requirements. Additionally, we used linear random-effects models to determine which covariates would have the greatest influence on DNA yield. We determined that all covariates, tissue type, storage method, preservative, DNA quality, time until DNA extraction and time after DNA extraction could influence DNA yield.
Phenotype-Genotype Integrator (PheGenI)
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Supports finding human phenotype/genotype relationships with queries by phenotype, chromosome location, gene, and SNP identifiers. Currently includes information from dbGaP, the National Human Genome Research Institute (NHGRI) genome-wide association study (GWAS) Catalog, and Genotype - Tissue Expression (GTeX).
Sequencing Data Set of Sediment Layers
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A table (DP_SRA.xlsx) contains rows as sample and columns as entries representing the biosample accession number (NCBI), collection (date), library strategy, target (source), and sequencing (technology) for each individual sample. The zip file (Genome_Set01.zip) contain nine (9) fasta file (DP_bin_02.fasta, DP_bin_04.fasta, DP_bin_09.fasta, DP_bin_10.fasta, DP_bin_14.fasta, DP_bin_15.fasta, DP_bin_16a.fasta, DP_bin_20.fasta, DP_bin_23.fasta) with the contig sequences (i.e. binning) for each metagenome-assembled genomes (MAGs). These data are available from the NCBI Sequence Read Archive (SRA) under the BioProject (https://www.ncbi.nlm.nih.gov/bioproject) with accession number PRJNA646252 and the following BioSample numbers: SAMN15536103 to SAMN15536108. This dataset is associated with the following publication: Gomez-Alvarez, V., H. Liu, J. Pressman, and D. Wahman. Metagenomic Profile of Microbial Communities in a Drinking Water Storage Tank Sediment after Sequential Exposure to Monochloramine, Free Chlorine, and Monochloramine. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 1(5): 1283-1294, (2021).
Sequence Read Archive (SRA)
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The Sequence Read Archive (SRA) stores sequencing data from the next generation of sequencing platforms including Roche 454 GS System®, Illumina Genome Analyzer®, Life Technologies AB SOLiD System®, Helicos Biosciences Heliscope®, Complete Genomics®, and Pacific Biosciences SMRT®.
Database of Short Genetic Variations (dbSNP)
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Database of Short Genetic Variations (dbSNP) contains human single nucleotide variations, microsatellites, and small-scale insertions and deletions along with publication, population frequency, molecular consequence, and genomic and RefSeq mapping information for both common variations and clinical mutations.
Splign
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Compute cDNA-to-Genomic sequence alignments.