sherlock.ucsf.edu

Sherlock

Discover disease genes in GWAS using eQTL signature matching. What's hidden in your GWAS? Over the past decade, genome-wide association studies (GWAS) have identified numerous loci for a range of complex diseases. Often these genomic locations fall within non-coding regions that have limited annotation and no obvious functional consequence. Additionally, most loci account for only a small fraction of disease heritability, with the vast majority of published SNPs having odds ratios under two. Trans-. ...

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Discover disease genes in GWAS using eQTL signature matching. What's hidden in your GWAS? Over the past decade, genome-wide association studies (GWAS) have identified numerous loci for a range of complex diseases. Often these genomic locations fall within non-coding regions that have limited annotation and no obvious functional consequence. Additionally, most loci account for only a small fraction of disease heritability, with the vast majority of published SNPs having odds ratios under two. Trans-. ...

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Sherlock | sherlock.ucsf.edu Reviews

https://sherlock.ucsf.edu

Discover disease genes in GWAS using eQTL signature matching. What's hidden in your GWAS? Over the past decade, genome-wide association studies (GWAS) have identified numerous loci for a range of complex diseases. Often these genomic locations fall within non-coding regions that have limited annotation and no obvious functional consequence. Additionally, most loci account for only a small fraction of disease heritability, with the vast majority of published SNPs having odds ratios under two. Trans-. ...

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sherlock.ucsf.edu

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Sherlock

http://sherlock.ucsf.edu/links.html

Discover disease genes in GWAS using eQTL signature matching. We welcome your feedback regarding Sherlock. In certain cases, we may be able to tailor the analysis and/or available data sets for your particular needs. Also, we are eager to hear from groups willing to make their molecular data available to the wider research community. Please do not hesitate to contact us:. University of California, San Francisco. 1700 4th Street, Box 2542. San Francisco, CA, 94158. Xin He: xinhe2@gmail.com.

2

Sherlock

http://sherlock.ucsf.edu/publications.html

Discover disease genes in GWAS using eQTL signature matching. Sherlock: detecting gene-disease associations by matching patterns of expression QTL and GWAS. Xin He, Chris K Fuller, Yi Song, Qingying Meng, Bin Zhang, Xia Yang, Hao Li. American Journal of Human Genetics. Data Sets Currently Available in sherlock. Genetic Architecture of Transcript-Level Variation in Humans. Duan S, Huang RS, Zhang W, Bleibel WK, Roe CA, Clark TA, Chen TX, Schweitzer AC, Blume JE, Cox NJ, Dolan ME. Am J Hum Genet.

3

Sherlock

http://sherlock.ucsf.edu/submit.html

Discover disease genes in GWAS using eQTL signature matching. 1 Upload Your GWAS Associations File. Use tab-delimited text with one SNP and one p-value per row ( sample input file. Make sure to include all. GWAS associations, not just the top hits. Even large p-values, when aggregated, can prove very useful in Sherlock. If your study involves a quantitative trait. 2 Select Relevant Expression Data Sets. Affect the analysis of others. Public eQTL Data Sets:. GTEx Adipose Visceral Omentum. Brain Frontal Co...

4

Sherlock

http://sherlock.ucsf.edu/genes.html

Discover disease genes in GWAS using eQTL signature matching. Sample Results for Several Diseases. Here we provide an overview of Sherlock results for several diseases. The tables below list the gene implicated, its LBF, its p-value, whether or not the gene was already implicated in the disease through GWAS (i.e. through significant loci proximal to the gene), and the p-value obtained using our method and a replicate GWAS (when available). At The University of California, San Francisco.

5

Sherlock

http://sherlock.ucsf.edu/index.html

Discover disease genes in GWAS using eQTL signature matching. What's hidden in your GWAS? Over the past decade, genome-wide association studies (GWAS) have identified numerous loci for a range of complex diseases. Often these genomic locations fall within non-coding regions that have limited annotation and no obvious functional consequence. Additionally, most loci account for only a small fraction of disease heritability, with the vast majority of published SNPs having odds ratios under two. Trans-. ...

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genome.ucsf.edu

Li Lab Software

http://genome.ucsf.edu/tools.html

Computational Biology Tools Developed by the Li Lab. Building dictionaries for genomes based on probabilistic segmentation. Regulatory element detection using genome-wide gene expression data. To replace the CAGE. Comparative Analysis of Gene Expression profiles across organisms). Degenerate regulatory motifs detection by correlation of sequence with expression data. New tools available from 2013. Discover disease genes in GWAS using eQTL signature matching.

mobydick.ucsf.edu

Li Lab Software

http://mobydick.ucsf.edu/tools.html

Computational Biology Tools Developed by the Li Lab. Building dictionaries for genomes based on probabilistic segmentation. Regulatory element detection using genome-wide gene expression data. To replace the CAGE. Comparative Analysis of Gene Expression profiles across organisms). Degenerate regulatory motifs detection by correlation of sequence with expression data. New tools available from 2013. Discover disease genes in GWAS using eQTL signature matching.

varigenome.blogspot.com

Variable Genome: June 2013

http://varigenome.blogspot.com/2013_06_01_archive.html

Friday, June 21, 2013. FTO and memory - connecting the dots. Is a well known gene containing variants that have shown rather consistent association to obesity risk and BMI in many different populations. FTO is an efficient oxidative demethylase. Targeting the abundant N6-methyladenosine (m6A) residues in RNA in vitro. And mRNA in the nucleus. This implies that there is a heretofore undescribed, reversible regulatory process in mammalian cells. Late last year, it was reported. Meyer, et al. 2012. A main i...

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Discover disease genes in GWAS using eQTL signature matching. What's hidden in your GWAS? Over the past decade, genome-wide association studies (GWAS) have identified numerous loci for a range of complex diseases. Often these genomic locations fall within non-coding regions that have limited annotation and no obvious functional consequence. Additionally, most loci account for only a small fraction of disease heritability, with the vast majority of published SNPs having odds ratios under two. Trans-. ...

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