genocanyon.med.yale.edu

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GenoCanyon is a whole-genome functional annotation approach based on unsupervised statistical learning. It integrates genomic conservation measures and biochemical annotation data to predict the functional potential at each nucleotide. More details about the method can be found in our PAPER. We pre-calculated the prediction scores for the entire human genome (hg19). Prediction scores and all 22 annotations are available for download on the DOWNLOADS. We recently developed GenoWAP. Paper is now online.

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GenoCanyon Home | genocanyon.med.yale.edu Reviews

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GenoCanyon is a whole-genome functional annotation approach based on unsupervised statistical learning. It integrates genomic conservation measures and biochemical annotation data to predict the functional potential at each nucleotide. More details about the method can be found in our PAPER. We pre-calculated the prediction scores for the entire human genome (hg19). Prediction scores and all 22 annotations are available for download on the DOWNLOADS. We recently developed GenoWAP. Paper is now online.

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GenoCanyon Home | genocanyon.med.yale.edu Reviews

https://genocanyon.med.yale.edu

GenoCanyon is a whole-genome functional annotation approach based on unsupervised statistical learning. It integrates genomic conservation measures and biochemical annotation data to predict the functional potential at each nucleotide. More details about the method can be found in our PAPER. We pre-calculated the prediction scores for the entire human genome (hg19). Prediction scores and all 22 annotations are available for download on the DOWNLOADS. We recently developed GenoWAP. Paper is now online.

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genocanyon.med.yale.edu

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GenoCanyon Prediction

http://genocanyon.med.yale.edu/GenoCanyon_Prediction.html

To use the GenoCanyon WebApp. The user interface of GenoCanyon WebApp. For regions larger than 3M bp, we suggest you to download the data and analyze them on your local device. Lu, Q et al. (2015). A Statistical Framework to Predict Functional Non-Coding Regions in the Human Genome Through Integrated Analysis of Annotation Data. Sci. Rep.

2

GenoCanyon AboutUs

http://genocanyon.med.yale.edu/GenoCanyon_AboutUs.html

Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA. Yale Center for Medical Informatics, Yale School of Medicine, New Haven, CT, USA. Lu, Q et al. (2015). A Statistical Framework to Predict Functional Non-Coding Regions in the Human Genome Through Integrated Analysis of Annotation Data. Sci. Rep.

3

GenoCanyon FAQ

http://genocanyon.med.yale.edu/GenoCanyon_FAQ.html

Why don't my prediction results show properly in the GenoCanyon Web Application? There are several possible reasons. Did you select a region larger than 3 million bp? Does your highlighted sub-region reside in the large region? Is your stop coordinate smaller than the start coordinate? If your answer is YES to any of these questions, it might have caused the display error. Why is there a limit of 3M bp in the web application? Why does the WebApp freeze after I click the submit button?

4

GenoCanyon Home

http://genocanyon.med.yale.edu/index.html

GenoCanyon is a whole-genome functional annotation approach based on unsupervised statistical learning. It integrates genomic conservation measures and biochemical annotation data to predict the functional potential at each nucleotide. More details about the method can be found in our PAPER. We pre-calculated the prediction scores for the entire human genome (hg19). Prediction scores and all 22 annotations are available for download on the DOWNLOADS. We recently developed GenoWAP. Paper is now online.

5

GenoWAP

http://genocanyon.med.yale.edu/GenoWAP

Lu Q, Yao X, Hu Y, and Zhao H. (2016). GenoWAP: GWAS signal prioritization through integrated analysis of genomic functional annotation. Lu Q*, Powles R.*, Wang Q., He B., and Zhao H. (2016). Integrative tissue-specific functional annotations in the human genome provide novel insights on many complex traits and improve signal prioritization in genome wide association studies. 12(4): e1005947. (* Equal Contribution). Please read our paper for more details. Global performance in studies of Crohn’s disease.

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genocanyon.med.yale.edu

GenoCanyon Home

GenoCanyon is a whole-genome functional annotation approach based on unsupervised statistical learning. It integrates genomic conservation measures and biochemical annotation data to predict the functional potential at each nucleotide. More details about the method can be found in our PAPER. We pre-calculated the prediction scores for the entire human genome (hg19). Prediction scores and all 22 annotations are available for download on the DOWNLOADS. We recently developed GenoWAP. Paper is now online.

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