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An app for summarizing association analysis results of whole-genome/whole-exome sequencing (WGS/WES) studies in UK Biobank RAP

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staarpipelinesummary_indvar (DNAnexus Platform App)

This is the source code for the staarpipelinesummary_indvar app that runs on the DNAnexus Platform. For more information about how to run or modify it, see https://documentation.dnanexus.com.

Applet Usage

The staarpipelinesummary_indvar app can extract information (summary statistics) of individual variants from a user-specified variant set (gene category or genetic region), e.g. a genome-wide significant variant set detected from the staarpipeline app and summarized from the staarpipelinesummary_varset app, in the analytical follow-up of STAARpipeline.

Please see the user manual and tutorial for detailed usage of staarpipelinesummary_indvar app.

Cloning an Applet

To acquire the staarpipelinesummary_indvar applet, you will need to compile this applet for your respective DNANexus project, by cloning the repository from github and dx build an APPLET into your own workspace.

  1. Clone this github repo to some directory:
git clone https://github.com/li-lab-genetics/staarpipelinesummary_indvar-rap.git

This will create a folder named staarpipelinesummary_indvar-rap, you can then:

  1. Compile the source code:
dx build -f staarpipelinesummary_indvar-rap

the -f flag just tells DNANexus to overwrite older versions of the applet within the same project if it is already there.

You can then run the following to run this applet:

dx run staarpipelinesummary_indvar <options>

Citation

Zilin Li*, Xihao Li*, Hufeng Zhou, Sheila M. Gaynor, Margaret Sunitha Selvaraj, Theodore Arapoglou, Corbin Quick, Yaowu Liu, Han Chen, Ryan Sun, Rounak Dey, Donna K. Arnett, Paul L. Auer, Lawrence F. Bielak, Joshua C. Bis, Thomas W. Blackwell, John Blangero, Eric Boerwinkle, Donald W. Bowden, Jennifer A. Brody, Brian E. Cade, Matthew P. Conomos, Adolfo Correa, L. Adrienne Cupples, Joanne E. Curran, Paul S. de Vries, Ravindranath Duggirala, Nora Franceschini, Barry I. Freedman, Harald H. H. Göring, Xiuqing Guo, Rita R. Kalyani, Charles Kooperberg, Brian G. Kral, Leslie A. Lange, Bridget M. Lin, Ani Manichaikul, Alisa K. Manning, Lisa W. Martin, Rasika A. Mathias, James B. Meigs, Braxton D. Mitchell, May E. Montasser, Alanna C. Morrison, Take Naseri, Jeffrey R. O’Connell, Nicholette D. Palmer, Patricia A. Peyser, Bruce M. Psaty, Laura M. Raffield, Susan Redline, Alexander P. Reiner, Muagututi’a Sefuiva Reupena, Kenneth M. Rice, Stephen S. Rich, Jennifer A. Smith, Kent D. Taylor, Margaret A. Taub, Ramachandran S. Vasan, Daniel E. Weeks, James G. Wilson, Lisa R. Yanek, Wei Zhao, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Lipids Working Group, Jerome I. Rotter, Cristen J. Willer, Pradeep Natarajan, Gina M. Peloso, & Xihong Lin. (2023). A framework for detecting noncoding rare variant associations of large-scale whole-genome sequencing studies. Nature Methods, 19(12), 1599-1611. PMID: 36303018. PMCID: PMC10008172. DOI: 10.1038/s41592-022-01640-x.

Xihao Li*, Zilin Li*, Hufeng Zhou, Sheila M. Gaynor, Yaowu Liu, Han Chen, Ryan Sun, Rounak Dey, Donna K. Arnett, Stella Aslibekyan, Christie M. Ballantyne, Lawrence F. Bielak, John Blangero, Eric Boerwinkle, Donald W. Bowden, Jai G. Broome, Matthew P. Conomos, Adolfo Correa, L. Adrienne Cupples, Joanne E. Curran, Barry I. Freedman, Xiuqing Guo, George Hindy, Marguerite R. Irvin, Sharon L. R. Kardia, Sekar Kathiresan, Alyna T. Khan, Charles L. Kooperberg, Cathy C. Laurie, X. Shirley Liu, Michael C. Mahaney, Ani W. Manichaikul, Lisa W. Martin, Rasika A. Mathias, Stephen T. McGarvey, Braxton D. Mitchell, May E. Montasser, Jill E. Moore, Alanna C. Morrison, Jeffrey R. O'Connell, Nicholette D. Palmer, Akhil Pampana, Juan M. Peralta, Patricia A. Peyser, Bruce M. Psaty, Susan Redline, Kenneth M. Rice, Stephen S. Rich, Jennifer A. Smith, Hemant K. Tiwari, Michael Y. Tsai, Ramachandran S. Vasan, Fei Fei Wang, Daniel E. Weeks, Zhiping Weng, James G. Wilson, Lisa R. Yanek, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Lipids Working Group, Benjamin M. Neale, Shamil R. Sunyaev, Gonçalo R. Abecasis, Jerome I. Rotter, Cristen J. Willer, Gina M. Peloso, Pradeep Natarajan, & Xihong Lin. (2020). Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale. Nature Genetics, 52(9), 969-983. PMID: 32839606. PMCID: PMC7483769. DOI: 10.1038/s41588-020-0676-4.

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An app for summarizing association analysis results of whole-genome/whole-exome sequencing (WGS/WES) studies in UK Biobank RAP

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