This is the source code for the staarpipelinesummary_varset app that runs on the DNAnexus Platform. For more information about how to run or modify it, see https://documentation.dnanexus.com.
The staarpipelinesummary_varset app can summarize the single variant or aggregate test results generated from the staarpipeline app, and will
-
summarize these results across all chromosomes and create a unified list of results;
-
perform conditional analysis for (unconditionally) significant single variants or variant sets by adjusting for a given list of known variants.
Please see the user manual and tutorial for detailed usage of staarpipelinesummary_varset app.
To acquire the staarpipelinesummary_varset 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.
- Clone this github repo to some directory:
git clone https://github.com/li-lab-genetics/staarpipelinesummary_varset-rap.git
This will create a folder named staarpipelinesummary_varset-rap, you can then:
- Compile the source code:
dx build -f staarpipelinesummary_varset-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_varset <options>
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.