Building Highly-Optimized, Low-Latency Pipelines for Genomic Data Analysis
Summary: Combines a genomics-aware analysis pipeline, parallel execution engine, and principled pipeline optimizations to cut end-to-end latency of long-running NGS workflows. Evaluated on NYGC production pipelines, showing initial speedups that shorten development cycles and enable faster clinical turnaround. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Yanlei Diao
- 2. Abhishek Roy
- 3. Toby Bloom
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Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3 | Pig Latin: A Not-So-Foreign Language for Data Processing | 2008 | SIGMOD | 0.0024183614 |
| 42 | A Comparison of Approaches to Large-Scale Data Analysis | 2009 | SIGMOD | 0.00073498298 |
| 599 | Mining Quantitative Association Rules in Large Relational Tables | 1996 | SIGMOD | 0.00019394214 |
| 913 | Tenzing A SQL Implementation On The MapReduce Framework | 2011 | VLDB | 0.00015408131 |
| 1,944 | WHAM: A High-throughput Sequence Alignment Method | 2011 | SIGMOD | 0.00010004608 |
| 2,439 | CoHadoop: Flexible Data Placement and Its Exploitation in Hadoop | 2011 | VLDB | 8.8190594e-05 |
| 2,476 | A Platform for Scalable One-Pass Analytics using MapReduce | 2011 | SIGMOD | 8.6960139e-05 |
| 12,139 | Massive Genomic Data Processing and Deep Analysis | 2012 | VLDB | 4.1945683e-05 |
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