PT  - JOURNAL ARTICLE
AU  - Alex V. Kotlar
AU  - Cristina E. Trevino
AU  - Michael E. Zwick
AU  - David J. Cutler
AU  - Thomas S. Wingo
TI  - SeqAnt 2.0: Whole-Genome Annotation and Natural-Language Searching in the Cloud
AID  - 10.1101/146514
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 146514
4099  - http://biorxiv.org/content/early/2017/06/06/146514.short
4100  - http://biorxiv.org/content/early/2017/06/06/146514.full
AB  - Describing, prioritizing, and selecting alleles from large sequencing experiments remains technically challenging. SeqAnt 2.0 (https://seqant.emory.edu/) is the first web application that make these tasks accessible to non-programmers, even for large data sets consisting of thousands of whole-genome samples. It comprehensively describes alleles using public data (e.g., RefSeq, dbSNP, Clinvar, and others), and introduces a natural-language search engine that can locate the alleles of interest in a user’s experiment in milliseconds.