One of the interesting talks at this year’s AGBT (AGBT 2014) was from Joe DeRisi, a microarray technology pioneer and a professor at UCSF. DeRisi’s talk covered a feel good success story on how Next-Gen Sequencing was useful in finding the cause of a 14 year old boy suffering from acute encephalitis. The boy suffered from the disease for months and later on Joe DeRisi roped in to help identifying the cause by UCSF Prof. Charles Chiu. Charles Chiu’s team with Joe DeRisi’s help took just two days to identify the cause by sequencing and treated the kid with the dose of Pencillin to cure him.
The diagnostic science and the computational methodology behind the incredible story of NGS in critical care is published as two papers. The first paper is published in The New England Journal of Medicine describes the diagnosis by next-gen sequencing story.
- Actionable Diagnosis of Neuroleptospirosis by Next-Generation Sequencing, by Wilson MR, Naccache SN, Samayoa E, Biagtan M, Bashir H, Yu G, Salamat SM, Somasekar S, Federman S, Miller S, Sokolic R, Garabedian E, Candotti F, Buckley RH, Reed KD, Meyer TL, Seroogy CM, Galloway R, Henderson SL, Gern JE, DeRisi JL, Chiu CY.
The researchers made the computational pipeline used to diagnose encephalis available as a more general tool for fast and unbiased diagnostic tool for otherinfectious diseases. And the computational pipeline using opern-source tools is published in the second paper at Genome Research.
- A cloud-compatible bioinformatics pipeline for ultrarapid pathogen identification from next-generation sequencing of clinical samples, S. N. Naccache, S. Federman, N. Veeeraraghavan, M. Zaharia,D. Lee, E. Samayoa, J. Bouquet, A. L. Greninger, K. Luk, B. Enge,D. A. Wadford, S. L. Messenger, G. L. Genrich, K. Pellegrino, G. Grard, E. Leroy, B. S. Schneider, J. N. Fair, M. A. Martínez, P. Isa, J.A. Crump, J. L. DeRisi,T. Sittler, J. Hackett Jr., S.Miller and C.Y. Chiu
The paper presents SURPI: Sequence-based Ultrarapid Pathogen Identification, a computational pipeline for identifying pathogen from metagenomic NGS data from clinical samples. SURPI uses the aligners SNAP and RAPSearch (for protein) after benchmarking against a variety of aligners; testing for speed and accuracy. SNAP and RAPSearch were as accurate as other aligners but orders of magnitude faster. SURPI can run in two modes: fast mode and comprhensive mode. In fast mode, SURPI detects viruses and bacteria in data sets with 7–500 million reads in 11 min to 5 h. In the comprehensive mode, SURPI can identify all known microorganisms are identified, perform denovo assembly and protein homology searches in 50 min to 16 h. They showed the utility of the pipeline by testing it in 237 clinical samples containing over a billion reads.
Carl Zimmer has nice a article covering this NGS feel good story on NY Times,
You might also be interested on the story by Keith Robinson on his blog Omics Omics, immediately after AGBT 2014 (long before the publications)