 Unbiased Metagenomic Sequencing for Pediatric Meningitis in Bangladesh Reveals Neuroinvasive Chikungunya Virus Outbreak and Other Unrealized Pathogens American Society of Microbiology, 2019
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 Exploratory proteomic analysis implicates thealternative complement cascade in primary CNSvasculitis Neurology, 2019
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 Kelch-like Protein 11 Seminoma-associated Paraneoplastic Encephalitis NEJM 2019
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 Pulmonary Metagenomic Sequencing Suggests Missed Infections in Immunocompromised Children Oxford Academic, 2019
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 Towards precision quantification of contamination in metagenomic sequencing experiments Microbiome, 2019
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 Metagenomic comparison of tracheal aspirate and mini-bronchial alveolar lavage for assessment of respiratory microbiota American Journal of Physiology, 2019
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 Miniaturization and optimization of 384-well compatible RNA sequencing library preparation PLOS One, 2019
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|  Here we introduce HMMSplicer, an accurate and efficient algorithm for discovering canonical and non-canonical splice junctions in short read datasets. HMMSplicer identifies more splice junctions than currently available algorithms when tested on publicly available A. thaliana, P. falciparum, and H. sapiens datasets without a reduction in specificity. HMMSplicer was found to perform especially well in compact genomes and on genes with low expression levels, alternative splice isoforms, or non-canonical splice junctions. Because HHMSplicer does not rely on pre-built gene models, the products of inexact splicing are also detected. In addition, HMMSplicer provides a score for every predicted junction allowing the user to set a threshold to tune false positive rates depending on the needs of the experiment. HMMSplicer is implemented in Python. Code and documentation are freely available at the link below. Download HMMSplicer! (Updated Nov 25th 2010 - Version: 0.9.5) |
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