 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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 Integrating host response and unbiased microbe detection for lower respiratory tract infection diagnosis in critically ill adults PNAS, 2018
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 Clinicopathology conference: 41‐year‐old woman with chronic relapsing meningitis Annuls of Neurology, 2018
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 The Plasmodium falciparum cytoplasmic translation apparatus: a promising therapeutic target not yet exploited by clinically approved anti-malarials Malaria Journal, 2018
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 Ebola virus, but not Marburg virus, replicates efficiently and without required adaptation in snake cells Virus Evolution, 2018
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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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