TY - DATA T1 - SARS-CoV-2 variant quantification using kallisto code PY - 2022/01/26 AU - Matei Anton UR - https://data.4tu.nl/articles/software/SARS-CoV-2_variant_quantification_using_kallisto_code/18532973/1 DO - 10.4121/18532973.v1 KW - kallisto KW - Covid-19 KW - SARS-CoV-2 KW - Wastewater monitoring N2 - Code used together with its results for the paper as part of my Bachelor's Thesis project. The research consists of optimizing the kallisto algorithm for predicting the abundances of SARS-CoV-2 variants in wastewater samples. Specifically, I look at how only sequencing certain regions of the genome influences the prediction accuracy of this pipeline.
ER -