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Part 1: Document Description
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Citation |
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Title: |
Phylogenetic Tree-based Pipeline for Uncovering Mutational Patterns during Influenza Virus Evolution |
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Identification Number: |
doi:10.21979/N9/PDYCUD |
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Distributor: |
DR-NTU (Data) |
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Date of Distribution: |
2019-04-26 |
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Version: |
2 |
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Bibliographic Citation: |
Ivan, Fransiskus Xaverius; Deshpande, Akhila; Lim, Chun Wei; Kwoh, Chee Keong, 2019, "Phylogenetic Tree-based Pipeline for Uncovering Mutational Patterns during Influenza Virus Evolution", https://doi.org/10.21979/N9/PDYCUD, DR-NTU (Data), V2 |
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Citation |
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Title: |
Phylogenetic Tree-based Pipeline for Uncovering Mutational Patterns during Influenza Virus Evolution |
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Identification Number: |
doi:10.21979/N9/PDYCUD |
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Authoring Entity: |
Ivan, Fransiskus Xaverius (Nanyang Technological University) |
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Deshpande, Akhila (Nanyang Technological University) |
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Lim, Chun Wei (Nanyang Technological University) |
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Kwoh, Chee Keong (Nanyang Technological University) |
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Software used in Production: |
Python |
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Grant Number: |
AcRF Tier 2 grant MOE2014-T2-2-023 |
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Distributor: |
DR-NTU (Data) |
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Access Authority: |
Ivan, Fransiskus Xaverius |
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Depositor: |
Ivan, Fransiskus Xaverius |
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Date of Deposit: |
2019-04-25 |
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Holdings Information: |
https://doi.org/10.21979/N9/PDYCUD |
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Study Scope |
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Keywords: |
"Medicine, Health and Life Sciences", Influenza evolution, mutational patterns |
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Abstract: |
Various computational and statistical approaches have been proposed to uncover the mutational patterns of rapidly evolving influenza viral genes. A problem that draws much attention is to identify pairs of sites that potentially co-mutate to contribute to the overall fitness of the virus. Unlike previous methods that extract the mutations from sequence alignments, here we endeavor a novel method that relies on identifying mutations in the phylogenetic trees that are reconstructed using resampled sequence data. Since the method takes into account the evolutionary structure presents in the sequence data, spurious mutations obtained by comparing sequences from different clades could be removed. |
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Kind of Data: |
Python/R codes (.py and .ipynb files), compressed data, and documentations for the codes, input/output data and methods |
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Notes: |
This is an extension of the works for the ACM-BCB 2017 conference paper: Ivan FX, et al. (2017). Phylogenetic Tree based Method for Uncovering Co-mutational Site-pairs in Influenza Viruses. Proceeding of the 8th ACM Internation Conference on Bioinformatics, Computational Biology, and Health Informatics. pp. 21-26. Boston, Massachusetts, USA. August 20-23, 2017. |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Other Study Description Materials |
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Related Publications |
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Citation |
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Identification Number: |
10.1101/708420 |
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Bibliographic Citation: |
Ivan FX, et al. (2019). Phylogenetic Tree-based Pipeline for Uncovering Mutational Patterns during Influenza Virus Evolution. bioRxiv. July 19, 2019. doi: 10.1101/708420. |
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Citation |
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Identification Number: |
10.1145/3107411.3107479 |
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Bibliographic Citation: |
Ivan FX, et al. (2017). Phylogenetic Tree based Method for Uncovering Co-mutational Site-pairs in Influenza Viruses. Proceeding of the 8th ACM Internation Conference on Bioinformatics, Computational Biology, and Health Informatics. pp. 21-26. Boston, Massachusetts, USA. August 20-23, 2017. |
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Label: |
codes.tar.gz |
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Text: |
Codes for executing the analysis pipeline. |
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Notes: |
application/x-gzip |
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Label: |
Documentation - Codes (Tool) for Uncovering Mutational Patterns of Influenza Virus Evolution.pdf |
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Text: |
Documentation of the codes (tool), which describe the input and output of the codes, environment for running the codes, and the steps for running the codes or analysis pipeline. |
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Notes: |
application/pdf |
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Label: |
indata.tar.gz |
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Text: |
Examples of metadata and sequence data (contain records obtained from the NCBI Influenza Virus Resource) for analysis pipeline. |
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Notes: |
application/x-gzip |
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Label: |
Methods.pdf |
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Text: |
Description of methods for the analysis pipeline. |
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Notes: |
application/pdf |