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  1. KEEP
  2. Theses and Dissertations
  3. Barrett, The Honors College Thesis/Creative Project Collection
  4. ConstrictR and ConstrictPy: R Package and Python Tool for Microbiome Analysis
  5. Full metadata

ConstrictR and ConstrictPy: R Package and Python Tool for Microbiome Analysis

Full metadata

Title
ConstrictR and ConstrictPy: R Package and Python Tool for Microbiome Analysis
Description
I, Christopher Negrich, am the sole author of this paper, but the tools described were designed in collaboration with Andrew Hoetker. ConstrictR (constrictor) and ConstrictPy are an R package and python tool designed together. ConstrictPy implements the functions and methods defined in ConstrictR and applies data handling, data parsing, input/output (I/O), and a user interface to increase usability. ConstrictR implements a variety of common data analysis methods used for statistical and subnetwork analysis. The majority of these methods are inspired by Lionel Guidi's 2016 paper, Plankton networks driving carbon export in the oligotrophic ocean. Additional methods were added to expand functionality, usability, and applicability to different areas of data science. Both ConstrictR and ConstrictPy are currently publicly available and usable, however, they are both ongoing projects. ConstrictR is available at github.com/cnegrich and ConstrictPy is available at github.com/ahoetker. Currently, ConstrictR has implemented functions for descriptive statistics, correlation, covariance, rank, sparsity, and weighted correlation network analysis with clustering, centrality, profiling, error handling, and data parsing methods to be released soon. ConstrictPy has fully implemented and integrated the features in ConstrictR as well as created functions for I/O and conversion between pandas and R data frames with a full feature user interface to be released soon. Both ConstrictR and ConstrictPy are designed to work with minimal dependencies and maximum available information on the algorithms implemented. As a result, ConstrictR is only dependent on base R (v3.4.4) functions with no libraries imported. ConstrictPy is dependent upon only pandas, Rpy2, and ConstrictR. This was done to increase longevity and independence of these tools. Additionally, all mathematical information is documented alongside the code, increasing the available information on how these tools function. Although neither tool is in its final version, this paper documents the code, mathematics, and instructions for use, in addition to plans for future work, for of the current versions of ConstrictR (v0.0.1) and ConstrictPy (v0.0.1).
Date Created
2018-05
Contributors
  • Negrich, Christopher Alec (Author)
  • Can, Huansheng (Thesis director)
  • Hansford, Dianne (Committee member)
  • School of Mathematical and Statistical Sciences (Contributor)
  • Barrett, The Honors College (Contributor)
Topical Subject
  • Python
  • R
  • Tools
  • Bioinformatics
  • Microbiomes
Resource Type
Text
Extent
16 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Barrett, The Honors College Thesis/Creative Project Collection
Series
Academic Year 2017-2018
Handle
https://hdl.handle.net/2286/R.I.48156
Level of coding
minimal
Cataloging Standards
asu1
System Created
  • 2018-04-21 12:23:03
System Modified
  • 2021-08-11 04:09:57
  •     
  • 2 years 3 months ago
Additional Formats
  • OAI Dublin Core
  • MODS XML

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