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Data from: Genomic analysis of Vanessa tameamea, the threatened Hawaiian endemic butterfly, reveals population genetic structure relevant to conservation efforts

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posted on 2024-12-13, 23:48 authored by HALEY ARNOLDHALEY ARNOLD, SHEINA SIMSHEINA SIM

Scripts listed here exemplify those used in the assembly of the Vanessa tameamea genome (Hawaiian Kamehameha butterfly) as found in NCBI BioProjects PRJNA1029194 (female) and PRJNA1029239 (male). Reduced representation sequences from double digest Restriction Associated DNA (ddRAD) are included in BioProject PRJNA428520 and were used for population genetic analyses. All workflows and analyses except for the DAPC (Discriminant Analysis of Principal Components), PCA (Principal Component Analysis), and hierarchical Fst were performed on the United States Department of Agriculture (USDA) - SCINet/Mississippi State University High Performance Computing Cluster (HPC) Atlas and were installed via Conda. The remaining scripts were run in R.

Funding

USDA-ARS: 2040-22430-028-000-D

USDA-ARS: 0201-88888-003-000D

USDA-ARS: 0201-88888-002-000D

History

Data contact name

Arnold, Haley, E.

Data contact email

arnoldhaley3@gmail.com

Publisher

Ag Data Commons

Temporal Extent Start Date

2023-10-01

Theme

  • Non-geospatial

ISO Topic Category

  • biota

National Agricultural Library Thesaurus terms

Vanessa tameamea; genome assembly; population genetics; genetic analysis; genome; females; males; DNA; discriminant analysis; principal component analysis; USDA; Hawaii; butterflies; models; protocols; threatened species; conservation programs

OMB Bureau Code

  • 005:18 - Agricultural Research Service

OMB Program Code

  • 005:040 - National Research

ARS National Program Number

  • 304

Pending citation

  • Yes

Related material without URL

Genomic analysis of Vanessa tameamea, the threatened Hawaiian endemic butterfly, reveals population genetic structure relevant to conservation efforts” with authors: Haley E. Arnold, Julian R. Dupuis, Daniel Rubinoff, William P. Haines, Scott M. Geib, and Sheina B. Sim (In Press).

Public Access Level

  • Public