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Datasets

published: 2018-06-18
 
This repository contains datasets and R scripts that were used in a study of the population structure of Miscanthus sacchariflorus in its native range across East Asia. Notably, genotypes of 764 individuals at 34,605 SNPs, called from reduced-representation DNA sequencing using a non-reference bioinformatics pipeline, are provided. Two similar SNP datasets, used for identifying clonal duplicates and for determining the ancestry of ornamental and hybrid Miscanthus plants identified in previous studies respectively, are also provided. There is also a spreadsheet listing the provenance and ploidy of all individuals along with their plastid (chloroplast) haplotypes. Software output for Structure, Treemix, and DIYABC is also included. See README.txt for more information about individual files. Results of this study are described in a manuscript in revision in Annals of Botany by the same authors, "Population structure of Miscanthus sacchariflorus reveals two major polyploidization events, tetraploid-mediated unidirectional introgression from diploid Miscanthus sinensis, and diversity centered around the Yellow Sea."
keywords: Miscanthus; restriction site-associated DNA sequencing (RAD-seq); single nucleotide polymorphism (SNP); population genetics; Miscanthus xgiganteus; Miscanthus sacchariflorus; R scripts; germplasm; plastid haplotype
published: 2018-04-26
 
GBS data from soybean lines carrying introgressions from Glycine tomentella. This project is led by Dr. Randy Nelson, USDA scientist at the University of Illinois. Fastq files contain raw Illumina data. Txt files are keyfiles containing barcodes for each genetic entity.
published: 2018-05-01
 
GBS data for G. max x G. soja crosses, a project led by Dr. Randy Nelson.
published: 2017-12-04
 
Data used for Zaya et al. (2018), published in Invasive Plant Science and Management DOI 10.1017/inp.2017.37, are made available here. There are three spreadsheet files (CSV) available, as well as a text file that has detailed descriptions for each file ("readme.txt"). One spreadsheet file ("prices.csv") gives pricing information, associated with Figure 3 in Zaya et al. (2018). The other two spreadsheet files are associated with the genetic analysis, where one file contains raw data for biallelic microsatellite loci ("genotypes.csv") and the other ("structureResults.csv") contains the results of Bayesian clustering analysis with the program STRUCTURE. The genetic data may be especially useful for future researchers. The genetic data contain the genotypes of the horticultural samples that were the focus of the published article, and also genotypes of nearly 400 wild plants. More information on the location of the wild plant collections can be found in the Supplemental information for Zaya et al. (2015) Biological Invasions 17:2975–2988 DOI 10.1007/s10530-015-0926-z. See "readme.txt" for more information.
keywords: Horticultural industry; invasive species; microsatellite DNA; mislabeling; molecular testing
published: 2017-12-15
 
These are the results of an 8 month cohort study in two commercial dairy herds in Northwest Illinois. From each herd, 50 cows were selected at random, stratified over lactations 1 to 3. Serum from these animals was collected every two months and tested for antibodies to Bovine Leukosis Virus, Neospora caninum, and Mycobacterium avium subsp. paratuberculosis. Animals that left the herd during the study were replaced by another animal in the same herd and lactation. At the last sampling, serum neutralization assays were performed for Bovine Herpesvirus type 1 and Bovine Viral Diarrhea virus type 1 and 2. Production data before and after sampling was collected for the entire herd from PCdart.
keywords: serostatus;dairy;production;cohort
published: 2018-01-13
 
This dataset provides the time series (Aug. - Sep. 2016) data of sun-induced chlorophyll fluorescence, photosynthesis, photosynthetically active radiation, and associated vegetation indices that were collected in a soybean field in the farm of University of Illinois at Urbana and Champaign. Data contain 255 records and 6 variables (PPFD-IN: Photosynthetically active radiation; GPP-Gross Primary Production; SIF: Sun-Induced Fluorescence; NDVI: Normalized Difference Vegetation Index; Rededge: Rededge Index; Redege_NDVI: Rededge Normalized Difference Vegetation Index). The timestamp uses the standard time. Data are available from 8 am to 4 pm (corresponding to 9 am to 5 pm local time) every day.
keywords: sun-induced chlorophyll fluorescence; photosynthesis; soybean
published: 2018-02-22
 
Datasets used in the study, "OCTAL: Optimal Completion of Gene Trees in Polynomial Time," under review at Algorithms for Molecular Biology. Note: DS_STORE file in 25gen-10M folder can be disregarded.
keywords: phylogenomics; missing data; coalescent-based species tree estimation; gene trees
published: 2017-06-16
 
Table S1. Pollen types identified in the BCI and PNSL pollen rain data sets. Pollen types were identified to species when possible and assigned a life form based on descriptions provided in Croat, T.B. (1978). Taxa from BCI and PNSL were assigned a 1 if present in forest census data or a 0 if absent. The relative representation of each taxon has been provided for each extended record and by dry and wet season representation respectively. CA loadings are provided for axes 1 and 2 (Fig. 1).
keywords: pollen; identifications; abundance; data; BCI; PNSL; Panama
published: 2017-10-11
 
The International Registry of Reproductive Pathology Database is part of pioneering work done by Dr. Kenneth McEntee to comprehensively document thousands of disease cases studies. His large and comprehensive collection of case reports and physical samples was complimented by development of the International Registry of Reproductive Pathology Database in the 1980s. The original FoxPro Database files and a migrated access version were completed by the College of Veterinary Medicine in 2016. Access CSV files were completed by the University of Illinois Library in 2017.
keywords: Animal Pathology; Databases; Veterinary Medicine
published: 2017-09-28
 
This is the dataset used in the Journal of Ecology publication of the same name. It is a site by species matrix of species relative abundances. The file BH.veg.data.csv contains a site by species matrix of species relative abundance (percent cover across all sampling quadrats within site). Data under the heading Year refers to sampling periods. Year 1 refers to the first set of samples taken between 1997 and 2000, Year 2 refers to the second set taken between 2002 and 2005, Year 3 refers to the third set taken between 2007 and 2010, and Year 4 refers to the fourth set taken between 2012 and 2015. All sites met Critical Trends Assessment Program (CTAP) size criteria of being at least 2 ha in size with a minimum of 500 m2 of suitable sampling area. The data in file BH.site.location.csv contains Public Land Survey System ranges and townships in which specific sites were located. All sites were located within the U.S. state of Illinois. More information about this dataset: Interested parties can request data from the Critical Trends Assessment Program, which was the source for the data on the wetlands in this study. More information on the program and data requests can be obtained by visiting the program webpage. Critical Trends Assessment Program, Illinois Natural History Survey. http://wwx.inhs.illinois.edu/research/ctap/
keywords: biodiversity; biotic homogenization; invasive species; Phalaris arundinacea; plant population and community dynamics; similarity index; wetlands
published: 2017-09-06
 
Spire angle data for sinistral whelks of the family Busyconidae. Data focuses on spire angles, with some data on total shell length. Locality information is present for all modern specimens.
keywords: lightning whelk; sinistral whelk; spire angle; sourcing; Busycon; Cahokia; Spiro
published: 2017-06-16
 
Table S2. Raw pollen counts and climatic data for each seasonal sampling period. Climatic data reflects the average daily conditions observed over the duration samples were collected (˚C/day, mm/day, MJ/m2/day). Lycopodium counts and counts for each pollen taxon reflect the aggregated pollen sum from four sampling heights.
keywords: pollen; count; climate; data; BCI; PNSL; Panama
published: 2017-06-16
 
Table S3. Mean slope response for each predictive model used in the ecoinformatic analysis. Mean responses are provided for each seasonal and annual pollen data set analyzed from BCI and PNSL and are summarized by life form. Calculated p-values are provided for each model.
keywords: pollen; response; climate; ecoinformatics; BCI; PNSL; Panama
published: 2017-06-15
 
Datasets used in the study, "Optimal completion of incomplete gene trees in polynomial time using OCTAL," presented at WABI 2017.
keywords: phylogenomics; missing data; coalescent-based species tree estimation; gene trees
published: 2017-05-31
 
Dataset includes maternal antigen treatment and early-life antigen treatment for male zebra finches. Also includes data on beak coloration, measures of song complexity for each male, and female responses to treated males. Male beak color and song metadata: * MATID= Maternal Identity * MATTRT=Maternal antigen treatment prior to egg laying (KLH=keyhole limpet hemocyanin, LPS= lipopolysaccharide, PBS=phosphate buffered saline) * YGTRT= Young antigen treatment post-hatch (KLH=keyhole limpet hemocyanin, LPS= lipopolysaccharide, PBS=phosphate buffered saline)) * NESTBANDNUM= Nestling band number * Haptoglobin=haptoglobin levels at day 28 (mg/ml) * Mean TE= Mean number of total elements in that male's song * TE (z)= Z-transformed total elements * Mean UE=Mean number of unique elements in the song * UE (z)= z-transformed unique elements * mean phrases= Mean number of song phrases * Phrases (z)= z-transformed song phrases * Mean D= Mean song duration in seconds * D (z)=z-transformed song duration * B2 standard=beak brightness standardized so that lower values reflect less bright beaks * B2 (z)=z-transformed brightness * S1R standard= beak saturation at high wavelengths standardized so that lower values reflect less red beaks * S1R (z)=z-transformed S1R * S1U standard= beak saturation at low wavelengths standardized so that lower values reflect less red beaks * S1U (z)=z-transformed S1U * H4B standard= beak hue standardized so that lower values reflect less red beaks * H4B (z)=z-transformed H4B Female choice metadata: * Control Bird=PBS denotes that all control males received phosphate buffered saline * Treatment Bird= Treatment the male received (keyhole limpet hemocyanin (KLH) or lipopolysaccharide (LPS)) * Beak Wipes Control=# of beak wipes the female performed when on the control male side * Beak Wipes Treatment=# of beak wipes the female performed when on the "treatment male" side * Hops Control=# of hops female performed when on the control male side * Hops Treatment=# of hops female performed when on the treatment male side * Time Spent Near Control=amount of time (sec) female spent on the control male side * Time Spent Near Treatment=amount of time (sec) the female spent on the treatment male side
keywords: early-life; stress; immune response; phenotypic correlation; sexual signal; zebra finch;birdsongs; acoustic signals; beak coloration; mate selection
published: 2017-03-02
 
This data was collected between 2004 and 2010 at White River National Wildlife Refuge (WRNWR) and Saint Francis National Forest (SF). It was collected as part of two master’s and one PhD project at Arkansas State University USA studying Swainson’s Warbler habitat use, survival, and body condition.
keywords: Swainson’s Warbler; Limnothlypis swainsonii; flooding; natural disturbance; apparent survival; body condition
published: 2017-02-23
 
GBS data from diverse sorghum lines. Project funded by DOE, ARPA-E, and startup funds to PJ Brown.
published: 2017-02-21
 
GBS data from biparental sorghum populations provided by Dr. Bill Rooney, TAMU. Data produced and analyzed by Pradeep Hirannaiah to study recombination in sorghum. Funding for this study was provided by the Sorghum Checkoff.
published: 2017-02-21
 
GBS data from diverse sorghum lines. Project funded by DOE, ARPA-E, and startup funds to PJ Brown.