cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5061/dryad.kr17k
title: Data from: Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data

description: In vivo calcium imaging through microendoscopic lenses enables imaging of
 previously inaccessible neuronal populations deep within the brains of
 freely moving animals. However, it is computationally challenging to
 extract single-neuronal activity from microendoscopic data, because of the
 very large background fluctuations and high spatial overlaps intrinsic to
 this recording modality. Here, we describe a new constrained matrix
 factorization approach to accurately separate the background and then
 demix and denoise the neuronal signals of interest. We compared the
 proposed method against previous independent components analysis and
 constrained nonnegative matrix factorization approaches. On both simulated
 and experimental data recorded from mice, our method substantially
 improved the quality of extracted cellular signals and detected more
 well-isolated neural signals, especially in noisy data regimes. These
 advances can in turn significantly enhance the statistical power of
 downstream analyses, and ultimately improve scientific conclusions derived
 from microendoscopic data.
description: in vivo calcium imaging
 data recorded in dorsal striatum of a freely behaving
 mouseThis data correspond to
 Figure 5 in our manuscript.blood_vessel_10Hz.matin vivo calcium imaging data recorded in prefrontal cortex of a freely behaving mouseThis data corresponds to Figure 6 in our manuscript.PFC4_15Hz.matin vivo calcium imaging data recorded in BNST of a freely behaving mouseThis data corresponds to Figure 8 in our manuscript.CaMKII_120_TMT Exposure_5fps.matin vivo calcium imaging data recorded in ventral hippocampus of a freely behaving mouseThis data corresponds to Figure 7 in our manuscript.bma22_epm_motioncorrected_round1_cropped_correction.mat
DOI: 10.5061/dryad.s4d28
title: Data from: Comparative dynamics of microglialand glioma cell motility at the infiltrative margin of brain tumours

description: Microglia are a major cellular component of gliomas, and abundant in the
 centre of the tumour and at the infiltrative margins. While glioma is a
 notoriously infiltrative disease, the dynamics of microglia and glioma
 migratory patterns have not been well characterized. To investigate the
 migratory behaviour of microglia and glioma cells at the infiltrative
 edge, we performed two-colour time-lapse fluorescence microscopy of brain
 slices generated from a platelet-derived growth factor-B (PDGFB)-driven
 rat model of glioma, in which glioma cells and microglia were each
 labelled with one of two different fluorescent markers. We used
 mathematical techniques to analyse glioma cells and microglia motility
 with both single cell tracking and particle image velocimetry (PIV). Our
 results show microglia motility is strongly correlated with the presence
 of glioma, while the correlation of the speeds of glioma cells and
 microglia was variable and weak. Additionally, we showed that microglia
 and glioma cells exhibit different types of diffusive migratory behaviour.
 Microglia movement fit a simple random walk, while glioma cell movement
 fits a super diffusion pattern. These results show that glioma cells
 stimulate microglia motility at the infiltrative margins, creating a
 correlation between the spatial distribution of glioma cells and the
 pattern of microglia motility.
description: Time lapse microscopy -
 Experiment 3Time lapse microscopy
 video of microglia and glioma movement for Experiment
 3.3-4-14C2.zipTime lapse microscopy - Experiment 2Time lapse microscopy video of microglia and glioma movement for Experiment 2.6-6-11.zipTime lapse microscopy - Experiment 1Time lapse microscopy video of microglia and glioma movement for Experiment 1.5-16-11.zipCode and Data FilesThis zip file contains the code and data set used to conduct the analysis in the manuscript. Data includes tracking and PIV movie data from three separate experiments of microglia and glioma cells.To Generate Figures.zip
DOI: 10.5061/dryad.mp6cp
title: Data from: Extensive genetic diversity is present within North American switchgrass germplasm

description: Switchgrass (Panicum virgatum L.) is a perennial native North American
 grass present in two ecotypes: upland, found primarily in the northern
 range of switchgrass habitats, and lowland, found largely in the southern
 reaches of switchgrass habitats. Previous studies focused on a diversity
 panel of primarily northern switchgrass, so to expand our knowledge of
 genetic diversity in a broader set of North American switchgrass, exome
 capture sequence data were generated for 632 additional, primarily lowland
 individuals. In total, over 37 million single nucleotide polymorphisms
 (SNPs) were identified and a set of 1.9 million high-confidence SNPs were
 obtained from 1169 individuals from 140 populations (67 upland, 65
 lowland, 8 admixed) were used in downstream analyses of genetic diversity
 and population structure. Seven separate population groups were identified
 with moderate genetic differentiation [mean fixation index (Fst) estimate
 of 0.06] between the lowland and the upland populations. Ecotype-specific
 and population-specific SNPs were identified for use in germplasm
 evaluations. Relative to rice (Oryza sativa L.), maize (Zea mays L.),
 soybean [Glycine max (L.) Merr.], and Medicago truncatula Gaertn.,
 analyses of nucleotide diversity revealed a high degree of genetic
 diversity (0.0135) across all individuals, consistent with the outcrossing
 mode of reproduction and the polyploidy of switchgrass. This study
 supports the hypothesis that repeated glaciation events, ploidy barriers,
 and restricted gene flow caused by flowering time differences have
 resulted in distinct gene pools across ecotypes and geographic regions.
 These data provide a resource to associate alleles with traits of interest
 for forage, restoration, and biofuel feedstock efforts in switchgrass.
description: README.rtfREADME.rtf10_colored_tree_RENAMED_xK09_corrected.nwkGenetic distance tree as presented in Figure 3 based on K=9 in newick format.snipe_slap_sapper_filtered_biallelic_snps_final_reheader.txt.bz2HapMapv2 SNP matrix. All SNPs, coordinate positions, and allele calls for HapMap v2.
DOI: 10.5061/dryad.hk258
title: Data from: Insight in genome-wide association of metabolite quantitative traits by exome sequence analyses

description: Metabolite quantitative traits carry great promise for epidemiological
 studies, and their genetic background has been addressed using Genome-Wide
 Association Studies (GWAS). Thus far, the role of less common variants has
 not been exhaustively studied. Here, we set out a GWAS for metabolite
 quantitative traits in serum, followed by exome sequence analysis to zoom
 in on putative causal variants in the associated genes. 1H Nuclear
 Magnetic Resonance (1H-NMR) spectroscopy experiments yielded successful
 quantification of 42 unique metabolites in 2,482 individuals from The
 Erasmus Rucphen Family (ERF) study. Heritability of metabolites were
 estimated by SOLAR. GWAS was performed by linear mixed models, using
 HapMap imputations. Based on physical vicinity and pathway analyses,
 candidate genes were screened for coding region variation using exome
 sequence data. Heritability estimates for metabolites ranged between 10%
 and 52%. GWAS replicated three known loci in the metabolome wide
 significance: CPS1 with glycine (P-value = 1.27×10−32), PRODH with proline
 (P-value = 1.11×10−19), SLC16A9 with carnitine level (P-value =
 4.81×10−14) and uncovered a novel association between DMGDH and
 dimethyl-glycine (P-value = 1.65×10−19) level. In addition, we found three
 novel, suggestively significant loci: TNP1 with pyruvate (P-value =
 1.26×10−8), KCNJ16 with 3-hydroxybutyrate (P-value = 1.65×10−8) and 2p12
 locus with valine (P-value = 3.49×10−8). Exome sequence analysis
 identified potentially causal coding and regulatory variants located in
 the genes CPS1, KCNJ2 and PRODH, and revealed allelic heterogeneity for
 CPS1 and PRODH. Combined GWAS and exome analyses of metabolites detected
 by high-resolution 1H-NMR is a robust approach to uncover metabolite
 quantitative trait loci (mQTL), and the likely causative variants in these
 loci. It is anticipated that insight in the genetics of intermediate
 phenotypes will provide additional insight into the genetics of complex
 traits.
description: Lipids_CH3.gwas2-Hydroxybutyrate.gwasLeucine.gwasIsoleucine.gwasValine.gwas3-Hydroxyisobutyrate.gwasAlpha-ketoisovalerate.gwasEthanol.gwas3-Hydroxybutyrate.gwasLipids_CH2.gwasAlanine.gwasAcetate.gwasMethionine.gwasAcetone.gwasLipids_CH2CO.gwasGlutamate.gwasPyruvate_Oxaloacetate.gwasSuccinate.gwasCarnitine.gwasGlutamine.gwasCitrate.gwasDimethylamine.gwasDimethylglycine.gwasAlpha-ketoglutarate.gwasLysine.gwasOrnithine.gwasTMAO_Betaine.gwas1_5-Anhydrosorbitol.gwasMethanol.gwasGlycine.gwasGlycerol.gwasMyoinositol.gwasBetaine.gwasCreatine.gwasCreatinine.gwasLactate.gwasProline.gwasGlucose.gwasLipids_CH=CH%2ACH2CH2.gwasLipids_CHTyrosine.gwasPhenylalanine.gwasFormate.gwas
DOI: 10.5061/dryad.354kg7d
title: Data from: Explosion-generated infrasound recorded on ground and airborne microbarometers at regional distances

description: Recent work in deploying infrasound (low frequency sound) sensors on
 aerostats and free flying balloons has shown them to be viable
 alternatives to ground stations. However, no study to date has compared
 the performance of surface and free floating infrasound microbarometers
 with respect to acoustic events at regional (100s of kilometers) range.
 The prospect of enhanced detection of aerial explosions at similar ranges,
 such as those from bolides, has not been investigated either. We examined
 infrasound signals from three 1 ton TNT equivalent explosions using
 microbarometers on two separate balloons at ranges of 280 to 400 km and
 ground stations at ranges of 6.3 to 350 km. Signal celerities were
 consistent with acoustic waves traveling in the stratospheric duct.
 However, significant differences were noted between the observed arrival
 patterns and those predicted by an acoustic propagation model. Very low
 background noise levels on the balloons were consistent with previous
 studies that suggest wind interference is minimal on freely drifting
 sensors. Simulated propagation patterns and observed noise levels also
 confirm that balloon-borne microbarometers should be very effective at
 detecting explosions in the middle and upper atmosphere as well as those
 on the surface.
description: Download the data file, unzip it, and then run the following
 shell commands to concatenate and then uncompress the files:
 <pre>cat
 usie.tgz.* | tar xzv</pre>
description: # Data from: Explosion-generated infrasound recorded on ground and
 airborne microbarometers at regional distances
 [https://doi.org/10.5061/dryad.354kg7d](https://doi.org/10.5061/dryad.354kg7d) Give a brief summary of dataset contents, contextualized in experimental procedures and results. ## Description of the data and file structure The data come in four tar archives that must be downloaded and combined using the following shell commands: There are two types of data included in this repository: raw digitizer output files in a proprietary format, and data converted into physical units (Pascals) in Seismic Analysis Code (SAC) format. Both types are provided for traceability purposes. The Seismic Analysis Code (SAC) file format is one of the most commonly used formats used in seismic studies. It can be read by a variety of programming languages, including the Obspy library in Python and RSEIS in R. It also has a standalone interactive program. A good reference for SAC is here: http://ds.iris.edu/files/sac-manual/manual/file\_format.html The raw digitizer output consists of files written by the Omnirecs (now DiGOS) Datacube unit. The manufacturer provides several methods of extracting data from these files. Programs for data extraction are located here: https://digos.eu/seismology/
DOI: 10.5061/dryad.ch4ns27
title: Data from: Prediction of cooking time for soaked and unsoaked dry beans (Phaseolus vulgaris L.) using hyperspectral imaging technology

description: The cooking time of dry beans varies widely by genotype and is also
 influenced by the growing environment, storage conditions and cooking
 method. Thus, high throughput phenotyping methods to assess cooking time
 would be useful to breeders interested in developing cultivars with
 desired cooking time. The objective of this study was to evaluate the
 performance of hyperspectral imaging technology for predicting dry bean
 cooking time. Fourteen dry bean (Phaseolus vulgaris L.) genotypes with a
 wide range of cooking times were grown in five environments over 2 yr.
 Hyperspectral images were taken from whole dry seeds and partial least
 squares regression models based on the extracted spectral image features
 were developed to predict water uptake and cooking time of both soaked and
 unsoaked beans. Relatively good predictions of water uptake were obtained,
 as measured by the correlation coefficient for prediction (Rpred=0.789)
 and standard error of prediction (SEP=4.4%). Good predictions of cooking
 time for soaked beans (ranging between 19.9–95.5 min) were achieved giving
 Rpred=0.886 and SEP=7.9 min. The prediction models for the cooking time of
 unsoaked beans (ranging between 80–147 min) were less robust and accurate
 (Rpred=0.708, SEP=10.6 min). This study demonstrated that hyperspectral
 imaging technology has potential for providing a nondestructive, simple,
 fast and economical means for estimating the water uptake and cooking time
 of dry beans. Moreover, a totally independent set of 110 similar dry bean
 samples confirmed the suitability of the technique for predicting cooking
 time of soaked beans after updating the calibration model with 20 of the
 new samples, giving Rpred=0.872 and SEP=3.7 min. However, due to the
 genotypic and phenotypic variability of dry bean properties, periodical
 updates of these prediction models with more samples and new bean
 accessions, as well as testing other multivariate prediction methods are
 needed for further improving model robustness and generalization.
description: HYP data
 2015MATLAB codes and
 representative pre-processed data files for cross-year model updating and
 testing using dry bean seeds information from 2015.HYP data
 2014MATLAB codes and
 representative pre-processed data files for model building and validation
 using dry bean seeds information from 2014.
DOI: 10.5061/dryad.pj105
title: Data from: Genetic drivers of pancreatic islet function

description: Nearly all gene loci that have been associated with type 2 diabetes play a
 role in pancreatic islet function. To evaluate the role of islet gene
 expression in the etiology of diabetes, we sensitized a genetically
 diverse mouse population with a Western diet and carried out genome-wide
 association mapping of diabetes-related phenotypes. We quantified mRNA
 abundance in the islets, and identified 18,775 expression quantitative
 trait loci. We applied mediation analysis to identify candidate causal
 driver genes at loci where numerous transcripts co-map. These include two
 genes previously associated with monogenic diabetes (PDX1 and HNF4A), as
 well as three genes with nominal association with diabetes-related traits
 in humans (FAM83E, IL6ST, and SAT2). We grouped transcripts into gene
 modules and show that these modules enrich for physiological pathways that
 also map to distinct loci. We identified and mapped regulatory loci for
 modules enriched with transcripts specific for α-cells, and another
 specific for δ-cells. However, no single module enriched for
 β-cell-specific transcripts, reflecting heterogeneity within the β-cell
 population. A module enriched in transcripts associated with branched
 chain amino acid metabolism was the most strongly correlated with clinical
 traits that reflect insulin resistance. Although the mice in this study
 were not overtly diabetic, the analysis of pancreatic islet gene
 expression under dietary-induced stress, enabled us to identify genes and
 pathways linked to diabetes-associated clinical traits. Our analysis
 reveals a high degree of concordance between diabetes-associated loci in
 the mouse with those found in human populations, and demonstrates how the
 mouse can provide evidence to support nominal associations found in human
 genome-wide association mapping.
description: Attie Islet eQTL
 dataThis is an R compressed
 binary file. The objects are described in the README.Attie_DO378_eQTL_viewer_v1.Rdata
DOI: 10.5061/dryad.8c81j
title: Data from: Robustness to noise in gene expression evolves despite epistatic constraints in a model of gene networks

description: Stochastic noise in gene expression causes variation in the development of
 phenotypes, making such noise a potential target of stabilizing selection.
 Here we develop a new simulation model of gene networks to study the
 adaptive landscape underlying the evolution of robustness to noise. We
 find that epistatic interactions between the determinants of the
 expression of a gene and its downstream effect impose significant
 constraints on evolution, but these interactions do allow the gradual
 evolution of increased robustness. Despite strong sign epistasis,
 adaptation rarely proceeds via deleterious intermediate steps, but instead
 occurs primarily through small beneficial mutations. A simple mathematical
 model captures the relevant features of the single-gene fitness landscape
 and explains counterintuitive patterns, such as a correlation between the
 mean and standard deviation of phenotypes. In more complex networks,
 mutations in regulatory regions provide evolutionary pathways to increased
 robustness. These results chart the constraints and possibilities of
 adaptation to reduce expression noise and demonstrate the potential of a
 novel modeling framework for gene networks.
description: Part APart A--use
 "cat" utility to reassemble into a zipped folder containing the
 complete code and data files.dryad_files_aPart BPart B--use "cat" utility to reassemble into a zipped folder containing the complete code and data files.dryad_files_bPart CPart C--use "cat" utility to reassemble into a zipped folder containing the complete code and data files.dryad_files_c
DOI: 10.5061/dryad.2822t
title: Data from: Macrophages contribute to the cyclic activation of adult hair follicle stem cells

description: Skin epithelial stem cells operate within a complex signaling milieu that
 orchestrates their lifetime regenerative properties. The question of
 whether and how immune cells impact on these stem cells within their niche
 is not well understood. Here we show that skin-resident macrophages
 decrease in number because of apoptosis before the onset of epithelial
 hair follicle stem cell activation during the murine hair cycle. This
 process is linked to distinct gene expression, including Wnt
 transcription. Interestingly, by mimicking this event through the
 selective induction of macrophage apoptosis in early telogen, we identify
 a novel involvement of macrophages in stem cell activation in vivo.
 Importantly, the macrophage-specific pharmacological inhibition of Wnt
 production delays hair follicle growth. Thus, perifollicular macrophages
 contribute to the activation of skin epithelial stem cells as a novel,
 additional cue that regulates their regenerative activity. This finding
 may have translational implications for skin repair, inflammatory skin
 diseases and cancer.
description: FCS Figure
 Files
DOI: 10.5061/dryad.7pt2m
title: Data from: Inbreeding and selection shape genomic diversity in captive populations: implications for the conservation of endangered species

description: Captive breeding programs are often initiated to prevent species
 extinction until reintroduction into the wild can occur. However, the
 evolution of captive populations via inbreeding, drift, and selection can
 impair fitness, compromising reintroduction programs. To better understand
 the evolutionary response of species bred in captivity, we used nearly
 5500 single nucleotide polymorphisms (SNPs) in populations of white-footed
 mice (Peromyscus leucopus) to measure the impact of breeding regimes on
 genomic diversity. We bred mice in captivity for 20 generations using two
 replicates of three protocols: random mating (RAN), selection for docile
 behaviors (DOC), and minimizing mean kinship (MK). The MK protocol most
 effectively retained genomic diversity and reduced the effects of
 selection. Additionally, genomic diversity was significantly related to
 fitness, as assessed with pedigrees and SNPs supported with genomic
 sequence data. Because captive-born individuals are often less fit in wild
 settings compared to wild-born individuals, captive-estimated fitness
 correlations likely underestimate the effects in wild populations.
 Therefore, minimizing inbreeding and selection in captive populations is
 critical to increasing the probability of releasing fit individuals into
 the wild.
description: GBS-SNPsSNP genotypes generated using genotyping by sequencing approaches. SNPs were used to characterize genomic diversity of captive Peromyscus leucopus populations. See readme for additional information.genome annotationAnnotation associated with genome sequencing of Peromyscus leucopus. Additional details are provided in the readme file, and raw reads are available via genbank.genome_annotation.tarPeromyscus leucopus genome assemblyGenome assembly that utilized 2 lanes of illumina 150bp, paired end reads (available at NCBI genbank accession number PRJNA375113).pleucopus.fasta.zip
DOI: 10.5061/dryad.2fc32
title: Data from: Long-term experimental warming alters community composition of ascomycetes in Alaskan moist and dry arctic tundra

description: Arctic tundra regions have been responding to global warming with visible
 changes in plant community composition, including expansion of shrubs and
 declines in lichens and bryophytes. Even though it is well-known that the
 majority of arctic plants are associated with their symbiotic fungi, how
 fungal community composition will be different with climate warming
 remains largely unknown. In this study, we addressed the effects of
 long-term (18 years) experimental warming on the community composition and
 taxonomic richness of soil ascomycetes in dry and moist tundra types.
 Using deep Ion Torrent sequencing we quantified how OTU assemblage and
 richness of different orders of Ascomycota changed in response to summer
 warming. Experimental warming significantly altered ascomycete communities
 with stronger responses observed in the moist tundra compared to dry
 tundra. The proportion of several lichenized and moss-associated fungi
 decreased with warming, while the proportion of several plant and insect
 pathogens and saprotrophic species was higher in the warming treatment.
 The observed alterations in both taxonomic and ecological groups of
 ascomycetes are discussed in relation to previously reported
 warming-induced shifts in arctic plant communities, including decline in
 lichens and bryophytes and increase in coverage and biomass of shrubs.
description: DC1ITS2 rDNA sequence data
 partitioned into individual soil samples based on tag
 identifiers.DC2DC3DC4DC5DT1DT2DT3DT4DT5MC1MC2MC3MC4MC5MT1MT2MT3MT4MT5