Find research datasets worth reusing

opencc-by-4.0Nov 2024View details →

Improving anxiety research novel approach to reveal trait anxiety through summary measures of multiple states - raw count data set - RNAseq

Raw count data of the RNAseq analysis of a project and manuscript under the title "Improving anxiety research novel approach to reveal trait anxiety through summary measures of multiple states". The header of the table includes the subject identifiers except the first column "genes". The latter column includes all assessed gene identifiers.

opencc-by-4.0Mar 2018View details →

Project Tycho Level 2 data: Counts of multiple diseases reported in UNITED STATES OF AMERICA, 1888-2014

Project Tycho data include counts of infectious disease cases or deaths per time interval. A count is equivalent to a data point.Project Tycho level 2 version 1.1.0 data include data counts that have been filtered from the raw data to render standardized data that can be used immediately for analysis. All level 2 data were originally reported in a consistent format and have not been transformed into a standard format by Project Tycho staff, except for smallpox records that included repeated counts for the same location and week, but sometimes with different numbers. These duplicate smallpox records have been averaged into one count for each location and week. Level 2 data include counts for a wide variety of diseases and locations for varying time periods. Because we removed data in an inconsistent format from level 2 data, counts may be missing for certain diseases, locations, or years. For the most complete collection of standardized data, we encourage users to use Project Tycho version 2.0 datasets.More detailed methods and additional information about the origin of Projec Tycho level 2 version 1.1.0 data can be found in our original publication in the New England Journal of Medicine: <a href="http://www.nejm.org/doi/full/10.1056/NEJMms1215400">http://www.nejm.org/doi/full/10.1056/NEJMms1215400</a>Level 2 version 1.1.0 data is represented in a CSV file with 11 columns:<ul><li>epi_week: a six digit number that represents the year and epidemiological week for which disease cases or deaths were reported (yyyyww)</li><li>country: a two digit country abbreviation, only including "US" in version 1.1.0</li><li>state: the two digit postal code state abbreviation that represents the state for which a count has been reported</li><li>loc: the name of a state or city for which a count has been reported, capitalized</li><li>loc_type: the type of location (STATE or CITY) for which a count has been reported</li><li>disease: the disease for which a count has been reported, in all capitals</li><li>event: an indicator representing the disease outcome reported, including "CASES" or "DEATHS"</li><li>number: the reported number of cases or deaths</li><li>from_date: the start date of the time interval for which a count was reported, as yyyy-mm-dd</li><li>to_date: the end date of the time interval for which a count was reported, as yyyy-mm-dd</li><li>url: the URL of the source document from which the count was obtained</li></ul>

opencc-by-4.0Mar 2018View details →

Project Tycho Level 1 data: Counts of multiple diseases reported in UNITED STATES OF AMERICA, 1916-2011

Project Tycho data include counts of infectious disease cases or deaths per time interval. A count is equivalent to a data point. Project Tycho level 1 data include data counts that have been standardized for a specific, published, analysis. Standardization of level 1 data included representing various types of data counts into a common format and excluding data counts that are not required for the intended analysis. In addition, external data such as population data may have been integrated with disease data to derive rates or for other applications.Version 1.0.0 of level 1 data includes counts at the state level for smallpox, polio, measles, mumps, rubella, hepatitis A, and whooping cough and at the city level for diphtheria. The time period of data varies per disease somewhere between 1916 and 2011. This version includes cases as well as incidence rates per 100,000 population based on historical population estimates. These data have been used by investigators at the University of Pittsburgh to estimate the impact of vaccination programs in the United States, published in the New England Journal of Medicine: <a href="http://www.nejm.org/doi/full/10.1056/NEJMms1215400">http://www.nejm.org/doi/full/10.1056/NEJMms1215400</a>. See this paper for additional methods and detail about the origin of level 1 version 1.0.0 data.Level 1 version 1.0.0 data is represented in a CSV file with 7 columns:<ul><li>epi_week: a six digit number that represents the year and epidemiological week for which disease cases or deaths were reported (yyyyww)</li><li>state: the two digit postal code state abbreviation that represents the state for which a count has been reported</li><li>loc: the name of a state or city for which a count has been reported, capitalized</li><li>loc_type: the type of location (STATE or CITY) for which a count has been reported</li><li>disease: the disease for which a count has been reported: HEPATITIS A, MEASLES, MUMPS, PERTUSSIS, POLIO, RUBELLA, SMALLPOX, or DIPHTHERIA</li><li>cases: the number of cases reported for the specified disease, epidemiological week, and location</li><li>incidence_per_100000: the number of cases per 100,000 people, computed using historical population counts for cities and states as reported by the US Census Bureau</li></ul>

opencc-by-nc-sa-4.0Jun 2019View details →

UK Parliament Petition Website: Hourly count data

This dataset contains hourly counts of the number of signatures on each petition posted to the UK Parliament petition website from 2015-07-20 to 2016-09-12. The file is gzip compressed text data in tab-separated values format with four columns: <ul> <li>db_id: An internal id number</li> <li>pet_id: The id of the petition on the Parliament website (e.g., 131215 corresponds to the petition https://petition.parliament.uk/archived/petitions/131215 )</li> <li>sigs: The number of signatures observed at datetime.</li> <li>datetime: The date and time of the observation in YYYY-MM-DD HH:mm:SS format (e.g., 2015-07-20 18:24:35)</li> </ul> This data was collected via a Python scrapping script and initially stored in a MySQL database.

openCC (other)Jan 2025View details →

Fish and crayfish density and count data for Peeks Creek, Macon County, NC, USA 2005-2014, 2019, and 2022 following a catastrophic debris flow, as well as six reference streams

We followed the process of recovery of the fish and crayfish assemblage in Peeks Creek, a high-gradient second order stream in the Little Tennessee River watershed of North Carolina, after a debris flow devastated the channel and its riparian zone. After 15 years, the fish assemblage had recovered, and the channel and riparian zone had stabilized. Of the three major components of the fish assemblage, Rainbow Trout (Oncorhynchus mykiss (Walbaum)), a strong swimmer, reappeared in year 1. Longnose Dace (Rhinichthys cataractae (Valenciennes in Cuvier and Valenciennes)) reappeared in year 3. Mottled Sculpin (Cottus bairdii Girard), a weak swimmer, did not become established until year 6 and only resumed expected abundance in year 9. Appalachian Brook Crayfish (Cambarus bartonii cavatus Hay) numbers recovered quickly, though only one individual was found the year following the debris flow. Unassisted natural recovery occurred after a costly engineered restoration project had been rejected and arguably represents the preferable solution. However, recovery of the fish assemblage may not have been achieved if the stream flowed directly into an impoundment or low gradient river that lacked the source of species for recolonization, or if the stream had been located above a barrier to upstream movement.

openCC (other)May 2010View details →

Macrophyte count data collected from Northeast Shark Slough, Everglades National Park (FCE LTER) from September 2006 to September 2008

Three 1m2 throws are made within a few meters of each site center. Within each throw, all emergent macrophytes are counted (live and dead) and recorded. Submerged periphyton-associated aquatic vegetation are identified and recorded as a percentage of the total periphyton component. Macrophyte cover is recorded in percent cover, and average plant height is determined from three representative plants. Water depth is also recorded as an average of three depths.

openCC (other)Dec 2019View details →

Count data of air-breathing fauna from visual transect surveys including water temperature, time, sea and weather conditions in Shark Bay Marine Park, Western Australia from February 2008 to July 2014

This dataset provides information on the relative abundances of air breathing fauna (dugongs, dolphins, sea snakes, marine birds, and sea turtles) in the study area of the Eastern Gulf of Shark Bay, Western Australia. The dataset comprises transects that quantify animal abundances in three microhabitats (shallow seagrass banks, seagrass bank edges, and deep sandy channels). These microhabitats vary in their food supply as well as their potential to facilitate or inhibit detection and escape from predators, mainly the tiger shark (Galeocerdo cuvier). As a result these data have been used to examine risk-specific habitat use behaviors of these fauna, in addition to general abundance estimates.

openCC (other)Nov 2023View details →

Canopy Trimming Experiment (CTE) litterbag invertebrate counts and weights data

Identification, number and dry weight of invertebrates recovered from each litterbag. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.

opencc-by-4.0Apr 2024View details →

JR100 Expedition 379T Site J1002 beryllium isotope, XRF element count and carbon isotope data sets

<h2>JR100 Expedition 379T Site J1002 beryllium isotope, XRF element count and carbon isotope data sets (Finalised 8th of April 2024)</h2> <h3>How to cite these data:</h3> The full data were published in Sproson et al., 2024. Sproson AD, Yokoyama Y, Miyairi Y, Aze T, Clementi VJ, Riechelson H, Bova SC, Rosenthal Y, Childress LB & Expedition 379T Scientists. Near-synchronous Northern Hemisphere and Patagonian ice sheet variation over the last glacial cycle. Nature Geoscience <a href="https://doi.org/10.1038/s41561-024-01436-y">https://doi.org/10.1038/s41561-024-01436-y</a> (2024). <h3>Files:</h3> Supplementary Table 1: Multiple linear regression results between 10Be/9Be ratios and sedimentation rate, K/Ca, Fe/Ca, Al/Ti (this study), Green/Blue (Li et al., 2022), and Global Mean Sea Level (Lambeck et al., 2014). The multiple linear regression was calculated using the MATLAB(R) function “regress”. Supplementary Table 2:  Age-depth model and beryllium isotope measurements for Site J1002. The age-depth model was calculated from radiocarbon dates and oxygen isotope stratigraphy (Li et al., 2022) using the BIGMACS modelling routine (Lee et al., 2022). Beryllium-9 and beryllium-10 were measured by Adam D. Sproson by HR-ICP-MS and AMS at the Atmosphere and Ocean Research Institute (Sproson et al., 2021) and University of Tokyo (Matsuzaki et al., 2007), respectively. 10Be/9Be* ratios were corrected for 10Be paleo-production following von Blanckenburg et al. (2015).  Supplementary Table 3: X-ray Fluorescence Ti, K, Fe, Ca, and Al element counts per second for Site J1002 measured at the Lamont-Doherty Earth Observatory by Vincent J. Clementi. Supplementary Table 4: Carbon isotope measurements for the benthic foraminifera, U. peregrina, measured at Rutgers University by Vincent J. Clementi. <h3>Format:</h3> Depth (m CCSF-A) = core composite depth below seafloor. Calendar age (kyr BP) = age in thousand years before present. [10Be]reac, [9Be]reac = the concentration of 10Be and 9Be in the reactive phase of marine sediments.  Sample ID = expedition sample designation specifying hole (e.g., A), core number (e.g., 1), type (i.e., H), section number (e.g., 1), and then section half (i.e., W). σ = standard deviation. <h3>References:</h3> Lambeck K, Rouby H, Purcell A, Sun Y, Sambridge M. Sea level and global ice volumes from the Last Glacial Maximum to the Holocene. Proceedings of the National Academy of Sciences. 2014;111(43):15296-15303.  Lee T, Rand D, Lisiecki LE, Gebbie G, Lawrence CE. Bayesian age models and stacks: Combining age inferences from radiocarbon and benthic δ18O stratigraphic alignment. EGUsphere. 2022;2022:1-29. Li C, Clementi VJ, Bova SC, et al. The sediment green‐blue color ratio as a proxy for biogenic silica productivity along the Chilean Margin. Geochemistry, Geophysics, Geosystems. 2022:e2022GC010350.  Matsuzaki H, Nakano C, Tsuchiya Y, et al. Multi-nuclide AMS performances at MALT. Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms. 2007;259(1):36-40.  Sproson AD, Aze T, Behrens B, Yokoyama Y. Initial measurement of beryllium‐9 using high‐resolution inductively coupled plasma mass spectrometry allows for more precise applications of the beryllium isotope system within the Earth Sciences. Rapid Communications in Mass Spectrometry. 2021;35(8):e9059.  Von Blanckenburg F, Bouchez J, Ibarra DE, Maher K. Stable runoff and weathering fluxes into the oceans over Quaternary climate cycles. Nature Geoscience. 2015;8(7):538-542.

opencc-by-4.0Mar 2022View details →

Gene expression count data from human post-mortem spinal cord

Gene expression data from human post-mortem tissue for three spinal cord sections (cervical, thoracic and lumbar) from amyotrophic lateral sclerosis (ALS) patients and non-neurological disease controls. RNA sequencing performed as part of the New York Genome Center ALS Consortium. Analysis workbooks: <a href="https://jackhump.github.io/ALS_SpinalCord_QTLs/">https://jackhump.github.io/ALS_SpinalCord_QTLs/</a>  Preprint describing results: <a href="https://www.medrxiv.org/content/10.1101/2021.08.31.21262682v1">https://www.medrxiv.org/content/10.1101/2021.08.31.21262682v1</a>  Sample sizes: <table align="left"> <tbody> <tr> <td> Region </td> <td> Control </td> <td> ALS </td> </tr> <tr> <td> Cervical </td> <td> 35 </td> <td> 139 </td> </tr> <tr> <td> Thoracic  </td> <td> 10 </td> <td> 42 </td> </tr> <tr> <td> Lumbar </td> <td> 32 </td> <td> 122 </td> </tr> </tbody> </table>               Library preparation RNA was extracted from flash-frozen postmortem tissue using TRIzol (Thermo Fisher Scientific) chloroform, followed by column purification (RNeasy Minikit, QIAGEN). RNA integrity number (RIN) was assessed on a Bioanalyzer (Agilent Technologies). RNA-Seq libraries were prepared from 500ng total RNA using the KAPA Stranded RNA-Seq Kit with RiboErase (KAPA Biosystems) for rRNA depletion and Illumina-compatible indexes (NEXTflex RNA-Seq Barcodes, NOVA-512915, PerkinElmer, and IDT for Illumina TruSeq UD Indexes, 20022370). Pooled libraries (average insert size: 375 bp) passing the quality criteria were sequenced either on an Illumina HiSeq 2500 (125 bp paired end) or an Illumina NovaSeq (100 bp paired-end). The samples had a median sequencing depth of 42 million read pairs, with a range between 16 and 167 million read pairs. Data processing Samples were uniformly processed using RAPiD-nf, an efficient RNA-Seq processing pipeline implemented in the NextFlow framework. Following adapter trimming with Trimmomatic (version 0.36), all samples were aligned to the hg38 build (GRCh38.primary_assembly) of the human reference genome using STAR (2.7.2a), with indexes created from GENCODE, version 30. Gene expression was quantified using RSEM (1.3.1) using GENCODE v30. Quality control was performed using SAMtools and Picard, and the results were collated using MultiQC. Various technical metrics for sequencing quality control are provided in the metadata. Estimated read counts and normalised transcripts per million (TPM) matrices provided for each tissue. Provided data: gencode.v30.gene_meta.tsv.gz - tab separated table with columns "genename", the HGNC gene symbol, and "geneid" the Ensembl ID, as set in the GENCODE v30 comprehensive annotation. For {tissue} in Cervical_Spinal_Cord, Thoracic_Spinal_Cord, Lumbar_Spinal_Cord: {tissue}_metadata.tsv.gz - metadata describing each sample. Each row describes a sample. Descriptions of each column below. {tissue}_gene_tpm.tsv.gz - the normalised TPM values from RSEM for all 58,884 genes in GENCODE v30. Each row describes a gene and each column describes a sample. {tissue}_gene_counts.tsv.gz - the estimated read counts from RSEM for all 58,884 genes in GENCODE v30. Each row describes a gene and each column describes a sample. Metadata Column Description rna_id  - de-identified sample ID for each unique RNA-seq sample dna_id - de-identified donor ID for each patient enrolled in the study site_id - de-identified site name for each contributing site tissue - name of tissue/region age_rounded - age at death, rounded to nearest decade sex - biological sex of donor subject_group - long form disease group disease - short form disease group site_of_motor_onset - for ALS donors, where did symptoms start? disease_duration - for ALS donors, how long did donor live with disease?  mutations - any known ALS gene mutations library_prep - type of library preparation method used seq_platform - sequencing platform used for sequencing rin - RNA integrity number, 0-10 c9orf72_repeat_size - estimated C9orf72 repeat expansion size gPC1 - gPC5 - principal component of genetic ancestry from whole genome sequencing Remaining metadata columns are from Picard - see here: <a href="http://broadinstitute.github.io/picard/picard-metric-definitions.html#RnaSeqMetrics">http://broadinstitute.github.io/picard/picard-metric-definitions.html#RnaSeqMetrics</a>

opencc-by-4.0Apr 2022View details →

Raw RNAseq count data for figure 4 - by Van de Beek et al., 2022

This CSV file is generated by Van de Beek et al., (2022) and is part of "PRDM10 directs FLCN expression in a novel disorder overlapping with Birt-Hogg-Dubé syndrome and familial lipomatosis" to be published in Human Molecular Genetics.

opencc-by-3.0-usJul 2021View details →

GDC-PANCAN.htseq_counts and associated meta-data no longer available from gdc.xenahubs.net

The RNA-seq data and associated meta-data I used for my publications, downloaded from gdc.xenahubs.net but no longer available in this form (i.e. raw counts) from the website.

opencc-by-3.0-usSep 2023View details →

Data for 2D Signal Estimation for Sparse Distributed Target Photon Counting Data

Data used in publication of 2D Signal Estimation for Sparse Distributed Target Photon Counting Data Data provided consists of: raw and PTV processed MicroPulse DIAL (MPD) data (10.26023/MX0D-Z722-M406) simulated photon counting data and the processed results

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Harvest data including the shoot leaf area index, position in the canopy, and shoot and plant tissue area, count and mass for each shoot harvested at three levels in the canopy from 19 1m x 1m plots near LTER Shrub plots, Toolik Field Station, AK 2012.

Leaf and plant tissue area and mass from shoots harvested from 19 1m x 1m point frame plots near Toolik Field Station, AK during the summer of 2012. Six shoots were harvested from each plot, two from each canopy layer: upper, middle, and low. Each shoot came from a different plant, and the species selected was based on the species dominant in that canopy layer. The leaf area and mass were used to correct A/Ci and light response curves taken on each shoot [data published separately]. At the time of collection, the location relative to the point frame, height, and leaf area index (LAI) of each shoot was measured; those data are included here.

openOpenDec 2015View details →

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Snowshoe hare pellet count data in Bonanza Creek Experimental Forest

Snowshoe hares, Lepus americanus, are a 'keystone' prey species in northern boreal forests and experience population fluctuations of 8-11-years. Despite intense responses of both vegetation and predators to changes in hare densities, landscape-scale comparisons of hare populations in Alaska have been limited to qualitative descriptions. We conducted capture-recapture studies of snowshoe hares at 5 locales in the Tanana valley, from Tok in the east to Clear in the west from 1999 to 2002. Snowshoe hare densities were highest in 1999 ( =6.36 ha-1, SE=0.63) and declined thereafter. We were unable to detect declines in apparent survival during declining densities in our study populations. Movement distances did not vary temporally and persistence of individuals through declining densities may be associated positively with body condition at the peak. The relationship of hare pellets and hare densities was weak and limits the utility of this methodology for estimating hare densities in Interior Alaska.

openOpenApr 2003View details →

opencc-by-4.0May 2024View details →

Code and supplementary plots for "Flexible distributed lag models for count data using mgcv"

R code and supplementary plots accompanying the paper: "Flexible distributed lag models for count data using mgcv".

dryad40/100

Context-dependent multimodal behaviour in a coral reef fish: Stage 1 & 2 total duration and count data in behaviour trials

Animals are expected to respond flexibly to changing circumstances, with multimodal signalling providing potential plasticity in social interactions. Whilst numerous studies have documented context-dependent behavioural trade-offs in terrestrial species, far less work has considered such decision-making in fish, especially in natural conditions. Coral reef ecosystems host 25% of all known marine species, making them hotbeds of competition and predation. We conducted experiments with wild Ambon damselfish (Pomacentrus amboinensis) to investigate context-dependent responses to a conspecific intruder; specifically, how nest defence is influenced by an elevated predation risk. We found that nest-defending male Ambon damselfish responded aggressively to a conspecific intruder, spending less time sheltering and more time interacting, as well as signalling both visually and acoustically. In the presence of a model predator compared to a model herbivore, males spent less time interacting with the intruder, with a tendency towards reduced investment in visual displays compensated for by an increase in acoustic signalling instead. We therefore provide ecologically valid evidence that the context experienced by an individual can affect its behavioural responses and multimodal displays towards conspecific threats.

opencc-zeroMar 2024View details →

opencc-by-4.0Jan 2022View details →

Extra Testing Data for paper "OC_Finder: A deep learning-based software for osteoclast segmentation, classification, and counting"

<pre>Here we have 9 datasets we used to validate OC_Finder's performance on various imaging settings. The 9 datasets are inside the folder named "9 datasets for validation experiment". Each dataset is composed of image files and csv files for the coordination of osteoclasts and non-osteoclasts that were manually labelled by human examiner. csv files ending "_posi" has coordination of osteoclasts and "_nega" has coordination of non-osteoclasts. Images in dataset #4, #5, #6, #7, #8, and #9 were resized so the scale of the images matched to the OC_Finder's training dataset. Images in original size before resizing are also provided in "Original images before resizing". Detailed capture setting and resizing information of images in each dataset can be found in "capture setting.xlsx". The number of images in each dataset are as following: #1: 18 #2: 18 #3: 18 #4: 36 #5: 36 #6: 36 #7: 16 #8: 16 #9: 16</pre>

opencc-by-4.0Oct 2020View details →

Pollen morphometric data and phytolith counts and frequencies of native grasses of the Falkland Islands

Groff et al. phytolith count freq.csv is a dataset of the raw counts and cumulative frequencies of phytolith shape/texture classifications for nine native grass species from the Falkland Islands. Grass species include xyz. and 42 phytoliths were classified by counting at least 300 phytoliths.  Groff et al. pollen morphometrics.csv is a dataset of the raw measurements of pollen grains from eight native grass species from the Falkland Islands. Measurements (in µm) include the polar axis, equatorial axis, annulus diameter, pore diameter (col B), annulus diameter (col C), polar axis (col D), equatorial axis (col E), and the respective transformed data (cols F-I) and the six possible ratios of measurements (cols J-O).