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376 results for “Causality”
Data from: Population structure of Venturia inaequalis, a causal agent of apple scab, in response to heterogeneous apple tree cultivation
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Data for: Estimating causal effects with machine learning: A guide for ecologists
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Causal effect of familial short stature on three quantitative traits in Taiwan
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Data from: Causal link between insulin-like growth factor 1 and growth in nestlings of a wild passerine bird
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Code and dataset for neural dynamics of causal inference in the macaque frontoparietal circuit
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Data from: Population typing of the causal agent of cassava bacterial blight in the Eastern Plains of Colombia using two types of molecular markers
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Datasets for "The causal-noncausal alternation in the Northern Tungusic languages of Russia".
<p>These are the datasets used in the paper: Natalia Aralova & Brigitte Pakendorf. 2022. The causal-noncausal alternation in the Northern Tungusic languages of Russia. In Andreas Hölzl & Thomas E. Payne (eds.), Tungusic languages: Past and present, 21–62. Berlin: Language Science Press.</p> <p>For more details, see the ReadMe file.</p>
causal knowledge rules
<p>The rules we learned from our rule learning framework.</p> <p>It can also be seen as a causal knowledge graph.</p>
Gene validation and remodelling using proteogenomics of Phytophthora cinnamomi, the causal agent of Dieback
<p>This spectral data is in support for the manuscript 'Gene validation and remodelling using proteogenomics of Phytophthora cinnamomi, the causal agent of Dieback'. This data was used to detect errors in the draft genome and curate previously undescribed genes in the <em>Phytophthora cinnamomi</em> genome. </p>
Alterations in gut microbiota do not play a causal role in diet-independent weight gain caused by ovariectomy
<p>These files are associated with the following publication:<a href="https://doi.org/10.1210/jendso/bvaa173">https://doi.org/10.1210/jendso/bvaa173</a></p> <p>And the sequence data are available at the European Nucleotide Archive: PRJEB40801</p> <p>This link contains the metadata, sequences reads, and analysis files used in the study "Alterations in gut microbiota do not play a causal role in diet-independent weight gain caused by ovariectomy."</p> <p>Alpha_diversity files:<br> File: AlphaDiversity_analysis_sham_ovex<br> Description: R statistical analysis file for Faith's Phylogenetic Diversity (Faith's PD) and Observed<br> Sequence Variant (SV) alpha diversity metrics<br> File: faith_pd_sham_ovex<br> Description: QIIME2 output file for Faith's PD alpha diversity measurements for sham/ovex samples<br> File: obserevd_svs_sham_ovex<br> Description: QIIME2 output file for Observed SVs alpha diversity measurements for sham/ovex samples<br> </p> <p>Beta_diversity files:<br> File: BetaDiversity_analysis_sham_ovex<br> Description: R statistical analysis file for beta diversiy metrics<br> File: merged.sv.sham.ovex<br> Description: Combined SV table and taxa table for sham/ovex samples <br> File: sv.sham.ovex<br> Description: SV table for sham/ovex samples<br> File: table.sham.ovex.biom<br> Description: BIOM formated file for combined SV and taxa data. (For import into Phyloseq)<br> File: tax.sham.ovex<br> Description: Taxa table for sham/ovex samples<br> File: tree.nwk<br> Description: Phylogentic tree for sham/ovex data (For import into Phyloseq)<br> <br> DeSeq2 Analysis files:<br> File: merged.sv.sham.ovex.trimmed<br> Description: Combined SV table and taxa table for sham/ovex samples. SVs found in 4 samples or less removed. <br> File: sv.table.sham.ovex.trimmed <br> Description: SV table for sham/ovex samples. SVs found in 4 samples or less removed.<br> File: sham.ovex.trimmed.biom<br> Description: BIOM formated file for combined SV and taxa data. SVs found in 4 samples or less removed.(For import into Phyloseq)<br> File: tax.sham.ovex.trimmed<br> Description: Taxa table for sham/ovex samples. SVs found in 4 samples or less removed.<br> File: tree.trimmed.nwk<br> Description: Phylogentic tree for sham/ovex data. SVs found in 4 samples or less removed. (For import into Phyloseq)<br> File: Phyloseq.DeSeq2.Ovex.Sham<br> Description: Log2 Fold change analysis (relative species abundance) done in DESeq2 for time points 1-5.<br> File: Phyloseq.DeSeq2.Ovex.Sham.week3<br> Description: Log2 Fold change analysis (relative species abundance) done in DESeq2 for time point 3.<br> File: Phyloseq.DeSeq2.Ovex.Sham.week4<br> Description: Log2 Fold change analysis (relative species abundance) done in DESeq2 for time point 4.<br> File: Phyloseq.DeSeq2.Ovex.Sham.week5<br> Description: Log2 Fold change analysis (relative species abundance) done in DESeq2 for time point 5.<br> <br> <br> Mapping_files including metadata (for use with sequences below):<br> File: ovex_mapping <br> Description: Mapping file - maps barcodes to samples<br> File: ovex_mapping_samples removed<br> Description: Mapping file - maps barcodes to reads. Two samples removed for low sequence count.<br> 1. Plate2 A08 806rcbc103 GCG AGC GAA GTA CCG GAC TAC HVG GGT WTC TAA T 8 870 (T2) Ovex F<br> 2. Plate2 C02 806rcbc121 GCA ATT AGG TAC CCG GAC TAC HVG GGT WTC TAA T 26 888 (T2) Co-Sham O<br> File: ovex_mapping_sham_ovex_samples removed<br> Description: Mapping file - maps barcodes to reads. Sham/ovex samples only. One sample removed for low sequence count.<br> 1. Plate2 A08 806rcbc103 GCG AGC GAA GTA CCG GAC TAC HVG GGT WTC TAA T 8 870 (T2) Ovex F<br> </p> <p>QIIME2 Script:</p> <p>File: QIIME2_sham_ovex<br> Description: This file includes the commands used in the QIIME2 pipeline.</p>
Genetic overlap and causal inferences between kidney function and cerebrovascular disease
<p><u>Objective:</u> Leveraging large-scale genetic data, we aimed to identify shared pathogenic mechanisms and causal relationships between impaired kidney function and cerebrovascular disease phenotypes.</p> <p><u>Methods:</u> We used summary statistics from genome-wide association studies (GWAS) of kidney function traits (<a name="_Hlk536087805">chronic kidney disease (CKD) diagnosis, estimated glomerular filtration rate (eGFR), and Urinary Albumin-to-Creatinine Ratio (UACR)</a>), and of cerebrovascular disease phenotypes: ischemic stroke and its subtypes, intracerebral hemorrhage (ICH), white matter hyperintensities (WMH) on brain MRI. We (i) tested the genetic overlap between them with polygenic risk scores (PRS), (ii) searched for common pleiotropic loci with pairwise GWAS analyses, and (iii) explored causal associations by employing two-sample Mendelian Randomization (MR).</p> <p><u>Results:</u> A PRS for lower eGFR was associated with higher large-artery stroke (LAS) risk (p=1x10<sup>-4</sup>). Multiple pleiotropic loci were identified between kidney function traits and cerebrovascular disease phenotypes, with 12q24 associated with eGFR and both LAS and small-vessel stroke (SVS), and 2q33 associated with UACR and both SVS and WMH. MR revealed associations of both lower eGFR (OR per 1-log decrement=2.10, 95%CI=1.38-3.21) and higher UACR (OR per 1-log increment=2.35, 95%CI=1.12-4.94) with a higher risk of LAS, as well as between higher UACR and higher risk of ICH.</p> <p><u>Conclusions:</u> Impaired kidney function, as assessed by decreased eGFR and increased UACR, may be causally involved in the pathogenesis of LAS. Increased UACR, previously proposed as a marker of systemic small vessel disease, is involved in ICH risk and shares a genetic risk factor at 2q33 with manifestations of cerebral small vessel disease.</p>
Comprehensive investigation of circulating biomarkers and their causal role in atherosclerosis-related risk factors and clinical events
<p><strong>Background</strong>: Circulating biomarkers have been previously associated with atherosclerosis-related risk factors, but the nature of these associations is incompletely understood.</p> <p><strong>Methods</strong>: We performed multivariable-adjusted regressions and 2-sample Mendelian randomization analyses to assess observational and causal associations of 27 circulating biomarkers with 7 cardiovascular traits in up to 451 933 participants of the UK Biobank.</p> <p><strong>Results</strong>: After multiple-testing correction (alpha=1.3Å~10−4), we found a total of 15, 9, 21, 22, 26, 24, and 26 biomarkers strongly associated with coronary artery disease, ischemic stroke, atrial fibrillation, type 2 diabetes, systolic blood pressure, body mass index, and waist-to-hip ratio; respectively. The Mendelian randomization analyses confirmed strong evidence of previously suggested causal associations for several glucose- and lipid-related biomarkers with type 2 diabetes and coronary artery disease. Particularly interesting findings included a protective role of IGF-1 (insulin-like growth factor 1) in systolic blood pressure, and the strong causal association of lipoprotein(a) in coronary artery disease development (β, −0.13; per SD change in exposure and outcome and odds ratio, 1.28; P=2.6Å~10−4 and P=7.4Å~10−35, respectively). In addition, our results indicated a causal role of increased ALT (alanine aminotransferase) in the development of type 2 diabetes and hypertension (odds ratio, 1.59 and β, 0.06, per SD change in exposure and outcome; P=4.8Å~10−11 and P=6.0Å~10−5). Our results suggest that it is unlikely that CRP (C-reactive protein) and vitamin D play causal roles of any meaningful magnitude in development of cardiometabolic disease.</p> <p><strong>Conclusions</strong>: We confirmed and extended known associations and reported several novel causal associations providing important insights about the cause of these diseases, which can help accelerate new prevention strategies.</p>
Data from: Direct and indirect causal effects of heterozygosity on fitness-related traits in Alpine ibex
Heterozygosity–fitness correlations (HFCs) are a useful tool to investigate the effects of inbreeding in wild populations, but are not informative in distinguishing between direct and indirect effects of heterozygosity on fitness-related traits. We tested HFCs in male Alpine ibex (Capra ibex) in a free-ranging population (which suffered a severe bottleneck at the end of the eighteenth century) and used confirmatory path analysis to disentangle the causal relationships between heterozygosity and fitness-related traits. We tested HFCs in 149 male individuals born between 1985 and 2009. We found that standardized multi-locus heterozygosity (MLH), calculated from 37 microsatellite loci, was related to body mass and horn growth, which are known to be important fitness-related traits, and to faecal egg counts (FECs) of nematode eggs, a proxy of parasite resistance. Then, using confirmatory path analysis, we were able to show that the effect of MLH on horn growth was not direct but mediated by body mass and FEC. HFCs do not necessarily imply direct genetic effects on fitness-related traits, which instead can be mediated by other traits in complex and unexpected ways.
Data from: Causal reasoning in rats' behaviour systems
Conceiving of stimuli and responses as causes and effects, and assuming that rats acquire representational models of causal relations from Pavlovian procedures, previous work by Causal Model Theory proponents attempted to train rat subjects to represent Light as a cause of both Tone and food. By these assumptions, with formal help from Bayesian Networks, self-production of the Tone should reduce expectation of alternative causes, including Light, and their effects, including food. Reduced feeder-directed responding to the Tone when self-produced has been taken as evidence for a general causal reasoning capacity among rats involving mental maps of causal relations. Critics have rejoined that response competition can explain these effects. The present research replicates the key effect, but uses continuous and finer-grained measurement of a broader range of behaviours. Behaviours not recorded in previous studies contradict both prior explanations. Even results cited in support of these explanations, when measured in finer detail and continuously over longer periods, show patterns not expected by either view, but supportive of a specific-process approach with attention to motivational factors. Still, the abstract prediction from Bayesian Networks holds, providing a potentially complementary normative analysis. Behaviour systems theory provides firmer framing for such theories than representational-map alternatives.
Data from: De novo genome assembly of Geosmithia morbida, the causal agent of thousand cankers disease
Geosmithia morbida is a filamentous ascomycete that causes thousand cankers disease in the eastern black walnut tree. This pathogen is commonly found in the western U.S.; however, recently the disease was also detected in several eastern states where the black walnut lumber industry is concentrated. G. morbida is one of two known phytopathogens within the genus Geosmithia, and it is vectored into the host tree via the walnut twig beetle. We present the first de novo draft genome of G. morbida. It is 26.5 Mbp in length and contains less than 1% repetitive elements. The genome possesses an estimated 6,273 genes, 277 of which are predicted to encode proteins with unknown functions. Approximately 31.5% of the proteins in G. morbida are homologous to proteins involved in pathogenicity, and 5.6% of the proteins contain signal peptides that indicate these proteins are secreted. Several studies have investigated the evolution of pathogenicity in pathogens of agricultural crops; forest fungal pathogens are often neglected because research efforts are focused on food crops. G. morbida is one of the few tree phytopathogens to be sequenced, assembled and annotated. The first draft genome of G. morbida serves as a valuable tool for comprehending the underlying molecular and evolutionary mechanisms behind pathogenesis within the Geosmithia genus.
Causality of 486 human blood metabolites on gastric cancer: a two-sample Mendelian randomization study
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CHANCE: Causal hazard analysis for natural clinical experiments of therapies in uncommon diseases
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LATEst: Efficient computation of hazard ratios and identification of causal relationships using 'natural experiments' in medical informatics databases
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Causality analysis, path analyses and models between Chlorophyll a and environmental factors
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The causal links between gut microbiota and diabetic nephropathy: A Mendelian randomization study. Supplementary material
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ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.