cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18710/vm0wkq/vhujkb
title: Chromosome 1.csv

description: Contents: Gene (name of gene), 
 Gene ID (Ensemble ID of gene)
 Causal Estimate Least Squares (estimate of the causal effect of the gene on CAD using the least squares estimator), 
 Causal Estimate GMM (estimate of the causal effect of the gene on CAD using the Generalized method of moments estimator),
 se Least Squares/GMM (standard error of the least squares estimator and the GMM estimator, because the functional form is same, the standard error is same for both estimators),
 p-value GMM (p-value of the GMM estimator), 
 p-value Least Squares (p-value of the least squares estimator),
 Causal Estimate MVIVW (estimate of the causal effect of the gene on CAD using multivariable Mendelian randomization via the inverse-variance method using the Mendelian Randomization package), 
 se MVIVW (standard error of the estimate for multivariable Mendelian randomization via the inverse-variance method using the Mendelian Randomization package),
 p-value MVIVW (p-value of the estimate for multivariable Mendelian randomization via the inverse-variance method using the Mendelian Randomization package), 
 Causal effect MR (causal effect using univariate Mendelian Randomization), 
 F_stat (conditional F-statistic calculated using the Mendelian Randomization package), 
 Q_stat (cochran's Q-statistic calculated using the Mendelian Randomization package), 
 Q_pval (p-value of the cochran's Q-statistic calculated using the Mendelian Randomization package), 
 lead SNP (the SNP with the lowest p-value in the GWAS summary data for the given locus, hence the most significant SNP), 
 position (position in base pairs of the lead SNP), 
 chromosome (chromosome of the lead SNP), 
 tissue (name of the tissue from where the expression levels of genes are considered in the MVMR causal analysis), 
 No of SNPs (number of SNPs in the MVMR causal analysis), 
 study (GWAS study ebi-a-GCST003116), 
 determinant of LD matrix (the determinant of the Linkage disequilibrium matrix of the SNPs considered in the MVMR causal analysis), 
 determinant of instruments strength matrix (the determinant of the covariance matrix of the instruments and the genes for the SNPs considered in the MVMR causal analysis), 
 LD threshold (maximum allowed LD between SNPs considered as instruments for the causal MVMR analysis).
 
 Purpose: Collection of all results in the MVMR analysis
DOI: 10.18710/wko9qr/1bnn4f
title: 00_ReadMe.txt
DOI: 10.18710/ycq5hc/idce1h
title: Data_Protection_Impact_Assessment_TROLLing_Maouene_2024.pdf

description: Data protection Impact assessment
DOI: 10.18710/e9y4mu/ilo0m4
title: Euro_all_noindel_nodik_noTF_miss20_nomono_biallelic_maf0.05_LDpruned.vcf

description: dataset2
DOI: 10.18710/rxiuhf/bcicaz
title: 03_Uniaxial_compression_B02_5.2-5.3_CL.txt
DOI: 10.18710/rxiuhf/ho4zr9
title: 03_Uniaxial_compression_B02_3.7-3.8_CL.txt
DOI: 10.18710/ugnife/typn4f
title: PSGO_22.csv
DOI: 10.18710/1jhd7a/lwiihm
title: 00_README.txt

description: Descriptive readme file
DOI: 10.18710/bzog3s/ds7chd
title: scHSC_2_S3_1.fq.gz
DOI: 10.18710/etwncu/jw2hgu
title: POPC-10mPs-RPDLF.dx
DOI: 10.18710/gziuzl/l13b0f
title: ECOSENS_LF22_6_pf.txt
DOI: 10.18710/gziuzl/za0msb
title: ECOSENS_HF22_F2_ocean_irradiance.txt
DOI: 10.18710/j1k5xq/dk009i
title: 20240323_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/e4moht
title: 20240219_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/gg36r5
title: 20240207_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/hcjegf
title: 20240130_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/lgcmcs
title: 20240131_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/pvjrng
title: 20240305_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/reu4xj
title: 20240505_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/s4udys
title: 20240206_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/s9mqth
title: 20240502_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/ttiyny
title: 20240204_HOP_REDOBS_gps.txt
DOI: 10.18710/j1k5xq/ulzdjk
title: 20240218_HOP_REDOBS_gps.txt
DOI: 10.18710/l0vpw7/6zdaul
title: SBL245_A_Subt2__23__15-50-40-379.txt
DOI: 10.18710/l0vpw7/e8los7
title: SBL220_Subt2__26__18-25-59-020.txt
DOI: 10.18710/l0vpw7/u24clt
title: SBL100_Subt2__8__10-27-26-895.txt
DOI: 10.18710/l0vpw7/ud2lyv
title: SBL151_A_Subt8__7__17-48-35-495.txt
DOI: 10.18710/l0vpw7/vk0jua
title: SBL136_Subt2__13__14-16-33-423.txt
DOI: 10.18710/n1fi7e/3dug8j
title: 20240614_NYA_REDOBS_glo.txt
DOI: 10.18710/n1fi7e/97gpq8
title: 20240418_NYA_REDOBS_glo.txt
DOI: 10.18710/n4n1p4/o7fpck
title: 02_PSD_s3_m1_US.txt
DOI: 10.18710/qxqgwb/326fns
title: 20240428_NYA_REDTEC_gal.txt
DOI: 10.18710/qxqgwb/fhg1cu
title: 20240309_NYA_REDTEC_gal.txt
DOI: 10.18710/qxqgwb/fxzexv
title: 20240301_NYA_REDTEC_gps.txt
DOI: 10.18710/qxqgwb/h8mbu6
title: 20240225_NYA_REDTEC_gps.txt
DOI: 10.18710/qxqgwb/lgfi6g
title: 20240407_NYA_REDTEC_gal.txt
DOI: 10.18710/qxqgwb/nhwurd
title: 20240630_NYA_REDTEC_glo.txt
DOI: 10.18710/qxqgwb/qb7fzi
title: 20240526_NYA_REDTEC_glo.txt
DOI: 10.18710/qxqgwb/ty2ktj
title: 20240115_NYA_REDTEC_glo.txt
DOI: 10.18710/qxqgwb/udk0wd
title: 20240311_NYA_REDTEC_glo.txt
DOI: 10.18710/rxiuhf/eqfcr0
title: 03_Uniaxial_compression_B02_6.0-6.1_CL.txt
DOI: 10.18710/rxiuhf/rl1dtd
title: 03_Uniaxial_compression_B02_6.3-6.4_CL.txt
DOI: 10.18710/ugnife/6wxx0y
title: PSG_20.csv
DOI: 10.18710/ugnife/7xhwef
title: PSG_25.csv
DOI: 10.18710/ugnife/kkiwwg
title: PSGO_11.csv
DOI: 10.18710/vp5dmu/bmssee
title: participant13.csv

description: Actigraph acceleration data
DOI: 10.18710/ybpbsk/btnqm6
title: School_meals_in_Norway_2024.xlsx

description: Dataset in Excel-format
DOI: 10.18710/pwuqbp/04kcyo
title: 01_Bonde_EcolEvol_2024_data.txt
DOI: 10.18710/bzog3s/3icekw
title: scHSC_4_S1_2.fq.gz
DOI: 10.18710/bzog3s/e5mfnm
title: scHSC_4_C3_2.fq.gz
DOI: 10.18710/bzog3s/mqs1yt
title: scHSC_1_ST2_1.fq.gz
DOI: 10.18710/bzog3s/tofap4
title: scHSC_1_ST1_2.fq.gz
DOI: 10.18710/bzog3s/uhou6c
title: scHSC_1_T1_2.fq.gz
DOI: 10.18710/bzog3s/xztwaz
title: scHSC_1_T2_1.fq.gz
DOI: 10.18710/etwncu/2uetg3
title: POPC-15mPs-PSTATIC.dx
DOI: 10.18710/etwncu/aqrhvu
title: POPC-10mPs-H.dx
DOI: 10.18710/etwncu/juku04
title: POPC-10mPs-PSTATIC.dx
DOI: 10.18710/hmf7ee/nuelru
title: 2SN-A-C-02_TS-data.csv
DOI: 10.18710/j1k5xq/2ivmud
title: 20240403_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/5i4ey5
title: 20240506_HOP_REDOBS_gps.txt
DOI: 10.18710/j1k5xq/92os2r
title: 20240304_HOP_REDOBS_gps.txt
DOI: 10.18710/j1k5xq/gr66du
title: 20240123_HOP_REDOBS_gps.txt
DOI: 10.18710/j1k5xq/hice8z
title: 20240302_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/mxmyfb
title: 20240118_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/nykrze
title: 20240602_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/oopeie
title: 20240511_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/pllytu
title: 20240516_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/shovii
title: 20240406_HOP_REDOBS_gps.txt
DOI: 10.18710/j1k5xq/tu8qyd
title: 20240421_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/vslwpe
title: 20240404_HOP_REDOBS_gal.txt
DOI: 10.18710/n1fi7e/01j1qe
title: 20240529_NYA_REDOBS_glo.txt
DOI: 10.18710/n1fi7e/4uw1sw
title: 20240615_NYA_REDOBS_gps.txt
DOI: 10.18710/n1fi7e/7qa290
title: 20240604_NYA_REDOBS_glo.txt
DOI: 10.18710/n1fi7e/9w9j9g
title: 20240512_NYA_REDOBS_gal.txt
DOI: 10.18710/n1fi7e/e6kllk
title: 20240523_NYA_REDOBS_gps.txt
DOI: 10.18710/n1fi7e/f4piuz
title: 20240514_NYA_REDOBS_gps.txt
DOI: 10.18710/n1fi7e/kzykut
title: 20240630_NYA_REDOBS_glo.txt
DOI: 10.18710/n1fi7e/ljmkgw
title: 20240604_NYA_REDOBS_gps.txt
DOI: 10.18710/n1fi7e/lmzi4r
title: 20240601_NYA_REDOBS_glo.txt
DOI: 10.18710/n1fi7e/msqnci
title: 20240622_NYA_REDOBS_glo.txt
DOI: 10.18710/n1fi7e/ofrhuy
title: 20240429_NYA_REDOBS_gal.txt
DOI: 10.18710/n1fi7e/qcbykt
title: 20240629_NYA_REDOBS_glo.txt
DOI: 10.18710/n4n1p4/cdw6pa
title: 02_PSD_s3_m3_US.txt
DOI: 10.18710/n4n1p4/ldvjwz
title: 07_3ph_CO3.txt
DOI: 10.18710/n4n1p4/u5i9ir
title: 02_PSD_s3_m4_noUS.txt
DOI: 10.18710/n4n1p4/wjj2qw
title: 07_3ph_OH.txt
DOI: 10.18710/n4n1p4/wllnn5
title: 07_3ph_HCO3.txt
DOI: 10.18710/qxqgwb/3l2h5i
title: 20240626_NYA_REDTEC_gps.txt
DOI: 10.18710/qxqgwb/5fyflw
title: 20240424_NYA_REDTEC_glo.txt
DOI: 10.18710/qxqgwb/6xi9sr
title: 20240621_NYA_REDTEC_gps.txt
DOI: 10.18710/qxqgwb/89ycbo
title: 20240516_NYA_REDTEC_gal.txt
DOI: 10.18710/qxqgwb/auc0f2
title: 20240503_NYA_REDTEC_gal.txt
DOI: 10.18710/qxqgwb/ccthny
title: 20240613_NYA_REDTEC_gps.txt
DOI: 10.18710/qxqgwb/jmsxep
title: 20240425_NYA_REDTEC_glo.txt
DOI: 10.18710/qxqgwb/jw6zly
title: 20240512_NYA_REDTEC_glo.txt
DOI: 10.18710/qxqgwb/vmnd6y
title: 20240406_NYA_REDTEC_glo.txt
DOI: 10.18710/wrgqam/tmbn0t
title: 9_DIC_Data_EP350-1.zip

description: DIC Data EP350-1
DOI: 10.18710/zljn9x
title: Replication Data for: Trapdoor viscous remanent magnetization

description: Jupyter notebooks to generate several Figures of "Trapdoor viscous remanent magnetization".
The programs and functions in the notebooks can be used to vary model parameters and generate your own arbitrary trapdoor VRM model runs.
DOI: 10.15468/dl.ccqn4e
title: Occurrence Download

description: A dataset containing 74 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Eudrilus eugeniae",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 10000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 74 records from 12 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0054621-251120083545085/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18710/8lc9ea
title: Celiac Disease GWAS summary statistics

description: Previous studies have uncovered genetic loci associated with celiac disease (CeD) within both the human leukocyte antigen (HLA) and non-HLA regions. However, half of the heritability remains unexplained. This study aimed to identify novel loci associated with CeD in a general adult population screened for the disease, mitigating the likely selection bias observed in previous case-control studies. The study utilized data from the fourth Trøndelag Health Study (HUNT4) in Norway, where 52,358 adults were screened for CeD using serology, identifying 465 previously undiagnosed biopsy-confirmed cases. Additionally, 377 previously diagnosed cases were identified through hospital journal searches and registry data. Genotyping of 373,185 single nucleotide polymorphisms was performed on all participant using four Illumina HumanCoreExome arrays. Imputation, using the Haplotype Reference Consortium panel, resulted in approximately 24.9 million variants, post quality control. A genome-wide association study was performed using SAIGE, and functional mapping and pathway enrichment analysis was conducted using FUMA. All except one of the 42 known autosomal loci were present in the data, of which seven reached the suggestive significance threshold (P ≤ 5 × 10−6). Thirteen independent novel associations were observed (P ≤ 5× 10−8), with the 5p15.33 locus showing the highest potential for a true association with CeD, warranting further studies to validate the findings. Notably, the IRX1 gene, located close to the 5p15.33 locus has also been associated with rheumatoid arthritis, suggesting a new shared autoimmune locus.
description: R, 4.1.2
description: Plink, 1.9
description: The Trøndelag Health Study (HUNT) has invited individuals aged 13-100 years to four surveys between 1984 and 2019. Comprehensive data from more than 140,000 individuals having participated at least once and biological material from 78,000 individual are collected. The data are stored in HUNT databank and biological material in HUNT biobank. HUNT Research Centre has permission from the Norwegian Data Inspectorate to store and handle these data. The key identification in the database is the personal identification number given to all Norwegians at birth or immigration, whilst de-identified data are sent to researchers upon approval of a research protocol by the Regional Ethical Committee and HUNT Research Centre. To protect participants’ privacy, HUNT Research Centre aims to limit storage of data outside HUNT databank and cannot deposit data in open repositories. HUNT databank has precise information on all data exported to different projects and are able to reproduce these on request. There are no restrictions regarding data export given approval of applications to HUNT Research Centre. For more information see: http://www.ntnu.edu/hunt/data
DOI: 10.18710/digqgq/b5l5yv
title: miR-143.zip
DOI: 10.18710/digqgq/wlkmyd
title: miR-145.zip
DOI: 10.18710/fpfu7g/ode1v3
title: Amalie-ettergitt.pdf

description: Scanned content of folder (Handwritten Norwegian text)
DOI: 10.18710/gxmsuh/hrumck
title: 04c_ccar_annotation_v5_swissprot_wGO_outfmt6.txt

description: This is the blast output.
DOI: 10.18710/gxmsuh/tglmse
title: 04a_ccar_annotation_v5_kegg.txt

description: This file contains the output of the search for KEGG ortholog (KO) matches in the KEGG Ortholog database, found using the tool BlastKOALA (v. 3; https://www.kegg.jp/blastkoala/).
DOI: 10.18710/gxmsuh/zdeihr
title: 03b_ccar_annotation_v5_transcripts_fasta.txt

description: This is the predicted transcript sequences from the genome (262 scaffolds) in fasta format. The sequences were extracted using the AGAT script "agat_sp_extract_sequences.pl" in Anaconda3 (2022.10 on Saga).
DOI: 10.18710/n1fi7e/1clwpk
title: 20240515_NYA_REDOBS_gal.txt
DOI: 10.18710/n1fi7e/bsed9b
title: 20240529_NYA_REDOBS_gps.txt
DOI: 10.18710/n1fi7e/mmwrcn
title: 20240506_NYA_REDOBS_gps.txt
DOI: 10.18710/n1fi7e/wflg5n
title: 20240518_NYA_REDOBS_gal.txt
DOI: 10.18710/n1fi7e/wzsskz
title: 20240620_NYA_REDOBS_gal.txt
DOI: 10.18710/pn7dza/x8zwdf
title: re2500we10_10.tar
DOI: 10.18710/qmmer5/3enmz6
title: 20221204_MeOH_LDPE_1.mzML
DOI: 10.18710/qmmer5/6z4pwg
title: 20221206_NEG_MeOH_HDPE_1.mzML
DOI: 10.18710/qmmer5/dvqizs
title: 20221206_NEG_MeOH_LDPE_1.mzML
DOI: 10.18710/qmmer5/gsw8ut
title: 20221204_H2O_PET_2.mzML
DOI: 10.18710/qmmer5/it20ju
title: 20221206_NEG_H2O_PET_1.mzML
DOI: 10.18710/qmmer5/ljmjyk
title: 20220125_POS_PB_MeOH.mzML

description: SPE recovery
DOI: 10.18710/qmmer5/m4sgmo
title: 20221206_NEG_EtOH_PET_1.mzML
DOI: 10.18710/qmmer5/oesnbb
title: 20221206_NEG_EtOH_PS_1.mzML
DOI: 10.18710/qmmer5/ouiwpd
title: 20221204_MeOH_PUR_1.mzML
DOI: 10.18710/qmmer5/tgsaid
title: 20220125_POS_LDPE_1_EtOH_beforeSPE.mzML

description: SPE recovery
DOI: 10.18710/qmmer5/yvztjn
title: 20221206_NEG_MeOH_PB4.mzML
DOI: 10.18710/qsgwsj/xcmbpn
title: 00_Holthuis_DataverseNO_README.txt

description: Readme file for all the data repository
DOI: 10.18710/uat043/rwz8w1
title: re1000weInf_02.tar
DOI: 10.18710/uat043/vcrcvx
title: re1000weInf_04.tar
DOI: 10.18710/xakjy6/ha7fvo
title: bpmn-B-1-on.png
DOI: 10.18710/xakjy6/ijyluw
title: sd-B-on.png
DOI: 10.18710/xakjy6/say4tx
title: cold-A-3.txt
DOI: 10.18710/ztqurh/wxm47j
title: 04_3Way_Data.csv
DOI: 10.18710/bsxna1/go6cg7
title: CAPTIV8_meta_frame_video.xlsx

description: Frame and Video metadat file containing image and video names, paths and text-descriptions/labels.
DOI: 10.18710/bsxna1/hf46g1
title: PillCam_calibration_data.zip

description: Colorchecker and checkerboard images/video for camera calibration
DOI: 10.18710/bsxna1/jqxybl
title: Frames_and_videos.zip

description: Folder containing images and videos
DOI: 10.18710/j1k5xq/azzc08
title: 20240504_HOP_REDOBS_gal.txt
DOI: 10.18710/j1k5xq/hqyxce
title: 20240425_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/nxtjyu
title: 20240420_HOP_REDOBS_gps.txt
DOI: 10.18710/j1k5xq/pvgtfl
title: 20240414_HOP_REDOBS_glo.txt
DOI: 10.18710/j1k5xq/y82y2c
title: 20240619_HOP_REDOBS_gps.txt
DOI: 10.18710/kcqerf
title: Arctic ship traffic air pollutant emissions inventory 2013-2022

description: Monthly gridded ship-associated emissions (carbon monoxide (CO), sulfur oxides (SOx), nitrogen oxides (NOx), and volatile organic compounds (VOC)) in the Barents and Kara Sea region from 2013 - 2022. Data is collected from the Protection of the Arctic Marine Environment's (PAME) Arctic Ship Traffic Database (ASTD) and aggregated to monthly sums in a 0.1x0.1 longitude latitude grid.

Emissions are given in total emissions (tonnes) per month (unit: tonnes/month), where the filename indicate year and month: ASTD_shipping_emissions_yyyy_mm.

NB: Each file contains 12 time layers, which requires the user to refer to correct timestamp to view data (i. e. ASTD_shipping_emissions_2015_01, data is found in time=1. ASTD_shipping_emissions_2021_07, data is found in time=7).
description: Python, 3.8
DOI: 10.18710/l0vpw7/2gvpk8
title: SBL094_Subt2__6__10-19-50-891.txt
DOI: 10.18710/n1fi7e/hlutnz
title: 20240602_NYA_REDOBS_glo.txt
DOI: 10.18710/n1fi7e/hsplb4
title: 20240612_NYA_REDOBS_gal.txt
DOI: 10.18710/n4n1p4/ryxryp
title: 02_PSD_s1_m2_noUS.txt
DOI: 10.18710/qxqgwb/7u05o4
title: 20240509_NYA_REDTEC_glo.txt
DOI: 10.18710/qxqgwb/dmrupj
title: 20240615_NYA_REDTEC_glo.txt
DOI: 10.18710/qxqgwb/dpmd8k
title: 20240409_NYA_REDTEC_gps.txt
DOI: 10.18710/qxqgwb/ejnjw4
title: 20240626_NYA_REDTEC_gal.txt
DOI: 10.18710/qxqgwb/ffm9lc
title: 20240622_NYA_REDTEC_gal.txt
DOI: 10.18710/vm0wkq/ntcvdy
title: Chromosome 21.csv

description: Contents: Gene (name of gene), 
 Gene ID (Ensemble ID of gene)
 Causal Estimate Least Squares (estimate of the causal effect of the gene on CAD using the least squares estimator), 
 Causal Estimate GMM (estimate of the causal effect of the gene on CAD using the Generalized method of moments estimator),
 se Least Squares/GMM (standard error of the least squares estimator and the GMM estimator, because the functional form is same, the standard error is same for both estimators),
 p-value GMM (p-value of the GMM estimator), 
 p-value Least Squares (p-value of the least squares estimator),
 Causal Estimate MVIVW (estimate of the causal effect of the gene on CAD using multivariable Mendelian randomization via the inverse-variance method using the Mendelian Randomization package), 
 se MVIVW (standard error of the estimate for multivariable Mendelian randomization via the inverse-variance method using the Mendelian Randomization package),
 p-value MVIVW (p-value of the estimate for multivariable Mendelian randomization via the inverse-variance method using the Mendelian Randomization package), 
 Causal effect MR (causal effect using univariate Mendelian Randomization), 
 F_stat (conditional F-statistic calculated using the Mendelian Randomization package), 
 Q_stat (cochran's Q-statistic calculated using the Mendelian Randomization package), 
 Q_pval (p-value of the cochran's Q-statistic calculated using the Mendelian Randomization package), 
 lead SNP (the SNP with the lowest p-value in the GWAS summary data for the given locus, hence the most significant SNP), 
 position (position in base pairs of the lead SNP), 
 chromosome (chromosome of the lead SNP), 
 tissue (name of the tissue from where the expression levels of genes are considered in the MVMR causal analysis), 
 No of SNPs (number of SNPs in the MVMR causal analysis), 
 study (GWAS study ebi-a-GCST003116), 
 determinant of LD matrix (the determinant of the Linkage disequilibrium matrix of the SNPs considered in the MVMR causal analysis), 
 determinant of instruments strength matrix (the determinant of the covariance matrix of the instruments and the genes for the SNPs considered in the MVMR causal analysis), 
 LD threshold (maximum allowed LD between SNPs considered as instruments for the causal MVMR analysis).
 
 Purpose: Collection of all results in the MVMR analysis
DOI: 10.18710/vm0wkq/qbyaww
title: Chromosome 10.csv

description: Contents: Gene (name of gene), 
 Gene ID (Ensemble ID of gene)
 Causal Estimate Least Squares (estimate of the causal effect of the gene on CAD using the least squares estimator), 
 Causal Estimate GMM (estimate of the causal effect of the gene on CAD using the Generalized method of moments estimator),
 se Least Squares/GMM (standard error of the least squares estimator and the GMM estimator, because the functional form is same, the standard error is same for both estimators),
 p-value GMM (p-value of the GMM estimator), 
 p-value Least Squares (p-value of the least squares estimator),
 Causal Estimate MVIVW (estimate of the causal effect of the gene on CAD using multivariable Mendelian randomization via the inverse-variance method using the Mendelian Randomization package), 
 se MVIVW (standard error of the estimate for multivariable Mendelian randomization via the inverse-variance method using the Mendelian Randomization package),
 p-value MVIVW (p-value of the estimate for multivariable Mendelian randomization via the inverse-variance method using the Mendelian Randomization package), 
 Causal effect MR (causal effect using univariate Mendelian Randomization), 
 F_stat (conditional F-statistic calculated using the Mendelian Randomization package), 
 Q_stat (cochran's Q-statistic calculated using the Mendelian Randomization package), 
 Q_pval (p-value of the cochran's Q-statistic calculated using the Mendelian Randomization package), 
 lead SNP (the SNP with the lowest p-value in the GWAS summary data for the given locus, hence the most significant SNP), 
 position (position in base pairs of the lead SNP), 
 chromosome (chromosome of the lead SNP), 
 tissue (name of the tissue from where the expression levels of genes are considered in the MVMR causal analysis), 
 No of SNPs (number of SNPs in the MVMR causal analysis), 
 study (GWAS study ebi-a-GCST003116), 
 determinant of LD matrix (the determinant of the Linkage disequilibrium matrix of the SNPs considered in the MVMR causal analysis), 
 determinant of instruments strength matrix (the determinant of the covariance matrix of the instruments and the genes for the SNPs considered in the MVMR causal analysis), 
 LD threshold (maximum allowed LD between SNPs considered as instruments for the causal MVMR analysis).
 
 Purpose: Collection of all results in the MVMR analysis
DOI: 10.18710/wrgqam/yphb5r
title: 11_DIC_Data_EP350-3.zip

description: DIC data of EP350-3
DOI: 10.18710/yvecmk/qemetr
title: 00_README_file.txt
DOI: 10.18710/dqzkmx/kbmg3t
title: 1-seeds.csv

description: Accuracy tables for the dataset: Seeds.

Charytanowicz, M.; Niewczas, J.; Kulczycki, P.; Kowalski, P. and Lukasik, S. (2012). Seeds. UCI Machine Learning Repository. https://doi.org/10.24432/C5H30K. Licensed under CC BY 4.0.
DOI: 10.18710/j1k5xq/8y3fls
title: 20240508_HOP_REDOBS_gps.txt
DOI: 10.18710/l0vpw7/c3xmdm
title: SBL074_Subt4__4__14-32-15-888.txt
DOI: 10.18710/n1fi7e/hhvew3
title: 20240508_NYA_REDOBS_gps.txt
DOI: 10.18710/n1fi7e/ie1oyb
title: 20240422_NYA_REDOBS_gps.txt
DOI: 10.18710/n1fi7e/qgsucn
title: 20240407_NYA_REDOBS_gps.txt
DOI: 10.18710/n1fi7e/t4idur
title: 20240619_NYA_REDOBS_gal.txt
DOI: 10.18710/n4n1p4/cpe2j3
title: 06_ICPMS_upw_para_2.txt
DOI: 10.18710/n4n1p4/yxvsxi
title: 02_PSD_s2_m5_US.txt
DOI: 10.18710/n4n1p4/zufh0h
title: 04_EDS_1pH.tif
DOI: 10.18710/qxqgwb/dj6tra
title: 20240418_NYA_REDTEC_gps.txt
DOI: 10.18710/qxqgwb/icry7l
title: 20240614_NYA_REDTEC_gal.txt
DOI: 10.18710/qxqgwb/yrffrd
title: 20240620_NYA_REDTEC_gal.txt
DOI: 10.18710/dqzkmx/o7c6tw
title: 4-glass.csv

description: Accuracy tables for the dataset: Glass Identification.

German, B. (1987). Glass Identification. UCI Machine Learning Repository. https://doi.org/10.24432/C5WW2P. Licensed under CC BY 4.0.
DOI: 10.18710/j1k5xq/dsxpxy
title: 20240401_HOP_REDOBS_gal.txt
DOI: 10.18710/l0vpw7/ddtns5
title: SBL142_Subt4__11__15-03-22-398.txt
DOI: 10.18710/l0vpw7/ozvvkn
title: SBL275_A_Subt2__32__21-37-53-654.txt
DOI: 10.18710/l0vpw7/pkhyn7
title: SBL018_Subt4__117__16-42-45-095.txt
DOI: 10.18710/l0vpw7/pobfmk
title: SBL091_Subt2__4__10-06-12-402.txt
DOI: 10.18710/l0vpw7/u4716c
title: SBL227_A_Subt2__25__18-52-38-027.txt
DOI: 10.18710/l0vpw7/y3fdzu
title: SBL021_Subt4__70__13-34-23-781.txt
DOI: 10.18710/l0vpw7/ybkq3o
title: SBL181_A_Subt2__14__19-33-47-755.txt
DOI: 10.18710/n1fi7e/9wrotw
title: 20240910_NYA_REDOBS_glo.txt
DOI: 10.18710/n1fi7e/cdfff3
title: 20240528_NYA_REDOBS_gps.txt
DOI: 10.18710/n1fi7e/fyhaez
title: 20240429_NYA_REDOBS_gps.txt
DOI: 10.18710/n1fi7e/htbphd
title: 20240803_NYA_REDOBS_glo.txt