Genome wide association studies (GWAS) are hypothesis-free methods for identifing associations between genetic regions (loci) and traits (including diseases).
Resutls of different OMICS-level using LIFE Adult and LIFE Heart data are presented (Publications, Supplemental Data, & Summary Statistics).
LHA ID: 7WAD3R7GH9-5
Projects: Genetical Statistics and Systems Biology, LIFE Adult, LIFE Heart
Investigation position:
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Created: 16th May 2019 at 16:39
Last updated: 9th Sep 2020 at 12:15
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The LIFE-Heart study recruited 7,000 patients with suspected coronary heart disease, manifest heart disease or myocardial infarction. All patients received coronary angiography so that the vascular status in the heart is precisely known. In principle, this examination is not feasible in population-related studies. In addition, the patients were thoroughly examined with regard to the general vascular status and the health of the cardiovascular system. Extensive environmental factors were recorded. ...
Programme: LIFE Management Cluster
Public web page: http://life.uni-leipzig.de/
Start date: 1st Jan 2009
Organisms: Homo sapiens
Human Diseases: cardiovascular system disease
Goal of the Leipzig Research Center for Civilization Diseases (LIFE) is the investigation of civilization diseases like depression, diabetes, allergies or cardiovascular diseases. For this purpose we collect as much data as possible regarding health and living conditions of the population in Leipzig and provide these data for scientists of the University of Leipzig and other research institutions.
Programme: LIFE Management Cluster
Public web page: http://life.uni-leipzig.de/
Start date: 1st Jan 2009
This population-based study examined 10,000 participants randomly selected from the Leipzig population (2011 to 2014). A follow-up is to be carried out from 2017 - 2020. The study mainly included people aged between 40 and 79. All participants underwent a 6-hour study program and people over 60 years of age were invited two more times to in-depth study of cognition and depression and the brain (MRI, EEG). Extensive measurements of genome, metabolome and transcriptome are available. The LIFE-ADULT ...
Programme: LIFE Management Cluster
Public web page: http://life.uni-leipzig.de/en/adults/life_adult.html
Start date: 1st Jan 2009
Organisms: Homo sapiens
Human Diseases: mood disorder, dementia, coronary artery disease, obesity
The group is interested in omic-level studies including the genome, methylome, transcriptome, and metabolome of the general population as well as of various diseases including cardiovascular diseases, pneumonia, sepsis, obesity, and brain cancers. Additionally, we aim at transfering results of biomathematical model simulations into clinical practice e.g. by haematopoietic growth-factor opimization during cytotoxic chemotherapy and optimization of EPO applications in chronic kidney disease.
The ...
Programme: This Project is not associated with a Programme
Public web page: http://www.imise.uni-leipzig.de/en/Groups/GenStat/
Start date: 1st Jan 2013
Organisms: Homo sapiens
A meta-analysis of genome-wide associations for serum vaspin from six independent cohorts (N = 7446) was conducted. The data show that serum vaspin is strongly determined by genetic variants within vaspin.
This study belongs to the publication: https://doi.org/10.1002/oby.23882
Submitter: Katrin Horn
Investigation: OMICS Investigations
Resources: Summary Statistics
Study type: Genetic study
Snapshots: No snapshots
Submitter: Katrin Horn
Investigation: OMICS Investigations
Resources: Gene Expression data, LIFE-Adult EPIC data
Study type: Not specified
Snapshots: No snapshots
Summary statistics of Meta-GWAS results will be made available upon acceptance of our manuscript.
Submitter: Janne Pott
Investigation: OMICS Investigations
Resources: Summary Statistics
Study type: Genetic study
Snapshots: No snapshots
In our manuscript, we describe current procedures, tools, and results to create, compare and qualitatively assess the single-cell transcriptomes of the lung in three different species; human (Homo sapiens), hamster (Mesocricetus auratus), and mice (Mus musculus).
We make the analysis reproducible by publishing the R-based workflow on GitHub pulmonologists_interspecies_scRNA
.
Here in the LHA, we provide the required scRNA-Seq
...
Submitter: Holger Kirsten
Investigation: OMICS Investigations
Resources: scRNA-Seq expression data as RDS Seurat file
Study type: Cell study
Snapshots: No snapshots
Genome-wide Association Meta-Analyses of four steroid hormones (progesterone, 17-OH-progesterone, androstenedione, and aldosterone) and the ratio of testosterone to estradiol. Summary statistics of GWAMA results will be made available upon acceptance of our manuscript.
Submitter: Janne Pott
Investigation: OMICS Investigations
Resources: No Resources
Study type: Genetic study
Snapshots: No snapshots
Genome-wide Association Meta-Analyses of 32 phytosterol traits reflecting resorption, cholesterol synthesis and esterification in six studies with up to 9,758 subjects Summary statistics of GWAMA results will be made available upon acceptance of our manuscript.
Submitter: Janne Pott
Investigation: OMICS Investigations
Resources: Summary Statistics - Phytosterols
Study type: Genetic study
Snapshots: No snapshots
Submitter: Janne Pott
Investigation: OMICS Investigations
Resources: Summary Statistics
Study type: Genetic study
Snapshots: No snapshots
We analysed if measuring PWV in different segments of the body leads to association with different genetic variants, as well as different heritability and different genetic correlation with other biological traits. Furthermore we searched for shared genetic architecture concerning PWV, blood pressure (BP) and coronary artery disease (CAD) and examined the causal relationship between PWV and BP.
Submitter: Janne Pott
Investigation: OMICS Investigations
Resources: Summary Statistic for PWV GWAS
Study type: Genetic study
Snapshots: No snapshots
We defined six operationalizations of CPB considering plaques in common carotid arteries, carotid bulb, and internal carotid arteries (maximal plaque area, mean plaque area, sum of plaque areas at all six regions, maximal degree of stenosis, mean degree of stenosis, and sum of stenosis at all six regions). Link to publication (PMID, DOI), Supplemental Figures and Tables, and Summary Statistics of GWAS will be made available upon acceptance of our manuscript.
Submitter: Janne Pott
Investigation: OMICS Investigations
Resources: Summary Statistics
Study type: Genetic study
Snapshots: No snapshots
Supplement Data for Publication including Supplement Material & Results (eQTL annotation, Mendelian Randomization (MR), further significant loci), Figures (correlation plot of steroid hormones, scatter plot of genetic effect sizes, regional association plots, scatter plots of MR) and Tables (Correlations, GWAS summary statistics, interaction tests, MR results)
Submitter: René Hänsel
Investigation: OMICS Investigations
Resources: Summary Statistics, Supplement Data
Study type: Genetic study
Snapshots: No snapshots
Summary Statistics used in publication
Submitter: Katrin Horn
Resource type: Genome Wide Association
Technology type: Technology Type
Investigation: OMICS Investigations
Study: GWAMA vaspin
Human Diseases: No human diseases
Data files: Summary Statstics for vaspin ALL
Snapshots: No snapshots
Submitter: Katrin Horn
Resource type: Experimental Assay Type
Technology type: Technology Type
Investigation: OMICS Investigations
Human Diseases: No human diseases
Data files: LIFE-Adult EPIC Samples Sheet, LIFE-Adult EPIC data idat files
Snapshots: No snapshots
To provide data input and result from a scRNA-Seq integration workflow
Submitter: Holger Kirsten
Resource type: Experimental Assay Type
Technology type: Technology Type
Investigation: OMICS Investigations
Human Diseases: No human diseases
Data files: Input files used in scripts, scRNA-Seq expression-data as RDS Seurat file
Snapshots: No snapshots
Submitter: Andreas Kühnapfel
Biological problem addressed: Genome Scale
Investigation: OMICS Investigations
Study: GWAS Body Scanner Measures
Human Diseases: No human diseases
Models: No Models
Data files: BS Abbreviations, Summary Statistics for BS_3D_WAISTBAND, Summary Statistics for BS_3D_WAISTBAND_AVERAGE_..., Summary Statistics for BS_3D_WAISTBAND_B_HT, Summary Statistics for BS_3D_WAISTBAND_F_HT, Summary Statistics for BS_AC_BACK_WTH, Summary Statistics for BS_AC_BACK_WTH_AL, Summary Statistics for BS_ANKLE_GTH_AVERAGE, Summary Statistics for BS_ANKLE_HT, Summary Statistics for BS_ARM_LTH_AVERAGE, Summary Statistics for BS_ARM_LTH_T_NECK_AVERAGE, Summary Statistics for BS_ARM_LTH_T_NECK_B_AVERAGE, Summary Statistics for BS_BELLY_CIRC, Summary Statistics for BS_BELLY_CIRC_HT, Summary Statistics for BS_BMI, Summary Statistics for BS_BREAST_HT, Summary Statistics for BS_BUST_CHEST_GTH, Summary Statistics for BS_BUST_CHEST_GTH_HZ, Summary Statistics for BS_BUST_PT_AR_NECK, Summary Statistics for BS_BUST_PT_T_NECK_AVERAGE, Summary Statistics for BS_BUST_PT_WTH, Summary Statistics for BS_BUTTOCK_GTH, Summary Statistics for BS_BUTTOCK_HT, Summary Statistics for BS_CALF_GTH_AVERAGE, Summary Statistics for BS_CROTCH_HT, Summary Statistics for BS_CROTCH_LTH, Summary Statistics for BS_CROTCH_LTH_AT_WB, Summary Statistics for BS_CROTCH_LTH_AT_WB_A, Summary Statistics for BS_CROTCH_LTH_F, Summary Statistics for BS_CROTCH_LTH_R, Summary Statistics for BS_CR_SHOULDER, Summary Statistics for BS_CR_SHOULDER_O_NECK, Summary Statistics for BS_DEV_WB_FROM_WAIST_B, Summary Statistics for BS_DEV_WB_FROM_WAIST_F, Summary Statistics for BS_DEV_WB_FROM_WAIST_S, Summary Statistics for BS_DIST_AC_B_WTH_WAIST, Summary Statistics for BS_DIST_CROTCH_WAISTBAN, Summary Statistics for BS_DIST_NECK_KNEE, Summary Statistics for BS_DIST_NECK_T_HIP, Summary Statistics for BS_DIST_WAISTBAND_BUTT, Summary Statistics for BS_DIST_WAISTBAND_KNEE, Summary Statistics for BS_DIST_WAIST_KNEE, Summary Statistics for BS_ELBOW_GTH_AVERAGE, Summary Statistics for BS_FOREARM_GTH_AVERAGE, Summary Statistics for BS_FOREARM_LTH_AVERAGE, Summary Statistics for BS_HEAD_CIRC, Summary Statistics for BS_HEAD_HT, Summary Statistics for BS_HIGH_HIP_GTH, Summary Statistics for BS_HIGH_WAIST_GTH, Summary Statistics for BS_HIGH_WAIST_HT, Summary Statistics for BS_HIP_GTH, Summary Statistics for BS_HIP_HT, Summary Statistics for BS_HIP_THIGH_GTH, Summary Statistics for BS_HT, Summary Statistics for BS_HT_SHOULDER_BLADES, Summary Statistics for BS_INSEAM_AVERAGE, Summary Statistics for BS_IN_LEG_ANKLE_AVERAGE, Summary Statistics for BS_KNEE_GTH_AVERAGE, Summary Statistics for BS_KNEE_HT, Summary Statistics for BS_MAX_BELLY_CIRC, Summary Statistics for BS_MAX_BELLY_CIRC_HT, Summary Statistics for BS_MIDDLE_HIP, Summary Statistics for BS_MID_NECK_GTH, Summary Statistics for BS_MIN_LEG_GTH_AVERAGE, Summary Statistics for BS_NECK_AC_BACK_WTH_AL, Summary Statistics for BS_NECK_AT_BASE_GTH, Summary Statistics for BS_NECK_AVERAGE_T_WAIST_B, Summary Statistics for BS_NECK_DIAM, Summary Statistics for BS_NECK_F_T_WAIST, Summary Statistics for BS_NECK_F_T_WAIST_OV_BL, Summary Statistics for BS_NECK_HT, Summary Statistics for BS_NECK_R_WAIST_OV_BL, Summary Statistics for BS_NECK_WAIST_C_BACK, Summary Statistics for BS_SCAPULA_HT_2, Summary Statistics for BS_SIDESEAM_3D_WD_AVERAGE, Summary Statistics for BS_SIDESEAM_ANKLE_AVERAGE, Summary Statistics for BS_SIDESEAM_AVERAGE, Summary Statistics for BS_SIDESEAM_WAIST_AVERAGE, Summary Statistics for BS_THIGH_GTH_AVERAGE_HZ, Summary Statistics for BS_TORSO_WTH_WAIST, Summary Statistics for BS_TOT_TORSO_GTH, Summary Statistics for BS_UNDERBUST_CIRC_HZ, Summary Statistics for BS_UP_ARM_DIAM_AVERAGE, Summary Statistics for BS_UP_ARM_GTH_AVERAGE, Summary Statistics for BS_UP_ARM_LTH_AVERAGE, Summary Statistics for BS_WAISTBAND, Summary Statistics for BS_WAISTBAND_B_HT, Summary Statistics for BS_WAISTBAND_F_HT, Summary Statistics for BS_WAISTBAND_HT, Summary Statistics for BS_WAIST_BUTTOCK_HT_AVERAGE, Summary Statistics for BS_WAIST_GTH, Summary Statistics for BS_WAIST_HT, Summary Statistics for BS_WAIST_T_BUTTOCK, Summary Statistics for BS_WAIST_T_HIGH_HIP_B, Summary Statistics for BS_WB_BUTTOCK_HT_AVERAGE, Summary Statistics for BS_WRIST_GTH, Summary Statistics for BS_WRIST_GTH_AVERAGE, Summary Statistics for BS_WT, Summary Statistics for BS_WTH, Summary Statistics for BS_WTH_THIGH_AVERAGE
Snapshots: No snapshots
Submitter: Katrin Horn
Resource type: Gene Expression Profiling
Technology type: Technology Type
Investigation: OMICS Investigations
We are releasing the summary data from our GWAMA of PCSK9 levels, pending on acceptance of our publication, to empower other researchers to examine variants or loci in which they are interested for associations. These data are intended for research purposes only.
Citation: tba
When using this data acknowledge the source as follows: 'Data on PCSK9 has been downloaded from https://www.health-atlas.de/data_files/551.'
For any enquiries about the datasets, please contact Janne Pott (janne.pott@imise.uni-leipzig.de) ...
Submitter: Janne Pott
Resource type: Experimental Assay Type
Technology type: SNP Array
Investigation: OMICS Investigations
Study: GWAMA PCSK9
We are releasing the summary data from our GWAMA of phytosterol traits, pending on acceptance of our publication, to empower other researchers to examine variants or loci in which they are interested for associations. These data are intended for research purposes only.
Citation: tba
When using this data acknowledge the source as follows: 'Data on phytosterol X has been contributed by LIFE investigators and has been downloaded from https://www.health-atlas.de/assays/53.'
For any enquiries about ...
Submitter: Janne Pott
Resource type: Experimental Assay Type
Technology type: SNP Array
Investigation: OMICS Investigations
Study: GWAMA Phytosterole
Human Diseases: No human diseases
Data files: Summary statistics for brassicasterol (part 1), Summary statistics for brassicasterol (part 2), Summary statistics for campesterol (part 1), Summary statistics for campesterol (part 2), Summary statistics for sitosterol (part 1), Summary statistics for sitosterol (part 2), Summary statistics for stigmasterol (part 1), Summary statistics for stigmasterol (part 2)
Snapshots: No snapshots
Summary statistics from GWAS of baPWV, bfPWV, cfPWV All samples (adjusted for age, sex and log_sys)
These data is intended for research purposes only.
Citation: tbc
When using this data acknowledge the source as follows: 'Data on PWV has been contributed by LIFE-Adult investigators and has been downloaded from https://www.health-atlas.de/assays/34'
For any enquiries about the datasets, please contact Michael Rode (michael.rode@imise.uni-leipzig.de) or Markus Scholz (markus.scholz@imise.uni-leipzig.de) ...
Submitter: Michael Rode
Resource type: Genome Wide Association
Technology type: SNP Array
Investigation: OMICS Investigations
Study: GWAS Pulse Wave Velocity
We are releasing the summary data from our GWAS of carotid plaque burden traits, pending on acceptance of our publication, to empower other researchers to examine variants or loci in which they are interested for associations. These data are intended for research purposes only.
Citation:
When using this data acknowledge the source as follows: 'Data on carotid plaque burden has been contributed by LIFE-Adult investigators and has been downloaded from https://www.health-atlas.de/assays/31 '
For any ...
Submitter: Janne Pott
Resource type: Genome Wide Association
Technology type: SNP Array
Investigation: OMICS Investigations
Study: GWAS Carotid Plaque Burden
Human Diseases: atherosclerosis, coronary artery disease
Data files: Summary Statistics for CPA_max, Summary Statistics for CPA_mean, Summary Statistics for CPA_sum, Summary Statistics for CPS_max, Summary Statistics for CPS_mean, Summary Statistics for CPS_sum
Snapshots: No snapshots
We are releasing the summary data from our meta-analyses of steroid hormones, to empower other researchers to examine variants or loci in which they are interested for association with these hormonal traits. These data are intended for research purposes only.
Citation: Pott et al. (2019) Genetic Association Study of Eight Steroid Hormones and Implications for Sexual Dimorphism of Coronary Artery Disease. J Clin Endocrinol Metab 104: 5008–5023. PubMed ID: 31169883
When using this data acknowledge ...
Submitter: Janne Pott
Resource type: Genome Wide Association
Technology type: SNP Array
Investigation: OMICS Investigations
Study: GWAS Steroid Hormones
Human Diseases: No human diseases
Data files: Summary Statistics for 17-OH-Progesterone, Summary Statistics for Aldosterone, Summary Statistics for Androstenedione, Summary Statistics for Cortisol, Summary Statistics for DHEAS, Summary Statistics for Estradiol, Summary Statistics for Progesterone, Summary Statistics for Testosterone
Snapshots: No snapshots
Abstract (Expand)
Authors: Carl Beuchel, Holger Kirsten, Uta Ceglarek, Markus Scholz
Date Published: 16th Nov 2020
Publication Type: Journal article
DOI: 10.1093/bioinformatics/btaa967
Citation: Bioinformatics,btaa967
Abstract (Expand)
Authors: Michael Rode, Andrej Teren, Kerstin Wirkner, Katrin Horn, Holger Kirsten, Markus Loeffler, Markus Scholz, Janne Pott
Date Published: 13th Aug 2020
Publication Type: Journal article
Human Diseases: arteriosclerosis, arteriosclerotic cardiovascular disease
DOI: 10.1371/journal.pone.0237237
Citation: PLoS ONE 15(8):e0237237
Abstract (Expand)
Authors: J. Pott, F. Beutner, K. Horn, H. Kirsten, K. Olischer, K. Wirkner, M. Loeffler, M. Scholz
Date Published: 30th May 2020
Publication Type: Journal article
Human Diseases: cardiovascular system disease, atherosclerosis
PubMed ID: 32469969
Citation: PLoS One. 2020 May 29;15(5):e0233728. doi: 10.1371/journal.pone.0233728. eCollection 2020.
Abstract (Expand)
Authors: J. Pott, YJ. Bae, K. Horn, A. Teren, Andreas Kühnapfel, H. Kirsten, U. Ceglarek, Markus Löffler, J. Thiery, J. Kratzsch, Markus Scholz
Date Published: 6th Jun 2019
Publication Type: Not specified
Human Diseases: coronary artery disease
Abstract (Expand)
Authors: J. Pott, R. Burkhardt, F. Beutner, K. Horn, A. Teren, H. Kirsten, L. M. Holdt, G. Schuler, D. Teupser, M. Loeffler, J. Thiery, M. Scholz
PubMed ID: 28282560
Citation: Atherosclerosis. 2017 Apr;259:32-40. doi: 10.1016/j.atherosclerosis.2017.02.018. Epub 2017 Feb 24.
Abstract (Expand)
Authors: R. Burkhardt, H. Kirsten, F. Beutner, L. M. Holdt, A. Gross, A. Teren, A. Tonjes, S. Becker, K. Krohn, P. Kovacs, M. Stumvoll, D. Teupser, J. Thiery, U. Ceglarek, M. Scholz
PubMed ID: 26401656
Citation: PLoS Genet. 2015 Sep 24;11(9):e1005510. doi: 10.1371/journal.pgen.1005510. eCollection 2015 Sep.
Abstract (Expand)
Authors: H. Kirsten, H. Al-Hasani, L. Holdt, A. Gross, F. Beutner, K. Krohn, K. Horn, P. Ahnert, R. Burkhardt, K. Reiche, J. Hackermuller, M. Loffler, D. Teupser, J. Thiery, M. Scholz
Date Published: 15th Aug 2015
Publication Type: Journal article
PubMed ID: 26019233
Citation: Hum Mol Genet. 2015 Aug 15;24(16):4746-63. doi: 10.1093/hmg/ddv194. Epub 2015 May 27.
Investigations: OMICS Investigations
Studies: DNA methylation patterns reflect individual lif...
Resources: LIFE-Adult EPIC data
For our R-based workflow on GitHub pulmonologists_interspecies_scRNA
, we here provide the processed resulting annotated integrated Seurat file.
References for original datasets :
Human Charité: Hocke A, Hönzke K, Obermayer B, Baumgardt M, Wyler E, Hippenstiel S, Mache C. Charité Berlin /Berlin Institute of Health. GEO accessions GSM5958267, GSM5958272, GSM5958283, GSM5958285
Human Travaglini et al.: published at ...
Investigations: OMICS Investigations
Studies: scRNA-Seq across species for pulmonologists
Resources: scRNA-Seq expression data as RDS Seurat file
Investigations: OMICS Investigations
Studies: GWAS Body Scanner Measures
Resources: Summary Statistics
Input Files for Manuscript "A pulmonologist’s guide to perform and analyse cross-species single-lung-cell transcriptomic"
See https://github.com/GenStatLeipzig/pulmonologists_interspecies_scRNA for details.
Manuscript authored by:
Peter Pennitz1,2*, Holger Kirsten3*, Vincent D. Friedrich3,4, Emanuel Wyler5, Cengiz Goekeri1,2,6, Benedikt Obermayer7, Gitta A. Heinz8, Mir-Farzin Mashreghi8,9, Maren Büttner10,11 Jakob Trimpert12, Markus Landthaler5,13, Norbert Suttorp2, Andreas C. Hocke1,2, Stefan ...
Investigations: OMICS Investigations
Studies: scRNA-Seq across species for pulmonologists
Resources: scRNA-Seq expression data as RDS Seurat file
Investigations: OMICS Investigations
Studies: DNA methylation patterns reflect individual lif...
Resources: LIFE-Adult EPIC data
Investigations: OMICS Investigations
Studies: DNA methylation patterns reflect individual lif...
Resources: Gene Expression data
Summary statistics from GWAMA of PCSK9 levels. These data are intended for research purposes only, and available upon publication. For any enquiries about the datasets, please contact Janne Pott (janne.pott@imise.uni-leipzig.de) or Markus Scholz (markus.scholz@imise.uni-leipzig.de).
Citation: tba
When using this data acknowledge the source as follows: 'Data on PCSK9 has been downloaded from https://www.health-atlas.de/data_files/551'
We make three data sets available:
- Containing statistics ...
Creator: Janne Pott
Submitter: Janne Pott
Data file type: Not specified
Human Diseases: atherosclerosis
Summary statistics from GWAMA of stigmasterol (stf_chf, free stigmasterol to free cholesterol; stt_cht, total stigmasterol to total cholesterol; stf_laf, free stigmasterol to free lanosterol; stt_laf, total stigmasterol to free lanosterol). These data are intended for research purposes only, and available upon publication. For any enquiries about the datasets, please contact Janne Pott (janne.pott@imise.uni-leipzig.de) or Markus Scholz (markus.scholz@imise.uni-leipzig.de).
Citation: tba
When ...
Creators: Katrin Horn, Markus Scholz, Janne Pott
Submitter: Janne Pott
Data file type: Other OMICs Data
Investigations: OMICS Investigations
Studies: GWAMA Phytosterole
Resources: Summary Statistics - Phytosterols
Summary statistics from GWAMA of stigmasterol (ste, esterified stigmasterol; stf, free stigmasterol; stt, total stigmasterol; stf_ste, free to esterified stigmasterol). These data are intended for research purposes only, and available upon publication. For any enquiries about the datasets, please contact Janne Pott (janne.pott@imise.uni-leipzig.de) or Markus Scholz (markus.scholz@imise.uni-leipzig.de).
Citation: tba
When using this data acknowledge the source as follows: 'Data on stigmasterol ...
Creators: Katrin Horn, Markus Scholz, Janne Pott
Submitter: Janne Pott
Data file type: Other OMICs Data
Investigations: OMICS Investigations
Studies: GWAMA Phytosterole
Resources: Summary Statistics - Phytosterols
Creator: Katrin Horn
Submitter: Katrin Horn
Investigations: OMICS Investigations
Studies: DNA methylation patterns reflect individual lif...
Resources: LIFE-Adult EPIC data
Creator: Katrin Horn
Submitter: Katrin Horn
Investigations: OMICS Investigations
Studies: DNA methylation patterns reflect individual lif...
Resources: Gene Expression data
Creator: Katrin Horn
Submitter: Katrin Horn
Investigations: OMICS Investigations
Studies: DNA methylation patterns reflect individual lif...
Resources: Gene Expression data
Supplement Data for Publication including Supplement Material & Results (eQTL annotation, Mendelian Randomization (MR), further significant loci), Figures (correlation plot of steroid hormones, scatter plot of genetic effect sizes, regional association plots, scatter plots of MR) and Tables (Correlations, GWAS summary statistics, interaction tests, MR results)
Creator: Janne Pott
Submitter: René Hänsel
Projects: LHA - Leipzig Health Atlas, LIFE Adult, LIFE - Leipzig Research Center for Civilization Diseases, LIFE HNC - Head and Neck Cancer Group, LIFE Heart, MMML - Molecular mechanisms in malignant lymphoma, GLA - German Lymphoma Alliance, MMML Demonstrators - Molecular Mechanisms in Malignant Lymphomas - Demonstrators of Personalized Medicine, HaematoOpt - Individualized model-based managing of the next-cycle thrombopenia of CHOEP/CHOP treated patients based on platelets dynamics during the previous cycles, e:Med, GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer, GC-HNPCC - German Consortium for Hereditary Non-Polyposis Colorectal Cancer, MMML-MYC-SYS, NLP4CR - Natural Language Processing for Clinical Research, Genetical Statistics and Systems Biology, SepNet - German Competence Network Sepsis, LIFE Child, HNPCC-Sys - Genomic and transcriptomic heterogeneity of colorectal tumours arising in Lynch syndrome, GGN - German Glioma Network, CAPSys - Footprints of Sepsis Framed Within Community Acquired Pneumonia in the Blood Transcriptome, CapSys - Systems Medicine of Community Acquired Pneumonia, ProstataCA, HaematoSys - Systems biology of haematopoiesis and haematopoietic neoplasia, SMITH - Smart Medical Information Technology for Healthcare, Task Force COVID-19 Leipzig, NFDI4Health, POLAR - Polypharmacy, Drug Interactions, Risks, Management of health information systems, LivSys Transfer - Transfer of the LivSys in vitro system for hepatotoxicity into application, Project Test Demonstrator, Fundus photography as tool for analysis of eyes of subjects with diabetes, Clinical Trials Leipzig, NFDI4Health - TA3 Services, STOP-NUC, SCALE-TORT, EarlyAMDRate
Institutions: Institute for Medical Informatics, Statistics and Epidemiology (IMISE)
https://orcid.org/0000-0001-8344-0658Roles: Technician
Expertise: Data Management, Data analysis, Python, Html
Projects: LIFE Adult, LIFE - Leipzig Research Center for Civilization Diseases, LIFE Heart, Genetical Statistics and Systems Biology
Institutions: Institute for Medical Informatics, Statistics and Epidemiology (IMISE)
https://orcid.org/0000-0003-3668-0784Projects: LIFE Heart, LIFE - Leipzig Research Center for Civilization Diseases, LIFE HNC - Head and Neck Cancer Group, SepNet - German Competence Network Sepsis, GC-HNPCC - German Consortium for Hereditary Non-Polyposis Colorectal Cancer, LIFE Child, GC-HBOC - German Consortium for Hereditary Breast and Ovarian Cancer, LIFE Adult
Web page: https://www.uniklinikum-leipzig.de/einrichtungen/life