A practical problem with Egger regression in Mendelian randomization is a research paper published in PLoS Genetics (2022). On theSindex it has a DataRank of 0.505. It has been cited 28 times.
Scored on demand from live citation data
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full — never from an abstract alone.
Base Score Contribution
0.505
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →National Institutes of Health
Grant: R01AG065636
National Institutes of Health
Grant: R01AG065636, R01 AG069895, RF1 AG067924, U01AG073079, R01 HL116720, R01 GM113250 and R01GM126002
NIA NIH HHS
Grant: RF1 AG067924
NIGMS NIH HHS
Grant: R01 GM113250
NIGMS NIH HHS
Grant: R01 GM126002
NIA NIH HHS
Grant: R01 AG069895
NIA NIH HHS
Grant: U01 AG073079
National Institutes of Health
Grant: 5U01AG073079-03
Causal and integrative deep learning for Alzheimer's disease genetics
National Institutes of Health
Grant: 5R01HL116720-05
Association analysis of rare variants with sequencing data
National Institutes of Health
Grant: 5R01GM126002-04
Estimation and Inference of Gene Regulatory Networks
National Institutes of Health
Grant: 1R01AG069895-01
Deep Learning with Neuroimaging Genetic Data for Alzheimer's Disease
National Institutes of Health
Grant: 5R01AG065636-02
Discovering causal genes, brain regions and other risk factors for Alzheimer'a disease
National Institutes of Health
Grant: 1RF1AG067924-01
Integrating Alzheimer's disease GWAS with proteomic and metabolomic QTL data
National Institutes of Health
Grant: 9R01GM113250-11A1
Statistical Methods for Genomic Data
Minnesota Supercomputing Institute, University of Minnesota
FWCI
4.06
Citation Percentile
0.9%
Citation Trend
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals