Manuel A. Rivas

35.4k total citations · 2 hit papers
67 papers, 2.7k citations indexed

About

Manuel A. Rivas is a scholar working on Genetics, Molecular Biology and Epidemiology. According to data from OpenAlex, Manuel A. Rivas has authored 67 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Genetics, 29 papers in Molecular Biology and 7 papers in Epidemiology. Recurrent topics in Manuel A. Rivas's work include Genetic Associations and Epidemiology (34 papers), Genomics and Rare Diseases (13 papers) and Bioinformatics and Genomic Networks (11 papers). Manuel A. Rivas is often cited by papers focused on Genetic Associations and Epidemiology (34 papers), Genomics and Rare Diseases (13 papers) and Bioinformatics and Genomic Networks (11 papers). Manuel A. Rivas collaborates with scholars based in United States, United Kingdom and Finland. Manuel A. Rivas's co-authors include Mark J. Daly, Nasa Sinnott-Armstrong, Yosuke Tanigawa, David Altshuler, Benjamin M. Neale, Matthew Aguirre, Michael Wainberg, Marju Orho‐Melander, Benjamin F. Voight and Kathryn Roeder and has published in prestigious journals such as Nature Communications, Nature Genetics and Bioinformatics.

In The Last Decade

Manuel A. Rivas

63 papers receiving 2.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Opportunities and challenges for transcriptome-wide association studies

2019 506 citations Michael Wainberg, Nasa Sinnott-Armstrong et al. Nature Genetics profile →
Testing for an Unusual Distribution of Rare Variants

2011 432 citations Manuel A. Rivas, David Altshuler et al. PLoS Genetics profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Manuel A. Rivas United States	28	1.6k	1.3k	237	154	146	67	2.7k
Futao Zhang China	10	1.5k 0.9×	1.2k 0.9×	251 1.1×	171 1.1×	191 1.3×	27	2.7k
Andrew Bakshi Australia	15	1.5k 0.9×	1.1k 0.8×	270 1.1×	150 1.0×	182 1.2×	32	2.6k
Sarah S. Murray United States	23	1.7k 1.1×	1.5k 1.1×	255 1.1×	159 1.0×	158 1.1×	45	3.3k
Aoife McMahon United Kingdom	10	981 0.6×	1.2k 0.9×	201 0.8×	138 0.9×	157 1.1×	16	2.2k
Jack A. Kosmicki United States	13	1.3k 0.9×	1.4k 1.1×	215 0.9×	215 1.4×	84 0.6×	20	2.9k
Steven Gazal United States	26	1.6k 1.0×	1.1k 0.8×	174 0.7×	173 1.1×	271 1.9×	44	2.8k
Slavé Petrovski Australia	33	1.6k 1.0×	1.7k 1.3×	224 0.9×	100 0.6×	208 1.4×	71	3.8k
Peggy Hall United States	5	1.6k 1.0×	1.8k 1.4×	370 1.6×	200 1.3×	221 1.5×	8	3.3k
Elizabeth T. Cirulli United States	28	1.1k 0.7×	1.1k 0.8×	208 0.9×	270 1.8×	265 1.8×	50	2.8k
Christian Fuchsberger Italy	22	1.9k 1.2×	1.2k 1.0×	349 1.5×	213 1.4×	235 1.6×	61	3.3k

Countries citing papers authored by Manuel A. Rivas

Since Specialization

Citations

This map shows the geographic impact of Manuel A. Rivas's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Manuel A. Rivas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Manuel A. Rivas more than expected).

Fields of papers citing papers by Manuel A. Rivas

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Manuel A. Rivas. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Manuel A. Rivas. The network helps show where Manuel A. Rivas may publish in the future.

Co-authorship network of co-authors of Manuel A. Rivas

This figure shows the co-authorship network connecting the top 25 collaborators of Manuel A. Rivas. A scholar is included among the top collaborators of Manuel A. Rivas based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Manuel A. Rivas. Manuel A. Rivas is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Tanigawa, Yosuke, Junyang Qian, Guhan Venkataraman, et al.. (2022). Significant sparse polygenic risk scores across 813 traits in UK Biobank. PLoS Genetics. 18(3). e1010105–e1010105. 54 indexed citations

Wojcik, Genevieve L., Jacob Edelson, Christopher R. Gignoux, et al.. (2022). Opportunities and challenges for the use of common controls in sequencing studies. Nature Reviews Genetics. 23(11). 665–679. 16 indexed citations

O’Sullivan, Jack W., Anna Shcherbina, Johanne Marie Justesen, et al.. (2021). Combining Clinical and Polygenic Risk Improves Stroke Prediction Among Individuals With Atrial Fibrillation. Circulation Genomic and Precision Medicine. 14(3). e003168–e003168. 28 indexed citations

Chang, Christopher, Yosuke Tanigawa, Balasubramanian Narasimhan, et al.. (2021). Fast numerical optimization for genome sequencing data in population biobanks. Bioinformatics. 37(22). 4148–4155. 9 indexed citations

Kwon, Yongchan, Manuel A. Rivas, & James Zou. (2021). Efficient Computation and Analysis of Distributional Shapley Values. International Conference on Artificial Intelligence and Statistics. 793–801. 1 indexed citations

Tanigawa, Yosuke, Johanne Marie Justesen, Jonathan Taylor, et al.. (2021). Survival analysis on rare events using group-regularized multi-response Cox regression. Bioinformatics. 37(23). 4437–4443. 7 indexed citations

Wainberg, Michael, Samuel E. Jones, Sean Hill, et al.. (2021). Association of accelerometer-derived sleep measures with lifetime psychiatric diagnoses: A cross-sectional study of 89,205 participants from the UK Biobank. PLoS Medicine. 18(10). e1003782–e1003782. 38 indexed citations

Aguirre, Matthew, Yosuke Tanigawa, Guhan Venkataraman, et al.. (2021). Polygenic risk modeling with latent trait-related genetic components. European Journal of Human Genetics. 29(7). 1071–1081. 7 indexed citations

Li, Ruilin, Christopher Chang, Johanne Marie Justesen, et al.. (2020). Fast Lasso method for large-scale and ultrahigh-dimensional Cox model with applications to UK Biobank. Biostatistics. 23(2). 522–540. 22 indexed citations

10.

Córdova‐Palomera, Aldo, Catherine Tcheandjieu, Jason Fries, et al.. (2020). Cardiac Imaging of Aortic Valve Area From 34 287 UK Biobank Participants Reveals Novel Genetic Associations and Shared Genetic Comorbidity With Multiple Disease Phenotypes. Circulation Genomic and Precision Medicine. 13(6). e003014–e003014. 10 indexed citations

11.

Qian, Junyang, Yosuke Tanigawa, Matthew Aguirre, et al.. (2020). A fast and scalable framework for large-scale and ultrahigh-dimensional sparse regression with application to the UK Biobank. PLoS Genetics. 16(10). e1009141–e1009141. 67 indexed citations

12.

Tanigawa, Yosuke, et al.. (2020). Sex-specific genetic effects across biomarkers. European Journal of Human Genetics. 29(1). 154–163. 47 indexed citations

13.

Tcheandjieu, Catherine, Matthew Aguirre, Stefan Gustafsson, et al.. (2020). A phenome-wide association study of 26 mendelian genes reveals phenotypic expressivity of common and rare variants within the general population. PLoS Genetics. 16(11). e1008802–e1008802. 8 indexed citations

14.

Rivas, Manuel A., et al.. (2020). Datasets described in 'Genetics of 35 blood and urine biomarkers in the UK Biobank'. 2 indexed citations

15.

Wainberg, Michael, Nasa Sinnott-Armstrong, Nicholas Mancuso, et al.. (2019). Opportunities and challenges for transcriptome-wide association studies. Nature Genetics. 51(4). 592–599. 506 indexed citations breakdown →

16.

Rao, Abhiram, Daniel Lindholm, Manuel A. Rivas, et al.. (2018). Large-Scale Phenome-Wide Association Study of PCSK9 Variants Demonstrates Protection Against Ischemic Stroke. Circulation Genomic and Precision Medicine. 11(7). e002162–e002162. 45 indexed citations

17.

DeBoever, Christopher, Yosuke Tanigawa, Maléne E. Lindholm, et al.. (2018). Medical relevance of protein-truncating variants across 337,205 individuals in the UK Biobank study. Nature Communications. 9(1). 1612–1612. 61 indexed citations

18.

McInnes, Gregory, Yosuke Tanigawa, Adam Lavertu, et al.. (2018). Global Biobank Engine: enabling genotype-phenotype browsing for biobank summary statistics. Bioinformatics. 35(14). 2495–2497. 44 indexed citations

19.

Pirinen, Matti, Christian Benner, Pekka Marttinen, et al.. (2017). biMM: efficient estimation of genetic variances and covariances for cohorts with high-dimensional phenotype measurements. Bioinformatics. 33(15). 2405–2407. 5 indexed citations

20.

Choy, Edwin, Roman Yelensky, Robert M. Plenge, et al.. (2008). Genetic Analysis of Human Traits In Vitro: Drug Response and Gene Expression in Lymphoblastoid Cell Lines. PLoS Genetics. 4(11). e1000287–e1000287. 164 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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