Author

Rainer Lehtonen

University of HelsinkiORCID 0000-0002-8343-0318Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 3 Approach:statistical model· 3 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Research Focus:dimensionality reduction· 1 Assay:DNA methylation· 1

Frequent Co-Authors

Amjad AlkodsiiD· 3 shared Johanna HynnineniD· 3 shared Sakari HietaneniD· 3 shared Sampsa HautaniemiiD· 3 shared Antti HäkkineniD· 2 shared Kaisa HuhtineniD· 2 shared Kaiyang ZhangiD· 2 shared Katja KaipioiD· 2 shared

Activity by Year

2018-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 40 mutual co-author links

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3 shared papersBioinformatics

Amjad AlkodsiORCID

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Author profile →

4 papers

Recent·Most cited

Deciphering Cancer Genomes with GenomeSpy: A Grammar-Based Visualization Toolkit

Kari Lavikka, Jaana Oikkonen, Yilin Li, Taru Muranen, Giulia Micoli, Giovanni Marchi, Alexandra Lahtinen, Kaisa Huhtinen, Rainer Lehtonen, Sakari Hietanen, Johanna Hynninen, Anni Virtanen, Sampsa Hautaniemi

GenomeSpy is a grammar-based visualization toolkit for genomic data analysis that enables interactive exploration of large datasets, demonstrated on ovarian cancer samples.

GigaScience · Jan 1, 2024Peer-reviewedBioinformatics

PRISM: Recovering cell type specific expression profilesfrom composite RNA-seq data

Antti Häkkinen, Kaiyang Zhang, Amjad Alkodsi, Noora Andersson, Erdoğan Pekcan Erkan, Jun Dai, Katja Kaipio, Tarja Lamminen, Naziha Mansuri, Kaisa Huhtinen, Anna Vähärautio, Olli Carpén, Johanna Hynninen, Sakari Hietanen, Rainer Lehtonen, Sampsa Hautaniemi

PRISM recovers cell type specific expression profiles from composite RNA-seq data, improving patient response prediction compared to raw bulk data.

bioRxiv · Nov 25, 2019 · PreprintBioinformatics

Identifying differentially methylated sites in samples with varying tumor purity

Antti Häkkinen, Amjad Alkodsi, Chiara Facciotto, Kaiyang Zhang, Katja Kaipio, Sirpa Leppä, Olli Carpén, Seija Grénman, Johanna Hynninen, Sakari Hietanen, Rainer Lehtonen, Sampsa Hautaniemi

The paper presents a computational method to identify differentially methylated sites in heterogeneous tumor samples with varying cancer cell fractions, without needing normal controls or prior purity estimates.

Bioinformatics · Apr 17, 2018Peer-reviewedBioinformatics

ESR1, WT1, WNT4, ATM and TERT loci are major contributors to uterine leiomyoma predisposition

Niko Välimäki, Heli Kuisma, Annukka M. Pasanen, Oskari Heikinheimo, Jari Sjöberg, Ralf C. Bützow, Nanna S. Sarvilinna, Hanna-Riikka Heinonen, Jaana Tolvanen, Simona Bramante, Tomas J. Tanskanen, JUHA P. AUVINEN, Terhi Piltonen, Amjad Alkodsi, Rainer Lehtonen, , Lauri A. Aaltonen

This study identifies five new genetic loci associated with uterine leiomyoma risk and links them to estrogen receptor alpha and genetic stability.

bioRxiv · Mar 29, 2018 · PreprintGenomics