Author

Amjad Alkodsi

University of HelsinkiORCID 0000-0003-3528-4683Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Bioinformatics· 3 Genomics· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:statistical model· 4 Organism:human· 3 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1 Research Focus:GWAS / association mapping· 1 Assay:GWAS summary statistics· 1

Frequent Co-Authors

Rainer LehtoneniD· 3 shared Antti HäkkineniD· 2 shared Johanna HynnineniD· 2 shared Kaiyang ZhangiD· 2 shared Katja KaipioiD· 2 shared Olli CarpéniD· 2 shared Sakari HietaneniD· 2 shared Sampsa HautaniemiiD· 2 shared

Activity by Year

2018-2020 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 44 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

3 shared papersBioinformatics

Rainer LehtonenORCID

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

BioinformaticsbioRxivPreprintJan 27, 2020

ctDNAtools: An R package to work with sequencing data of circulating tumor DNA

Amjad Alkodsi, Leo Meriranta, Annika Pasanen, Sirpa Leppä

ctDNAtools is an R package for analyzing ctDNA sequencing data, offering MRD testing and cfDNA fragmentation analysis.

6 citations

whole-genome sequencingstatistical model

𝕏 PostBluesky

BioinformaticsbioRxivPreprintNov 25, 2019

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

Antti Häkkinen, Kaiyang Zhang, Amjad Alkodsi…·Sampsa Hautaniemi

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

1 citation

humanbulk RNA-seq

𝕏 PostBluesky

BioinformaticsBioinformaticsPeer-reviewedApr 17, 2018

Identifying differentially methylated sites in samples with varying tumor purity

Antti Häkkinen, Amjad Alkodsi, Chiara Facciotto…·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.

4 citations

humanDNA methylation

𝕏 PostBluesky

GenomicsbioRxivPreprintMar 29, 2018

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

Niko Välimäki, Heli Kuisma, Annukka M. Pasanen…·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.

DOI 10.1101/291237

humanGWAS summary statistics

𝕏 PostBluesky