Jakob Skou Pedersen

A deep generative decoder predicts microRNA expression from bulk and single-cell mRNA profiles

miDGD predicts microRNA expression from bulk and single-cell mRNA profiles using a deep generative decoder, achieving high accuracy across diverse datasets and cell types.

bayesReact: Expression-coupled regulatory motif analysis detects microRNA activity in cancer and at the single cell level

bayesReact infers microRNA regulatory activities from single-cell and bulk data, showing strong correlation with expression and improved performance over existing methods.

LRP2 expression in melanoma is associated with a transitory cell state, increased T cell infiltration, and is upregulated by IFNγ signaling

This study identifies LRP2 expression in melanoma as linked to a transient differentiation state, T cell infiltration, and IFNγ signaling, with associations to better prognostic features.

Using high-dimensional immunophenotyping for mapping immune cell composition in rapid cryopreserved liquid biopsies

This study develops a 37-marker spectral flow cytometry assay for high-dimensional immunophenotyping of cryopreserved liquid biopsies and validates its robustness against cryopreservation effects.

circHIPK3 nucleates IGF2BP2 and functions as a competing endogenous RNA

This paper identifies circHIPK3 as a competing endogenous RNA that sequesters IGF2BP2 to regulate target mRNAs, including STAT3, and shows its correlation with bladder cancer survival.

Pan-cancer association of DNA repair deficiencies with whole-genome mutational patterns

The paper identifies DNA repair deficiency genes using mutational patterns and develops predictive models for their loss-of-function variants across cancers.

DREAMS: Deep Read-level Error Model for Sequencing data applied to low-frequency variant calling and circulating tumor DNA detection

DREAMS improves variant calling and circulating tumor DNA detection by modeling sequencing errors at the read level using deep learning.

miRNA activity inferred from single cell mRNA expression

The paper estimates miRNA activity from single-cell RNA sequencing data by analyzing motif enrichment, validated on bulk and single-cell datasets.

Transcriptome-wide profiles of circular RNA and RNA binding protein interactions reveal effects on circular RNA biogenesis and cancer pathway expression

The paper identifies circRNA-RBP interactions in cancer, showing their role in circRNA biogenesis and cancer gene expression, with implications for bladder cancer prognosis.

Unique genomic features and deeply-conserved functions of long non-coding RNAs in the Cancer LncRNA Census (CLC)

The paper introduces the Cancer LncRNA Census (CLC), a curated resource of lncRNAs with causative roles in cancer, and shows their genomic and evolutionary features.

Whole genome and RNA sequencing of 1,220 cancers reveals hundreds of genes deregulated by rearrangement of cis-regulatory elements

The paper identifies hundreds of genes deregulated by SVs in cancer, showing increased expression linked to SV breakpoints and enhancer elements.

Integrative pathway enrichment analysis of multivariate omics data

ActivePathways integrates multivariate omics data to identify enriched pathways, revealing cancer driver genes and prognostic pathways in breast cancer.

EBADIMEX: An empirical Bayes approach to detect joint differential expression and methylation and to classify samples

EBADIMEX detects joint differential expression and methylation and classifies cancer samples using empirical Bayes methods and moderated tests.

Regmex, Motif analysis in ranked lists of sequences

Regmex identifies overrepresented motifs in ranked sequence lists using regular expressions and Markov models, with options for enrichment evaluation.

Deficiency of nucleotide excision repair explains mutational signature observed in cancer

The paper shows that NER deficiency increases Signature 8 mutations in specific tissues and suggests this could be a biomarker for NER-deficiency in cancer.

Pathway and network analysis of more than 2,500 whole cancer genomes

The paper analyzes non-coding mutations across 2,583 cancer genomes to identify genes and pathways affected, finding clusters of interacting proteins and insights into cancer mechanisms.

A Site Specific Model And Analysis Of The Neutral Somatic Mutation Rate In Whole-Genome Cancer Data

The paper develops a site-specific model to predict mutation rates in cancer genomes, showing it outperforms regional models by incorporating local genomic variables.

Passenger mutations in 2500 cancer genomes: Overall molecular functional impact and consequences

The paper analyzes 2500 cancer genomes to assess the molecular functional impact of mutations, finding that some putative passenger variants may influence gene activity and contribute to cancer phenotypes.

Discovery and characterization of coding and non-coding driver mutations in more than 2,500 whole cancer genomes

The paper identifies and characterizes coding and non-coding driver mutations across 2,500 cancer genomes, revealing new candidates and questioning previous findings.

The whole-genome panorama of cancer drivers

This paper identifies driver mutations across 2,500 tumors from 37 cancer types, revealing a whole-genome panorama of genomic events that underlie tumor development.