André Kahles

The Ocean Microbiomics Database reveals thermal niches and projected pressure on marine microbes in a warming ocean

The paper introduces the Ocean Microbiomics Database (OMDB) to analyze microbial thermal niches and predict their response to ocean warming, showing richness declines faster than abundance.

Indexing All Life's Known Biological Sequences

The paper develops a scalable indexing framework for biological sequences, enabling efficient and cost-effective full-text search across vast genomic datasets.

Splicing neoepitope prediction is sensitive to methodological differences

The paper evaluates the impact of methodological differences on splicing neoepitope prediction, finding high variability and limited reproducibility across pipelines.

SimReadUntil for Benchmarking Selective Sequencing Algorithms on ONT Devices

SimReadUntil benchmarks selective sequencing algorithms on ONT devices by simulating ReadUntil API behavior with real or simulated reads.

Aligning Distant Sequences to Graphs using Long Seed Sketches

The paper introduces a long seed sketch method for sequence-to-graph alignment, improving time-accuracy trade-offs in high mutation rate scenarios.

CAMP: A modular metagenomics analysis system for integrated multi-step data exploration

CAMP provides a modular metagenomics analysis system that enables scalable, extensible workflows with integrated data visualization and reporting.

Label-guided seed-chain-extend alignment on annotated De Bruijn graphs

This paper introduces a new alignment method for annotated De Bruijn graphs that improves taxonomic classification accuracy and coverage for long reads.

SECEDO: SNV-based subclone detection using ultra-low coverage single-cell DNA sequencing

SECEDO detects subclones in tumors using SNVs from ultra-low coverage single-cell DNA sequencing, achieving high accuracy in synthetic and real datasets.

scROSHI - robust supervised hierarchical identification of single cells

scROSHI identifies cell types without training data by using pre-existing gene sets and hierarchical relationships, outperforming methods in low-data and high-diversity scenarios.

Lossless Indexing with Counting de Bruijn Graphs

This paper introduces Counting de Bruijn graphs for efficiently indexing and querying sequencing data, achieving smaller storage and faster construction compared to existing methods.

Topology-based Sparsification of Graph Annotations

The paper introduces RowDiff, a method to compactly store graph labels by exploiting annotation similarities, achieving significant space reductions when combined with compression techniques.

Fast Alignment-Free Similarity Estimation By Tensor Sketching

The paper introduces Tensor Sketch, a method for fast and accurate edit distance estimation in biological sequences, outperforming existing methods in speed and accuracy.

SCIM: Universal Single-Cell Matching with Unpaired Feature Sets

SCIM matches single-cell measurements across technologies by learning a technology-invariant latent space and applying bipartite matching, achieving high accuracy in real-world datasets.

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.

AStarix: Fast and Optimal Sequence-to-Graph Alignment

AStarix provides a fast and optimal algorithm for aligning sequences to genome graphs, outperforming existing methods by 1-2 orders of magnitude.

Sparse Binary Relation Representations for Genome Graph Annotation

This paper introduces a new compression method for de Bruijn graph labels, showing improved performance over existing methods on real-world datasets.

A Pan-Cancer Transcriptome Analysis Reveals Pervasive Regulation through Tumor-Associated Alternative Promoters

This study identifies alternative promoters as key regulators in the cancer transcriptome using RNA-Seq data from 1,188 cancer samples.

Dynamic compression schemes for graph coloring

The paper introduces two compression methods for graph coloring in sequencing data, reducing memory use by up to three orders of magnitude while maintaining dynamic graph topology.

Metannot: A succinct data structure for compression of colors in dynamic de Bruijn graphs

The paper introduces a dynamic data structure called Metannot for compressing and indexing graph metadata in HTS data, achieving better compression ratios than existing methods.

Genomic basis for RNA alterations revealed by whole-genome analyses of 27 cancer types

The paper analyzes RNA alterations across 27 cancer types using whole-genome sequencing data, identifying gene expression associations with DNA variants and structural fusions.

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.

Assessing the Gene Regulatory Landscape in 1,188 Human Tumors

This study analyzes whole genome and RNA-Seq data from 1,188 cancer patients to map the effects of somatic and germline genetic variation on gene expression in cancer.

Large-Scale Uniform Analysis of Cancer Whole Genomes in Multiple Computing Environments

The paper describes the PCAWG project's large-scale analysis of cancer whole genomes across multiple computing environments, producing validated consensus variants for downstream research.

Genomic Rearrangements Considered as Quantitative Traits

The paper develops a method to map structural variants as quantitative traits in Arabidopsis, identifying transpositions and their phenotypic effects using low-coverage sequencing data.

Genome Graphs

This paper introduces genome graphs as an alternative to linear reference genomes, showing they improve read mapping and variant calling compared to the standard GRCh38 reference.

Integrative Analysis of Transcriptome Variation in Uterine Carcinosarcoma and Comparison to Sarcoma and Endometrial Carcinoma

The paper compares transcriptome variations between Uterine Carcinosarcoma, Sarcomas, and Endometrial Carcinoma to identify tumor-specific splicing and expression patterns and genetic determinants of expression differences.