Cancer Genomics and Diagnostics

Unique K-mer sequences for validating cancer-related substitution, insertion and deletion mutations

The paper develops a method using k-mer sequences to validate somatic mutations in cancer genome sequencing data, showing it effectively identifies true positive mutations including insertions and deletions.

annoFuse: an R Package to annotate, prioritize, and interactively explore putative oncogenic RNA fusions

annoFuse filters and prioritizes oncogenic gene fusions from RNA-Seq data, improving identification of clinically relevant fusions in cancer datasets.

Pan-cancer identification of clinically relevant genomic subtypes using outcome-weighted integrative clustering

This paper introduces survClust, an outcome-weighted clustering algorithm that identifies clinically relevant genomic subtypes in pan-cancer data, outperforming unsupervised methods in detecting subpopulations with aggressive clinical behavior.

Extensive phylogenies of human development reveal variable embryonic patterns

The paper reconstructs phylogenies of human development using whole-genome sequencing to show variable embryonic patterns and lineage asymmetries across individuals and tissues.

Mutational profiling of micro-dissected pre-malignant lesions from archived specimens

This paper develops a method to improve mutational profiling of pre-malignant lesions using degraded FFPE DNA, achieving better coverage and variant calling accuracy.

cancerAlign: Stratifying tumors by unsupervised alignment across cancer types

cancerAlign improves tumor stratification by aligning tumors across cancer types using adversarial learning and consensus clustering, showing better results than methods that cluster within single cancer types.

FinaleDB: a browser and database of cell-free DNA fragmentation patterns

FinaleDB provides a database and browser for cfDNA fragmentation patterns, enabling integration with other omics data to study gene regulation and disease.

Massively parallel phenotyping of variant impact in cancer with Perturb-seq reveals a shift in the spectrum of cell states induced by somatic mutations

The paper uses Perturb-seq to assess the phenotypic impact of somatic variants in cancer, revealing a continuum of gain-of-function KRAS variants.

DORGE: Discovery of Oncogenes and Tumor SuppressoR Genes Using Genetic and Epigenetic Features

DORGE identifies cancer driver genes by integrating genetic and epigenetic data, finding histone modifications predict TSGs and missense mutations predict OGs.

Mis-annotated multi nucleotide variants in public cancer genomics datasets can lead to inaccurate mutation calls with significant implications

The paper identifies mis-annotated multi-nucleotide variants (MNVs) in cancer genomics datasets, showing they lead to incorrect amino acid change predictions and recommends merging SNVs into MNVs for accurate variant annotation.

DeepSSV: detecting somatic small variants in paired tumor and normal sequencing data with convolutional neural network

DeepSSV detects somatic small variants in paired tumor and normal sequencing data using a convolutional neural network, achieving better performance than existing methods in F1 score.

MutSignatures: An R Package for Extraction and Analysis of Cancer Mutational Signatures

The paper introduces mutSignatures, an R package for analyzing cancer mutational signatures, showing it can identify known signatures and reveal new patterns linked to clinical and molecular features.

NIMBus: a Negative Binomial Regression based Integrative Method for Mutation Burden Analysis

NIMBus identifies mutational hotspots by integrating mutation data with genomic features to account for heterogeneity, revealing known drivers and regulatory disruptions in cancer.

TruSight Oncology 500: Enabling Comprehensive Genomic Profiling and Biomarker Reporting with Targeted Sequencing

The paper describes a targeted sequencing assay and bioinformatics workflow for comprehensive genomic profiling of cancer, achieving high accuracy in variant detection and biomarker assessment.

Genome-wide study of the effect of blood collection tubes on the cell-free DNA methylome

This study evaluates how blood collection tubes and time delay affect cfDNA methylation, finding robust results across tubes but recommending EDTA tubes processed within 24 hours.

Accuracy and Reproducibility of Somatic Point Mutation Calling in Clinical-Type Targeted Sequencing Data

This study evaluates somatic mutation calling accuracy and reproducibility in clinical-type targeted sequencing data using cell line samples and multiple variant callers.

mutSigMapper: an R package to map spectra to mutational signatures based on shot-noise modeling

mutSigMapper provides a method to map mutational spectra to signatures using shot-noise modeling, offering a non-parametric statistical assessment of significance.

Detection of genomic alterations in breast cancer with circulating tumour DNA sequencing

This paper develops a targeted cfDNA sequencing approach for detecting genomic alterations in breast cancer using UMIs and bioinformatics pipelines, showing high concordance with tumor sequencing.

Tumor Phylogeny Topology Inference via Deep Learning

This paper introduces deep learning methods to infer tumor phylogeny topology and feasibility from single-cell genotype data, demonstrating the potential of data-driven approaches in cancer evolution analysis.

Framework For Quality Assessment Of Whole Genome, Cancer Sequences

The paper introduces a framework for assessing the quality of whole genome cancer sequences using a star rating system based on five QC measures, providing a tool for researchers to evaluate and exclude low-quality data.

Generating realistic null hypothesis of cancer mutational landscapes using SigProfilerSimulator

SigProfilerSimulator generates realistic null mutational landscapes for cancer genomics to evaluate bioinformatics tools and statistical analyses.

The genomic landscapes of individual melanocytes from human skin

This study genotypes individual melanocytes from human skin, revealing mutation patterns linked to sun exposure, skin cancer risk, and melanoma origins.

Sigflow: an automated and comprehensive pipeline for cancer genome mutational signature analysis

Sigflow is a pipeline for comprehensive cancer genome mutational signature analysis, supporting multiple DNA alteration types and offering reproducible research through Docker.

PhyDOSE: Design of Follow-up Single-cell Sequencing Experiments of Tumors

PhyDOSE optimizes follow-up single-cell sequencing experiments using bulk data to reduce costs while maintaining accurate tumor phylogeny reconstruction.

Whole genome sequencing of cell-free DNA yields genome-wide read distribution patterns to track tissue of origin in cancer patients

This study uses whole genome sequencing of cell-free DNA to identify tissue-of-origin patterns, achieving high specificity and sensitivity in cancer patients.

The Clinical Kinase Index: Prioritizing Understudied Kinases as Targets for the Treatment of Cancer

The paper develops a scoring system to prioritize understudied kinases as potential cancer targets using TCGA data.

The landscape of interactions between cancer polygenic risk scores and somatic alterations in cancer cells

This study examines how cancer polygenic risk scores correlate with somatic alterations in tumors from The Cancer Genome Atlas, revealing associations with specific molecular subtypes and driver events.

STAMPede: A Precision Oncology Catalogue of Solid Tumors

STAMPede is a web-based portal for visualizing somatic tumor sequencing data from a solid tumor oncology panel, enabling query and display of gene-, variant-, and cancer-level summary statistics.

RRM2B is frequently amplified across multiple tumor types: non-oncogenic addiction and therapeutic opportunities

The paper identifies frequent RRM2B amplification in multiple tumors, links it to DNA repair defects and poor outcomes, and suggests therapeutic opportunities.

Performances of targeted RNA-sequencing for the analysis of fusion transcripts, gene mutation and expression in haematological malignancies.

This study evaluates targeted RNA sequencing for detecting fusion transcripts, mutations, and expression in hematological malignancies, finding it effective for diagnosing leukemia subtypes and identifying most DNA mutations at the mRNA level.