Machine learning (ML) is increasingly used in clinical oncology to diagnose cancers, predict
patient outcomes, and inform treatment planning. Here, we review recent applications of ML …

Cancer immunogenomics is an emerging field that bridges genomics and immunology. The
establishment of large-scale genomic collaborative efforts along with the development of …

Certified RNA reference materials are indispensable for assessing the reliability of RNA
sequencing to detect intrinsically small biological differences in clinical settings, such as …

Structural variants (SVs) are a major source of human genetic diversity and have been
associated with different diseases and phenotypes. The detection of SVs is difficult, and a …

Recent advances in neoantigen research have accelerated the development of tumor
immunotherapies, including adoptive cell therapies (ACTs), cancer vaccines and antibody …

Comparing diverse single-cell RNA sequencing (scRNA-seq) datasets generated by
different technologies and in different laboratories remains a major challenge. Here we …

A growing number of druggable targets and national initiatives for precision oncology
necessitate broad genomic profiling for many cancer patients. Whole exome sequencing …

In the late 19th century, formalin fixation with paraffin-embedding (FFPE) of tissues was
developed as a fixation and conservation method and is still used to this day in routine …

Background The cancer genome is commonly altered with thousands of structural
rearrangements including insertions, deletions, translocation, inversions, duplications, and …

DNA variation analysis has become indispensable in many aspects of modern biomedicine,
most prominently in the comparison of normal and tumor samples. Thousands of samples …