Tag Archives: Dana Farber Cancer Institute

In the last two decades, immunotherapy has emerged as a leading treatment for advanced renal carcinoma cancer (more commonly known as kidney cancer). This therapy is now part of the standard of...

Malignant abdominal fluid (ascites) frequently develops in women with advanced high-grade serous ovarian cancer (HGSOC) and is associated with drug resistance and a poor prognosis. To comprehensively characterize the HGSOC ascites ecosystem, a team...

Single-cell RNA-sequencing technologies provide a powerful tool for systematic dissection of cellular heterogeneity. However, the prevalence of dropout events imposes complications during data analysis and, despite numerous efforts from the community, this challenge has yet to be solved. Researchers at ...

RNA sequencing has become a ubiquitous technology used throughout life sciences as an effective method of measuring RNA abundance quantitatively in tissues and cells. The increase in use of RNA-seq technology has led to the continuous development of new tools ...

Technique detects technical biases that otherwise confound test results A new computational method can improve the accuracy of gene expression analyses, which are increasingly used to diagnose and monitor cancers and are a major tool for basic biological research. Researchers ...

The ability to quantify cellular heterogeneity is a major advantage of single-cell technologies. However, statistical methods often treat cellular heterogeneity as a nuisance. Researchers from the Dana-Farber Cancer Institute and the University of Wisconsin, Madison present a novel method to ...

Current computational methods for estimating transcript abundance from RNA-seq data can lead to hundreds of false-positive results. Researchers from the Dana-Farber Cancer Institute show that these systematic errors stem largely from a failure to model fragment GC content bias. Sample-specific ...

Current computational methods for estimating transcript abundance from RNA-seq data can lead to hundreds of false-positive results. Researchers from the Dana-Farber Cancer Institute show that these systematic errors stem largely from a failure to model fragment GC content bias. Sample-specific ...

Obtaining RNA-seq measurements involves a complex data analytical process with a large number of competing algorithms as options. There is much debate about which of these methods provides the best approach. Unfortunately, it is currently difficult to evaluate their performance ...

The ability to quantify cellular heterogeneity is a major advantage of single-cell technologies. Although understanding such heterogeneity is of primary interest in a number of studies, for convenience, statistical methods often treat cellular heterogeneity as a nuisance factor. A team ...