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This Analysis reports the development and assessment of 645 multiple reaction monitoring (MRM) mass spectrometry assays to quantify 319 targeted human breast cancer proteins. The results of this pilot project coordinated among three individual groups suggest that an organized international effort to generate MRM assays to the human proteome will be possible.
The RGASP consortium compared 25 RNA-seq analysis programs in their ability to identify exons, reconstruct transcripts and quantify expression levels. Assembly of isoforms and their expression levels in higher eukaryotes remains a challenge.
Authors compare RNA-seq aligners on mouse and human data sets using benchmarks such as alignment yield, splice junction accuracy and suitability for transcript reconstruction. The work highlights the strength of each program and discusses outstanding needs in RNA-seq analysis.
A systematic evaluation of various single-cell RNA-seq approaches reports their sensitivity, accuracy and reproducibility and establishes the high performance of a high-throughput microfluidic method.
This comparison of five RNA-seq library preparation methods highlights metrics for assessing the suitability of the methods for samples with low amounts of RNA and/or those with low-quality RNA.
A systematic study of the intra- and interlaboratory reproducibility of a standardized affinity purification–mass spectrometry protocol demonstrates the high reproducibility of this technique and hints at the feasibility of a large-scale human interactome project through interlaboratory efforts.
In this analysis, the authors directly compared immunofluorescence and fluorescent-protein tagging of 506 human proteins and studied their subcellular localization. They conclude that the two methodologies are highly complementary and propose an integrative strategy for the characterization of newly identified proteins.
In this analysis, the authors directly compared the performance of flow cytometry data processing algorithms to manual gating approaches. The results offer information of practical utility about the performance of the algorithms as applied to different data sets and challenges.