The MAQC Society Announces Publication of Next-Gen Sequencing Best Practice Articles in Nature Biotechnology
Collection showcases resources and recommendations to enhance sequencing reproducibility in the context of biology, health, and medicine
LITTLE ROCK, Ark., Sept. 16, 2021 /PRNewswire/ -- The Massive Analysis and Quality Control (MAQC) Society, an organization seeking to promote and advance reproducible science principles and quality control, today announced the publication of a collection of journal articles in the September issue of Nature Biotechnology (NBT). With leadership from the U.S. Food and Drug administration (FDA), the Sequencing and Quality Control Phase 2 (SEQC2) consortium published these articles from three hundred collaborating participants within more than 150 organizations spanning academia, industry, hospitals, and federal agencies. The September NBT collection includes other successful SEQC2 research articles that appeared earlier this year in NBT, Genome Biology, and Genome Medicine.
The publications in this collection detail bioinformatic methods, metrics, reference samples, recommendations, and protocols when using next-gen sequencing in the research, clinical or regulatory setting, especially in oncology, that lead to more reproducible results. For sequencing-community members wishing to construct or pressure-test the robustness of sequencing pipelines, this collection describes publicly available samples, data, and consensus results and recommendations. In addition, the collection provides a sweeping assessment of experimental and algorithmic sequencing methods. In addition to scientific research articles, the collection features an editorial by Marc Salit, Director of Joint Initiative for Metrology in Biology at SLAC National Accelerator Laboratory, and Janet Woodcock, Acting Commissioner of the U.S. FDA regarding the historical and current impact of MAQC Society member efforts.
Publications in Collection
- Salit, M. & Woodcock, J. MAQC and the era of genomic medicine. Nat. Biotechnol. 1–2 (2021).
- Xiao, W. et al. Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing. Nat. Biotechnol. 1–10 (2021).
- Fang, L. T. et al. Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing. Nat. Biotechnol. 1–10 (2021).
- Chen, W. et al. A multicenter study benchmarking single-cell RNA sequencing technologies using reference samples. Nat. Biotechnol. 1–12 (2020).
- Deveson, I. W. et al. Evaluating the analytical validity of circulating tumor DNA sequencing assays for precision oncology. Nat. Biotechnol. 1–14 (2021).
- Foox, J. et al. Performance assessment of DNA sequencing platforms in the ABRF Next-Generation Sequencing Study. Nat. Biotechnol. 39, 1129–1140 (2021).
- Chen, X. et al. A multi-center cross-platform single-cell RNA sequencing reference dataset. Sci. Data 8, 39 (2021).
- Gong, B. et al. Cross-oncopanel study reveals high sensitivity and accuracy with overall analytical performance depending on genomic regions. Genome Biol. 22, 109 (2021).
- Jones, W. et al. A verified genomic reference sample for assessing performance of cancer panels detecting small variants of low allele frequency. Genome Biol. 22, 111 (2021).
- Zhang, L. et al. X-CNV: genome-wide prediction of the pathogenicity of copy number variations. Genome Med. 13, 132 (2021).
About the MAQC Society
The goal of the MAQC Society is to communicate, promote, and advance reproducible science principles and quality control for analysis of the massive data generated from the existing and emerging technologies in solving biological, health, and medical problems. Specifically, the society seeks to advocate and facilitate the development and application of quality control practices and standard analysis protocols of bioinformatics and biostatistics for enhanced reproducibility across multiple experiments, laboratories, and data analysis methods. In addition, the MAQC Society seeks to advance our understanding and best practices in the analysis of massive data from emerging technologies applied in drug development, clinical application, and safety/risk assessment.
SOURCE MAQC Society
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