MAQC
Massive Analysis and Quality Control Society.
The objective 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. Thus, the goals of the Society are to
(1) advocate and facilitate the development and application of quality control practice and standard analysis protocols of bioinformatics and biostatistics for enhanced reproducibility across multiple experiments, laboratories, and data analysis methods, and
(2) 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.
Nature Biotechnology Special Collection
Publications in Collection
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Salit, M. & Woodcock, J. MAQC and the era of genomic medicine. Nat. Biotechnol. 1–2 (2021).
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Xiao, W. et al. Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing. Nat. Biotechnol. 1–10 (2021).
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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).
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Chen, W. et al. A multicenter study benchmarking single-cell RNA sequencing technologies using reference samples. Nat. Biotechnol. 1–12 (2020).
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Deveson, I. W. et al. Evaluating the analytical validity of circulating tumor DNA sequencing assays for precision oncology. Nat. Biotechnol. 1–14 (2021).
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Foox, J. et al. Performance assessment of DNA sequencing platforms in the ABRF Next-Generation Sequencing Study. Nat Biotechnol. 39, 1129–1140 (2021).
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Chen, X. et al. A multi-center cross-platform single-cell RNA sequencing reference dataset. Sci. Data 8, 39 (2021).
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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).
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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).
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Zhang, L. et al. X-CNV: genome-wide prediction of the pathogenicity of copy number variations. Genome Med. 13, 132 (2021).
Congratulations to our MAQC 2021 award winners!
MAQC Research Awards (Young Scientist):
- 3rd place: Nicole Bussola
- 2nd place: Ramyar Molania
- 1st place: Ira Deveson
MAQC Research Awards (Scientist):
- 3rd place: Michael Love
- 2nd place: Mohammad Sahraeian
- 1st place: Li Tai Fang
Outstanding Reproducibility in Science Award
- Runner Up: Tsuyoshi Miyakawa
- Winner: Davide Chicco
MAQC Society Award
- Runner Up: Benjamin Haibe-Kains
- Winner: Charles Wang
MAQC Society Board names Dr. Weida Tong as Chair Emeritus
