Sentence examples for practices data processing from inspiring English sources

Exact(1)

Analysis-ready BAM files were generated for both MiSeq and HiSeq with the best practices data processing pipeline (BWA alignment, Picard's Mark Duplicates, GATK's Base Quality Score Recalibration, and GATK's Indel Realignment).

Similar(59)

The purpose of the present work is to report the optimization of several steps in the microarray process both in laboratory practices and in data processing using criteria that do not rely on external standards.

One major area of discussion was best practices of statistical data processing and analysis.

For ChIP-chip analyses, details should be provided for how H3K9me2 profiles were obtained and the methods utilized should conform with normally accepted practices for microarray data processing and presentation.

Commenting about Facebook's data practices, Michael Veale, a researcher in data rights and machine learning at University College London, told us: "Many of Facebook's data processing practices appear to violate user expectations, and the way they interpret the law in Europe is indicative of their concern around this.

Data processing practices are evolving faster than the law can adapt to them, according to a senior British lawyer at an international law firm specialising in data protection.

Here, we review the best practices for deployment, calibration, and data processing and quality control, using our experience with Durafet®-based pH sensors as a model.

Although the IBM team declared their "results open up possibilities of achieving practical graphene technology with more complex functionality," in practice, getting the kind of data processing that goes on in silicon chips requires devising transistor circuits that can turn current on and off digitally.

Results show that the methods proposed in this paper support the accuracy evaluation targeted point cloud data processing efficiently in practice.

Clinical decision support systems (CDSSs) aim to codify and strategically manage biomedical knowledge to handle challenges in clinical practice using mathematical modelling tools, medical data processing techniques, and artificial intelligence methods.

The MicroArray Quality Control (MAQC) Consortium [ 58] suggests the use of a fold-change cut off along with a non-stringent p-value cut off as a baseline practice to improve reproducibility in microarray data processing.

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