Dataset Information

High quality variant calls from multiple dog genome project - Run2

ABSTRACT: Dog Biomedical Variant Database Consortium (DBVDC) was established to aggregate whole genome sequencing data from a variety of projects examining dog biomedical and morphological phenotypes.The VCF was produced using the BWA-GATK best practices pipeline.

INSTRUMENT(S): Illumina NovaSeq 6000, Illumina HiSeq 2500

ORGANISM(S): Canis Lupus Familiaris

SUBMITTER: Unibe

PROVIDER: PRJEB32865 | EVA | 2019-06-11

REPOSITORIES: EVA

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Dataset's files

Source:

			Action	DRS
	dogs.590publicSamples.accessioned.vcf.gz	Vcf
	dogs.590publicSamples.accessioned.vcf.gz.csi	Vcf
	dogs.590publicSamples.accessioned.vcf.gz.tbi	Vcf
	dogs.590publicSamples.vcf.gz	Vcf
	dogs.590publicSamples.vcf.gz.tbi	Vcf

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Project description:The foundation for integrating mass spectrometry (MS)-based proteomics into systems medicine is to develop standardized start-to-finish and fit-for-purpose workflows for clinical specimens. An essential step in this pursuit is to highlight common ground in a diverse landscape of different sample preparation techniques and LC-MS setups with the aim to explore differences and potential confounding factors as well as to identify areas for improvement with a direct practical benefit. With the aim to benchmark and improve current best practices among the proteomics MS laboratories of the CLINSPECT-M consortium we performed two consecutive round robin studies with full freedom to operate in terms of sample preparation and MS measurements. The six participating study partners were provided with two clinically relevant sample matrices: plasma, and cerebrospinal fluid (CSF). In the first round each laboratory applied their current best practice protocol for the respective matrix, covering laboratory-specific sample proteolysis, liquid chromatography, and MS measurement procedure. All resulting MS files were analyzed centrally by a standardized pipeline. Based on the achieved results and following a fully transparent exchange of all lab-specific protocols within the consortium, each laboratory could improve their methods before measuring the same samples in a second acquisition round. The results of both measurement time points are compared with respect to identifications (IDs), data completeness, retention time and quantitative precision as well as inter-laboratory reproducibility. For instance, the number of identified protein groups was increased on average by 14% for CSF and 5% for plasma from first to second measurement round across participants resulting in a median overlap number of 579 protein groups for CSF and 246 IDs for plasma across setups. The individual performances of participating study centers and the inter-laboratory reproducibility were improved in the second measurement, emphasizing the effect and importance of expert-driven exchange of best practices. In total, the study not only clearly demonstrates the beneficial effect of sharing knowledge and expertise for direct practical improvements but also highlights tendencies such as common limits of detection or preferable preparation strategies.

Dataset Information

High quality variant calls from multiple dog genome project - Run2

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