Quality control analysis of the 1000 Genomes Project Omni2.5 genotypes
Notice bibliographique
Résumé
Citation For any use of the 1000 Genomes Project data, please use the citation as noted here: http://www.1000genomes.org/faq/how-do-i-cite-1000-genomes-project . To cite this report or the lists described here, please use the following: Roslin NM, Li W, Paterson AD, Strug LJ. Quality control analysis of the 1000 Genomes Project Omni2.5 genotypes (Abstract/Program #576/F). Presented at the 66 th Annual Meeting of The American Society of Human Genetics, October 18-22, 2016, Vancouver, Canada. Data Summary Chips : IlluminaHumanOmni2.5-4v1_B and Illumina HumanOmni25M-8v1-1_B Initial number of SNPs : 2 458 861 Initial number of samples : 2318 Number of SNPs passing QC : 1 989 184 (80.9%) Number of samples passing QC : 2318 (100%) Number of quasi-unrelated samples with consistent ethnicity and well inferred sex : 1736 Abstract The 1000 Genomes Project genotype 2318 individuals (48.1% male) from 19 populations in 5 continental groups on the Illumina Omni2.5 platform. The data are publicly available, and will prove a valuable resource to obtain ethnic-specific allele frequencies, as well as exploring population histories through principal components analysis (PCA), estimation of inbreeding coefficients, and admixture analysis. As in any study, the data should be cleaned prior to analysis, to remove individuals or markers of questionable quality. Furthermore, a thorough understanding of the relationships between individuals must be established. Here we report our findings after comprehensive examination of the data for quality control. The basic quality of the genotypes was assessed using standard procedures. KING version 1.4 was used to confirm the relationships in the provided pedigrees, and also to detect undeclared relationships. PCA was used to examine the similarities and differences between individuals among and between population groups. In general, the data was found to be of high quality. No samples were removed due to low call rate (<97%) or excess heterozygosity. Sex chromosome genotypes showed two individuals with discrepancies between reported and inferred sex, and were unable to determine sex in an additional 20 individuals; the sex for these was changed to unknown. Relationship checking found discrepancies between first-degree relationships in the provided pedigrees and the genotypes in 9 families, including one instance where a reported parent/child pair was unrelated, two instances where full sibs were unrelated, and one set of three individuals who formed a newly defined trio. A set of 1756 individuals who were inferred to be more distant than 3 rd degree relatives was extracted and used in PCA. These individuals clustered in a pattern that is consistent with other published reports of global populations. We identified 4 individuals whose genotypes clustered more closely with a different geographic region than the one in the provided data. Although the genotype data is of high quality, errors exist in the publicly available dataset that require attention prior to using the genotypes. PLINK-format files including SNPs with good quality metrics and revised pedigree structures is available at http://tcag.ca . Files with distantly related or unrelated individuals, with sex inference consistent with provided gender, and with PCA consistent with continental group are also available.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».