Ontology highlight
ABSTRACT:
PROVIDER: PRJNA511747 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:A CNV map in pigs could facilitate the identification of chromosomal regions that segregate for important economic and disease phenotypes. The goal of this study was to identify CNV regions (CNVRs) in pigs based on a custom array comparative genome hybridization (aCGH). We carried out a custom-made array comparative genome hybridization (aCGH) experiment in order to identify copy number variations (CNVs) in the pig genome analysing animals of diverse pig breeds (White Duroc, Yangxin, Erhualian, Tongcheng, Large White, Pietrain, Landrace and Chinese new pig line DIV ) using a tiling oligonucleotide array with ~720,000 probes designed on the pig genome (Sus scrofa genome version 9.0). In this study, a custom-made tiling oligo-nucleotide 720k array was used with a median probe spacing of 2506 bp for screening 12 pigs with a female Duroc as the reference. WD: White Duroc (♀); YX: Yangxin (♂); EH: Erhualian (♀); TC: Tongcheng (♀); LW: Large White (♀); PT: Pietrain (♂); LD1: Landrace × DIV pig 1 (♂); LD2: Landrace × DIV pig 2 (♀); DIV1: Chinese new pig line DIV 1 (♀); DIV2: Chinese new pig line DIV 2 (♀); L1: Landrace 1 (♂); L2: Landrace 2 (♂).
2013-08-09 | E-GEOD-41488 | biostudies-arrayexpress
Project description:The gene expression profiles associated with tenderization in body wall of sea cucumber (Apostichopus japonicus) were determined
2019-03-27 | GSE123077 | GEO
Project description:Data showing the late 2-cell-stage, control embryos (Imp2♀+/♂+) and Imp2-knockout embryos (Imp2♀−/♂+) for HPLC MS/MS analysis. 3 replicates were performed using 330 embryos per group.
2019-11-12 | PXD010397 | Pride
Project description:Gene expression profiles were generated from muscle biopsies from 134 individuals, and differences in expression based on sex were explored. Top differentially expressed gene lists are often inconsistent between studies and it has been suggested that small sample sizes contribute to lack of reproducibility and poor prediction accuracy in discriminative models. We considered sex differences (69♂, 65♀) in 134 human skeletal muscle biopsies using DNA microarray. The full dataset and subsamples (n= 10 (5♂, 5♀) to n=120 (60♂, 60♀)) thereof were used to assess the effect of sample size on the differential expression of single genes, gene rank order and prediction accuracy. Using our full dataset (n=134), we identified 717 differentially expressed transcripts (p-value < 0.0001; false discovery rate < 0.006) and we were able to predict sex with 92% accuracy, both within our dataset and on external datasets. Both p-values and rank order of top differentially expressed genes became more variable using smaller subsamples. For example, at n=10 (5♂, 5♀), no gene was considered differentially expressed at p<0.0001 and prediction accuracy was ~50% (no better than chance). We found that sample size clearly affects microarray analysis results; small sample sizes result in unstable gene lists and poor prediction accuracy. We anticipate this will apply to other phenotypes, in addition to sex.
2014-05-15 | GSE41726 | GEO