Mezmaiskaya1
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB21195 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:A 30-fold coverage Vindija Neandertal genome from Croatia
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Project description:Neandertal Sidron Capture project
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Project description:In principle, whole-genome sequencing (WGS) of the human genome even at low coverage offers higher resolution for genomic copy number variation (CNV) detection compared to array-based technologies, which is currently the first-tier approach in clinical cytogenetics. There are, however, obstacles in replacing array-based CNV detection with that of low-coverage WGS such as cost, turnaround time, and lack of systematic performance comparisons. With technological advances in WGS in terms of library preparation, instrument platforms, and data analysis algorithms, obstacles imposed by cost and turnaround time are fading. However, a systematic performance comparison between array and low-coverage WGS-based CNV detection has yet to be performed. Here, we compared the CNV detection capabilities between WGS (short-insert, 3kb-, and 5kb-mate-pair libraries) at 1X, 3X, and 5X coverages and standardly used high-resolution arrays in the genome of 1000-Genomes-Project CEU genome NA12878. CNV detection was performed using standard analysis methods, and the results were then compared to a list of Gold Standard NA12878 CNVs distilled from the 1000-Genomes Project. Overall, low-coverage WGS is able to detect drastically more (approximately 5 fold more on average) Gold Standard CNVs compared to arrays and is accompanied with fewer CNV calls without secondary validation. Furthermore, we also show that WGS (at ≥1X coverage) is able to detect all seven validated deletions larger than 100 kb in the NA12878 genome whereas only one of such deletions is detected in most arrays. Finally, we show that the much larger 15 Mbp Cri-du-chat deletion can be clearly seen at even 1X coverage from short-insert WGS.
2018-06-26 | GSE105092 | GEO
Project description:In order to validate of CNV detection from low-coverage whole-genome sequencing in the blood samples from recurrent miscarriage couples, we employed a customized array Comparative Genomics Hybridization (aCGH, Agilent) approach as chromosomal microarray analysis (CMA) in present study for a cohort of 78 DNA samples from blood. CMA results were compared with low-coverage whole-genome sequencing detection results. 100% consistency was obtained in pathogenic or likely pathogenic CNVs detection.
2017-11-01 | GSE83941 | GEO
Project description:Low coverage whole-genome sequencing have been performed on uterine leiomyosarcoma to uncovered novel potential driver genes and recurrently affected pathways.
2018-07-02 | E-MTAB-5763 | biostudies-arrayexpress
Project description:Neandertal Amino Acid Capture project
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Project description:Neandertal and Denisovan Y Chromosomes
| PRJEB39390 | ENA
Project description:Whole-genome DNA libraries were prepared from a population of just under 100 Col/Ler F1 backcrossed to Col. Low-coverage whole-genome sequencing was used to map meiotic crossovers in this population following the protocol described in Rowan et al., 2015, doi: 10.1534/g3.114.016501.
2015-10-15 | E-MTAB-3926 | biostudies-arrayexpress
Project description:Microarray-based enrichment of selected genomic loci is a powerful method for genome complexity reduction. Since the vast majority of exons in vertebrate genomes are smaller than 150 nt, we have explored the use of short fragment libraries (85-110bp) to achieve higher enrichment specificity by reducing carryover and adverse effects of flanking intronic sequences. These short fragment libraries were enriched for 1.69 Mb of exonic sequences, using custom 244K microarrays, and sequenced using AB/SOLiD. High enrichment specificity (60 M-bM-^@M-^S 75%) was obtained at 67-213x average coverage, with 77-92% and 90-98% of targeted regions covered with more than 25% and 10% of the average coverage, respectively. As a more appropriate measure of the evenness of coverage, which is relatively independent of sequencing depth, we introduce the evenness of coverage parameter E. E values up to 75% were achieved. To verify the accuracy of SNP/mutation detection we evaluated 384 known non-reference SNPs in the targeted regions. At ~ 200x average sequence coverage, we were able to survey 96.4% of 1.69 Mb of genomic sequence with only 4.2% false negative calls while 3.6% of targeted regions were marked as unsurveyed. A total of 1197 new variants were detected. Verification revealed only 8 false positive calls, resulting in an overall false positive rate of less than 1 per ~200,000 bp (0.0005%, equivalent to an overall phred score of 55). 4 samples + capture design file
2010-02-01 | E-GEOD-18542 | biostudies-arrayexpress