Ontology highlight
ABSTRACT:
PROVIDER: PRJNA786064 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR17188832_1.fastq.gz | Fastqsanger.gz | |||
| SRR17188832_2.fastq.gz | Fastqsanger.gz | |||
| SRR17188833_1.fastq.gz | Fastqsanger.gz | |||
| SRR17188833_2.fastq.gz | Fastqsanger.gz | |||
| SRR17188834_1.fastq.gz | Fastqsanger.gz |
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Project description:Single-cell human genome analysis using whole-genome amplified product is hampered by allele bias during amplification. Using an oligonucleotide SNP array, we examined the nature of the allele bias and its effect on the chromosomal copy number analysis. Keywords: single cell, copy number analysis, whole genome amplification, brain
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Project description:The genomic DNA of rearranged chromosome VIII (~900kb) of EC9 diploid strain was extracted from the gel of pulsed field gel electrophoresis (PFGE), and analyzed by array-CGH to identify it's amplified regions After PFGE, The ChrVIII DNA was purified from agarose gel and purified by column. Then the DNA was amplified by GenomePlex Whole Genome Amplification Kit for Array-comparative genomic hybridization.
2012-05-17 | E-GEOD-38034 | biostudies-arrayexpress
Project description:The genomic DNA of wild-type chromosome VIII of evolved EC9-7 cells was extracted from the gel of pulsed field gel electrophoresis (PFGE), and analyzed by array-CGH to identify its chromosomal composition Yeast genomic DNA was extracted using QIAGEN Genomic-tip 100/G kit. After PFGE, The ChrVIII DNA was purified from agarose gel and purified by column. Then the DNA was amplified by GenomePlex Whole Genome Amplification Kit.
2011-11-13 | E-GEOD-33652 | biostudies-arrayexpress
Project description:Background: Insufficient quantities of human genomic DNA are a limiting factor for many clinical applications. Whole genome amplification (WGA) is an approach designed to overcome small amount of DNA for genome-wide genetic tests as it allows amplification of the entire genome from picogram or nanogram quantities of DNA. Various strategies of WGA have been developed; however, none of them can guarantee the absence of amplification bias. High-quality genome-representative amplified DNA is crucial for WGA use in basic research and clinical genetics. Thus, systematic evaluation of WGA effect on downstream methods is necessary. Results: In this paper, 4 multiple displacement amplification (MDA) -based and 2 PCR-based WGA kits were compared in their effect on segmental copy-number changes as well as copy-number neutral loss of heterozygosity detection by high-density oligonucleotide DNA arrays. We described outcomes and limits for each individual WGA; however, the main goal of this study was chiefly to show a general compatibility and features specific for particular WGA strategy. The main outcomes are as follows: 1) MDA-based WGAs showed higher tendency to generate false positive imbalances in contrast to PCR-based WGAs with higher risk of false negativity; 2) the specific risk of false positivity and/or negativity increased with decreasing copy-number segments size; 3) single-cell WGAs showed significantly worse effect on results in comparison to WGAs with nanogram level of DNA as input; 4) PCR-based WGAs were not compatible with copy-number neutral loss of heterozygosity analysis based on single nucleotide polymorphisms in restriction digestion sites and also showed higher risk of copy-number neutral loss of heterozygosity false negativity if combined with analysis based on simple hybridization. Conclusions: This study gives a comprehensive insight into the WGA effect on DNA array analysis. The results of this study help to choose WGA according to individual user requirements and options. Moreover, we show a strategy to verify and validate segmental copy-number changes detection by DNA array protocol including any WGA for any purpose to attain the highest efficiency without an unnecessary WGA bias.
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Project description:Several recent studies have suggested that genes that are longer than 100 kb are more likely to be misregulated in neurological diseases associated with synaptic dysfunction, such as autism and Rett syndrome. These length-dependent transcriptional changes are modest in Mecp2 mutant samples, but, given the low sensitivity of high-throughput transcriptome profiling technology, the statistical significance of these results needs to be re-evaluated. Here, we show that the apparent length-dependent trends previously observed in MeCP2 microarray and RNA-Sequencing datasets, particularly in genes with low-fold changes, disappeared when compared to randomized control samples. As we found no similar bias with Nanostring technology, this bias seems to be particular to PCR amplification-based platforms. Transcriptional alterations with large fold-change values, however, can reveal an authentic long gene bias. Discriminating authentic from artefactual length-dependent trends requires establishing a baseline from randomized control samples.
2018-06-05 | GSE105046 | GEO
Project description:Several recent studies have suggested that genes that are longer than 100 kb are more likely to be misregulated in neurological diseases associated with synaptic dysfunction, such as autism and Rett syndrome. These length-dependent transcriptional changes are modest in Mecp2 mutant samples, but, given the low sensitivity of high-throughput transcriptome profiling technology, the statistical significance of these results needs to be re-evaluated. Here, we show that the apparent length-dependent trends previously observed in MeCP2 microarray and RNA-Sequencing datasets, particularly in genes with low-fold changes, disappeared when compared to randomized control samples. As we found no similar bias with Nanostring technology, this bias seems to be particular to PCR amplification-based platforms. Transcriptional alterations with large fold-change values, however, can reveal an authentic long gene bias. Discriminating authentic from artefactual length-dependent trends requires establishing a baseline from randomized control samples.
2018-06-05 | GSE105045 | GEO
Project description:Several recent studies have suggested that genes that are longer than 100 kb are more likely to be misregulated in neurological diseases associated with synaptic dysfunction, such as autism and Rett syndrome. These length-dependent transcriptional changes are modest in Mecp2 mutant samples, but, given the low sensitivity of high-throughput transcriptome profiling technology, the statistical significance of these results needs to be re-evaluated. Here, we show that the apparent length-dependent trends previously observed in MeCP2 microarray and RNA-Sequencing datasets, particularly in genes with low-fold changes, disappeared when compared to randomized control samples. As we found no similar bias with Nanostring technology, this bias seems to be particular to PCR amplification-based platforms. Transcriptional alterations with large fold-change values, however, can reveal an authentic long gene bias. Discriminating authentic from artefactual length-dependent trends requires establishing a baseline from randomized control samples.
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