Ontology highlight
ABSTRACT:
PROVIDER: PRJNA726033 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14354884_1.fastq.gz | Fastqsanger.gz | |||
| SRR14354884_2.fastq.gz | Fastqsanger.gz | |||
| SRR14354885_1.fastq.gz | Fastqsanger.gz | |||
| SRR14354885_2.fastq.gz | Fastqsanger.gz | |||
| SRR14354886_1.fastq.gz | Fastqsanger.gz |
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Project description:Chromosomal copy number variations (CNV) have been associated with various neurological and developmental disorders and chromosomal microarray (CMA) is a method of choice to diagnose Copy Number Gain/Loss syndromes. Recently, next-generation sequencing (NGS)-based low-coverage whole genome sequencing (LC-WGS) has been applied to detect Copy Number Gain/Loss syndromes. This dataset is intended to be used as a “Golden standard data set” for development of LC-WGS analysis method. It consists of patients (n=63) who have a mental delay and/or physical disability phenotype and normal (n=20) phenotype.
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Project description:Structural variations (SVs) contribute significantly to the variability of the human genome and extensive genomic rearrangements are a hallmark of cancer. Genomic DNA paired-end-tag (DNA-PET) sequencing is an attractive approach to identify genomic SVs. The current application of PET sequencing with short insert size DNA is insufficient for the comprehensive mapping of SVs in low complexity and repeat-rich genomic regions. We have developed a robust procedure to generate PET sequencing data using large DNA inserts of 10 - 20 kb for the identification of SVs. We compared the characteristics of the large insert libraries with short insert (1 kb) libraries with the same sequencing depths and costs. Although short insert libraries bear an advantage in identifying small deletions, they do not provide a significantly better breakpoint resolution. Large inserts are superior to short inserts in providing higher physical genome coverage and therefore achieve greater sensitivity for the identification of the different types of SVs, including copy number neutral and complex events. Further, large inserts allow the identification of SVs within repetitive sequences which cannot be spanned by short inserts. Structural variations of three cancer cell lines using short (1 kb) and long (10 kb and 20 kb) insert size DNA fragments
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Project description:Screening for gene copy-number alterations (CNAs) has improved by applying genome-wide microarrays, where SNP arrays also allow analysis of loss of heterozygozity (LOH). We here analyzed 10 chronic lymphocytic leukemia (CLL) samples using four different high-resolution platforms: BAC arrays (32K), oligonucleotide arrays (185K, Agilent), and two SNP arrays (250K, Affymetrix and 317K, Illumina). Cross-platform comparison revealed 29 concordantly detected CNAs, including known recurrent alterations, which confirmed that all platforms are powerful tools when screening for large aberrations. However, detection of 32 additional regions present in 2-3 platforms illustrated a discrepancy in detection of small CNAs, which often involved reported copy-number variations. LOH analysis revealed concordance of mainly large regions, but showed numerous, small nonoverlapping regions and LOH escaping detection. Evaluation of baseline variation and copy-number ratio response showed the best performance for the Agilent platform and confirmed the robustness of BAC arrays. Accordingly, these platforms demonstrated a higher degree of platform-specific CNAs. The SNP arrays displayed higher technical variation, although this was compensated by high density of elements. Affymetrix detected a higher degree of CNAs compared to Illumina, while the latter showed a lower noise level and higher detection rate in the LOH analysis. Large-scale studies of genomic aberrations are now feasible, but new tools for LOH analysis are requested.
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Project description:Structural variations (SVs) contribute significantly to the variability of the human genome and extensive genomic rearrangements are a hallmark of cancer. Genomic DNA paired-end-tag (DNA-PET) sequencing is an attractive approach to identify genomic SVs. The current application of PET sequencing with short insert size DNA is insufficient for the comprehensive mapping of SVs in low complexity and repeat-rich genomic regions. We have developed a robust procedure to generate PET sequencing data using large DNA inserts of 10 - 20 kb for the identification of SVs. We compared the characteristics of the large insert libraries with short insert (1 kb) libraries with the same sequencing depths and costs. Although short insert libraries bear an advantage in identifying small deletions, they do not provide a significantly better breakpoint resolution. Large inserts are superior to short inserts in providing higher physical genome coverage and therefore achieve greater sensitivity for the identification of the different types of SVs, including copy number neutral and complex events. Further, large inserts allow the identification of SVs within repetitive sequences which cannot be spanned by short inserts.
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Project description:Screening for gene copy-number alterations (CNAs) has improved by applying genome-wide microarrays, where SNP arrays also allow analysis of loss of heterozygozity (LOH). We here analyzed 10 chronic lymphocytic leukemia (CLL) samples using four different high-resolution platforms: BAC arrays (32K), oligonucleotide arrays (185K, Agilent), and two SNP arrays (250K, Affymetrix and 317K, Illumina). Cross-platform comparison revealed 29 concordantly detected CNAs, including known recurrent alterations, which confirmed that all platforms are powerful tools when screening for large aberrations. However, detection of 32 additional regions present in 2-3 platforms illustrated a discrepancy in detection of small CNAs, which often involved reported copy-number variations. LOH analysis revealed concordance of mainly large regions, but showed numerous, small nonoverlapping regions and LOH escaping detection. Evaluation of baseline variation and copy-number ratio response showed the best performance for the Agilent platform and confirmed the robustness of BAC arrays. Accordingly, these platforms demonstrated a higher degree of platform-specific CNAs. The SNP arrays displayed higher technical variation, although this was compensated by high density of elements. Affymetrix detected a higher degree of CNAs compared to Illumina, while the latter showed a lower noise level and higher detection rate in the LOH analysis. Large-scale studies of genomic aberrations are now feasible, but new tools for LOH analysis are requested. 10 chronic lymphocytic leukemia (CLL) samples was analyzed using four different high-resolution platforms: 32K BAC arrays, 185K Agilent oligonucleotide arrays, 250K Affymetrix SNP arrays and 317K Illumina SNP arrays.
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Project description:Copy number analysis by low coverage whole genome sequencing using ultra low-input DNA from formalin-fixed paraffin embedded tumour tissue
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Project description:Human nontransformed retinal pigment epithelia RPE-PPM1D-T2 cells carrying a truncating mutation in exon 6 of the PPM1D were exposed to ionising radiation (3 Gy) and subsequently were grown in semisolid media for 8 weeks. Six spheroid clones (RPE-PPM1D-T2-SA clones 1-6) were recovered and then were cultivated in adherent conditions. DNA was isolated from asynchronically growing parental RPE-PPM1D-T2 and transformed RPE-PPM1D-T2-SA-1 to 6 cells and was subjected to whole exome sequencing. DNA sequencing libraries were prepared using KAPA EvoPlus Kit (Roche) and were sequenced on the NovaSeq 6000 system using NovaSeq S1 Reagent Kit v1.5, 200 cycles (Illumina) with mean coverage >35 DNA samples, respectively. DNA fastq files were mapped to the hg19 reference using Novoalign (novoalign_2.08.03). PCR duplicates were removed from the BAM files using Picard Tools (picard-tools 1.129), and variant calling was performed using GATK HaplotypeCaller (3.8). Copy number variations (CNV) were analyzed using CNVkit version 0.7.4. Areas with median coverage >20 were included in the analysis. RNA fastq files were mapped to the hg19 reference using STAR (STAR-2.5.2b). The PCR duplicates were removed using Picard Tools (picard-tools 1.129).
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