GENOMICON-Seq simulations
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB81738 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Microarray technology was used to assess transcriptome changes in poplar (Populus alba L.) under a realistic simulation of increased UV-B radiation. Plants were UV-Bbe (UV-B biologically effective radiation) supplemented with a dose of 6 kJ/m2/day for 12 hours per day and allowed to recover during the night. Poplar plants were UV-B treated using a refined controlled environment able to guarantee a realistic simulation of natural conditions, especially for light parameters such as presence of background UV-B radiation for control plants and balanced PAR/UV-A/UV-B ratio. A time course experiment was planned to look both at the rapid and delayed response of poplar to UVB; two time points after 3 h (T3h) and 30 h (6th hour of the third day of treatment, T30h) were considered. 4 independent biological replicates were analysed for each time point. Competitive hybridisations were carried out using the PICME 28K microarray. Keywords: Time course experiment, stress response Two condition experiment: UVB supplemented plants vs normal UV-B level plants. Biological replicates: 4 UVB suplemented plants, 4 control plants, two time points, one replicate per array. Dye swap between replicates.
2013-12-01 | E-GEOD-9470 | biostudies-arrayexpress
Project description:With its capacity for high-resolution data output in one region of interest, chromosome conformation capture combined with high-throughput sequencing (4C-seq) is a state-of-the-art next-generation sequencing technique that provides epigenetic insights, and regularly advances current medical research. However, 4C-seq data is complex and prone to biases, and while specialized programs exist, an unbiased, extensive benchmarking is still lacking. Furthermore, neither substantial datasets with fully characterized ground truth, nor simulation programs for realistic 4C-seq data have been published. We conducted a benchmarking study on 54 4C-seq samples from 12 datasets, including original murine BMM, T-cell, and 416B data, and developed a novel 4C-seq simulation software to allow for more detailed comparisons of 4C-seq algorithms on 50 simulated datasets with 10 to 120 samples each.
2019-05-29 | GSE123131 | GEO
Project description:Microarray technology was used to assess transcriptome changes in poplar (Populus alba L.) under a realistic simulation of increased UV-B radiation. Plants were UV-Bbe (UV-B biologically effective radiation) supplemented with a dose of 6 kJ/m2/day for 12 hours per day and allowed to recover during the night. Poplar plants were UV-B treated using a refined controlled environment able to guarantee a realistic simulation of natural conditions, especially for light parameters such as presence of background UV-B radiation for control plants and balanced PAR/UV-A/UV-B ratio. A time course experiment was planned to look both at the rapid and delayed response of poplar to UVB; two time points after 3 h (T3h) and 30 h (6th hour of the third day of treatment, T30h) were considered. 4 independent biological replicates were analysed for each time point. Competitive hybridisations were carried out using the PICME 28K microarray. Keywords: Time course experiment, stress response
2013-12-01 | GSE9470 | GEO
Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing. DNA copy number profiles of mouse squamous cell lung cancer (SCLC) were generated with ENCODER from whole exome sequencing data and compared to results from the NimbleGen array
2014-08-12 | E-GEOD-60254 | biostudies-arrayexpress
Project description:Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. Current methods for detection of copy number aberrations (CNA) from whole-exome sequencing (WES) data are based on the read counts of the captured exons only. However, accurate CNA determination is complicated by the non-uniform read depth and uneven distribution of exons. Therefore, we developed ENCODER (ENhanced COpy number Detection from Exome Reads), which eludes these problems. By exploiting the ‘off-target’ sequence reads, it allows for creation of robust copy number profiles from WES. The accuracy of ENCODER compares to approaches specifically designed for copy number detection, and outperforms current exon-based WES methods, particularly in samples of low quality. DNA copy number profiles generated with a new tool, ENCODER, were compared to DNA copy number profiles from SNP6, NimbleGen and low-coverage Whole Genome Sequencing. DNA copy number profiles of melanoma PDX sample were generated with ENCODER from whole exome sequencing data and compared to results from the SNP6 platform.
2014-08-12 | E-GEOD-60168 | biostudies-arrayexpress
Project description:Illumina human Omni5Exome arrays were used to investigate CNVs in SÑzary syndrome tumours as part of a larger study involving whole exome sequencing of the same samples and targeted resequencing of a further cohort. 16 Samples underwent SNP array including 10 tumour/gDNA matched samples that also underwent whole exome sequencing, public databases were used as further control data for calling CNVs.
2016-07-22 | E-GEOD-80650 | biostudies-arrayexpress
Project description:Agilent whole exome hybridisation capture was performed on genomic DNA derived from Chondrosarcoma cancer and matched normal DNA from the same patients. Next Generation sequencing performed on the resulting exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes. Now we aim to re find and validate the findings of those exome libraries using bespoke pulldown methods and sequencing the products.
2016-05-17 | E-ERAD-37 | biostudies-arrayexpress
Project description:Whole exome sequencing of 5 MDS/MPN patients to identify the target of chromosome 22 acquired uniparental disomy (22aUPD). For samples E4051 and E6523, peripheral blood leucocytes (tumour) and cultured T-cells (germline) were prepared for exome sequencing using the Agilent SureSelect kit (Agilent Technologies, Palo Alto, CA, USA) (Human All Exon 50 Mb) and then sequenced on an Illumina HiSeq 2000 (Illumina, Great Abington, UK) at the Wellcome Trust Centre for Human Genetics, Oxford, UK. For samples ULSAM1182, ULSAM1242 and ULSAM1356, peripheral blood leukocyte DNA only were exome sequenced by SciLifeLab (Stockholm, Sweden).
2019-01-22 | E-MTAB-7491 | biostudies-arrayexpress
Project description:Purpose: There are three goals of this study: 1. To compare the genomic, exome and chromatin accessiblity profiles of the specific engineered fallopian tube cells of high-grade serous tubo-ovarian cancer (HGSC) models (this study) using whole-exome, whole-genome and ATAC-seq sequencing. Methods: For whole-exome analysis, genomic DNA was extracted from the cell lines mentioned below. Conclusions: We conclude that whole-exome, whole-genome and ATAC-seq characterization would expedite genetic network analyses and permit the dissection of complex biological functions.
2020-11-17 | GSE159253 | GEO
Project description:Interventions: NA:No
Primary outcome(s): Whole exome;PFS
Study Design: Cross-sectional
| 47576 | ecrin-mdr-crc