Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA208732 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR902920_1.fastq.gz | Fastqsanger.gz | |||
| SRR902920_2.fastq.gz | Fastqsanger.gz | |||
| SRR902921_1.fastq.gz | Fastqsanger.gz | |||
| SRR902921_2.fastq.gz | Fastqsanger.gz | |||
| SRR902922_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 844 |
Similar Datasets
Project description:The ABRF Next-Generation Sequencing Study (ABRF-NGS): Multi-platform and cross-methodological reproducibility of transcriptome profiling by RNA-seq [Ion Torrent Proton]
| PRJNA208733 | ENA
Project description:The ABRF Next-Generation Sequencing Study (ABRF-NGS): Multi-platform and cross-methodological reproducibility of transcriptome profiling by RNA-seq [Ion Torrent PGM]
| PRJNA208735 | ENA
Project description:The ABRF Next-Generation Sequencing Study (ABRF-NGS): Multi-platform and cross-methodological reproducibility of transcriptome profiling by RNA-seq [454 GS FLX Titanium]
| PRJNA208734 | ENA
Project description:Next-generation sequencing (NGS) technology applications like RNA-sequencing (RNA-seq) have dramatically expanded the potential for novel genomics discoveries, but the proliferation of various platforms and protocols for RNA-seq has created a need for reference data sets to help gauge the performance characteristics of these disparate methods. Here we describe the results of the ABRF-NGS Study on RNA-seq, which leverages replicate experiments across multiple sites using two reference RNA standards tested with four protocols (polyA selected, ribo-depleted, size selected, and degraded RNA), and examined across five NGS platforms (IlluminaM-bM-^@M-^Ys HiSeqs, Life TechnologiesM-bM-^@M-^Y Personal Genome Machine and Proton, Roche 454 GS FLX, and Pacific Biosciences RS). These results show high (R2 >0.9) intra-platform consistency across test sites, high inter-platform concordance (R2 >0.8) for transcriptome profiling, and a large set of novel splice junctions observed across all platforms. Also, we observe that protocols using ribosomal RNA depletion can both salvage degraded RNA samples and also be readily compared to polyA-enriched fractions. These data provide a broad foundation for standardization, evaluation and improvement of RNA-seq methods. Two reference RNA standards tested with four protocols (polyA selected, ribo-depleted, size selected, and degraded RNA), and examined across five NGS platforms (IlluminaM-bM-^@M-^Ys HiSeqs, Life TechnologiesM-bM-^@M-^Y Personal Genome Machine and Proton, Roche 454 GS FLX, and Pacific Biosciences RS). Please note that the samples were named following the ABRF-Platform-Site-Sample-Replicate# format. For example, ABRF-454-CNL-A-1 means Sample A was run on 454 platform at Cornell and this is the first replicate, and ABRF-454-CNL-A-2 means the same exact sample was ran with same machine at same location and is 2nd replicate.
2014-05-14 | E-GEOD-48032 | biostudies-arrayexpress
Project description:Next-generation sequencing (NGS) technology applications like RNA-sequencing (RNA-seq) have dramatically expanded the potential for novel genomics discoveries, but the proliferation of various platforms and protocols for RNA-seq has created a need for reference data sets to help gauge the performance characteristics of these disparate methods. Here we describe the results of the ABRF-NGS Study on RNA-seq, which leverages replicate experiments across multiple sites using two reference RNA standards tested with four protocols (polyA selected, ribo-depleted, size selected, and degraded RNA), and examined across five NGS platforms (Illumina’s HiSeqs, Life Technologies’ Personal Genome Machine and Proton, Roche 454 GS FLX, and Pacific Biosciences RS). These results show high (R2 >0.9) intra-platform consistency across test sites, high inter-platform concordance (R2 >0.8) for transcriptome profiling, and a large set of novel splice junctions observed across all platforms. Also, we observe that protocols using ribosomal RNA depletion can both salvage degraded RNA samples and also be readily compared to polyA-enriched fractions. These data provide a broad foundation for standardization, evaluation and improvement of RNA-seq methods. Two reference RNA standards tested with four protocols (polyA selected, ribo-depleted, size selected, and degraded RNA), and examined across five NGS platforms (Illumina’s HiSeqs, Life Technologies’ Personal Genome Machine and Proton, Roche 454 GS FLX, and Pacific Biosciences RS). Please note that the samples were named following the ABRF-Platform-Site-Sample-Replicate# format. For example, ABRF-454-CNL-A-1 means Sample A was run on 454 platform at Cornell and this is the first replicate, and ABRF-454-CNL-A-2 means the same exact sample was ran with same machine at same location and is 2nd replicate.
2014-05-14 | E-GEOD-48035 | biostudies-arrayexpress
Project description:Next-generation sequencing (NGS) technology applications like RNA-sequencing (RNA-seq) have dramatically expanded the potential for novel genomics discoveries, but the proliferation of various platforms and protocols for RNA-seq has created a need for reference data sets to help gauge the performance characteristics of these disparate methods. Here we describe the results of the ABRF-NGS Study on RNA-seq, which leverages replicate experiments across multiple sites using two reference RNA standards tested with four protocols (polyA selected, ribo-depleted, size selected, and degraded RNA), and examined across five NGS platforms (Illumina’s HiSeqs, Life Technologies’ Personal Genome Machine and Proton, Roche 454 GS FLX, and Pacific Biosciences RS). These results show high (R2 >0.9) intra-platform consistency across test sites, high inter-platform concordance (R2 >0.8) for transcriptome profiling, and a large set of novel splice junctions observed across all platforms. Also, we observe that protocols using ribosomal RNA depletion can both salvage degraded RNA samples and also be readily compared to polyA-enriched fractions. These data provide a broad foundation for standardization, evaluation and improvement of RNA-seq methods. Two reference RNA standards tested with four protocols (polyA selected, ribo-depleted, size selected, and degraded RNA), and examined across five NGS platforms (Illumina’s HiSeqs, Life Technologies’ Personal Genome Machine and Proton, Roche 454 GS FLX, and Pacific Biosciences RS). Please note that the samples were named following the ABRF-Platform-Site-Sample-Replicate# format. For example, ABRF-454-CNL-A-1 means Sample A was run on 454 platform at Cornell and this is the first replicate, and ABRF-454-CNL-A-2 means the same exact sample was ran with same machine at same location and is 2nd replicate.
2014-05-14 | E-GEOD-48033 | biostudies-arrayexpress
Project description:Next-generation sequencing (NGS) technology applications like RNA-sequencing (RNA-seq) have dramatically expanded the potential for novel genomics discoveries, but the proliferation of various platforms and protocols for RNA-seq has created a need for reference data sets to help gauge the performance characteristics of these disparate methods. Here we describe the results of the ABRF-NGS Study on RNA-seq, which leverages replicate experiments across multiple sites using two reference RNA standards tested with four protocols (polyA selected, ribo-depleted, size selected, and degraded RNA), and examined across five NGS platforms (Illumina’s HiSeqs, Life Technologies’ Personal Genome Machine and Proton, Roche 454 GS FLX, and Pacific Biosciences RS). These results show high (R2 >0.9) intra-platform consistency across test sites, high inter-platform concordance (R2 >0.8) for transcriptome profiling, and a large set of novel splice junctions observed across all platforms. Also, we observe that protocols using ribosomal RNA depletion can both salvage degraded RNA samples and also be readily compared to polyA-enriched fractions. These data provide a broad foundation for standardization, evaluation and improvement of RNA-seq methods. Two reference RNA standards tested with four protocols (polyA selected, ribo-depleted, size selected, and degraded RNA), and examined across five NGS platforms (Illumina’s HiSeqs, Life Technologies’ Personal Genome Machine and Proton, Roche 454 GS FLX, and Pacific Biosciences RS). Please note that the samples were named following the ABRF-Platform-Site-Sample-Replicate# format. For example, ABRF-454-CNL-A-1 means Sample A was run on 454 platform at Cornell and this is the first replicate, and ABRF-454-CNL-A-2 means the same exact sample was ran with same machine at same location and is 2nd replicate.
2014-05-14 | E-GEOD-48034 | biostudies-arrayexpress
Project description:To survey transcriptome changes by the mutations of a DNA demethylase ROS1 responding to a phytohormone abscisic acid, we performed the Next-gen sequencing (NGS) associated RNA-seq analysis. Two ROS1 knockout lines (ros1-3, ros1-4; Penterman et al. 2007 [PMID: 17409185]) with the wild-type Col line (wt) were subjected. Three samples (ros1-3, ros1-4 and wt), biological triplicates, ABA or mock treatment, using Illumina HiSeq 2500 system
2016-01-15 | E-GEOD-65016 | biostudies-arrayexpress
Project description:The goal of this study is to investigate the effect of ABCB6 inhibition on the transcriptome level of melanoma cell line MNT-1. We performed next-generation sequencing (NGS) on both ABCB6 depleted MNT-1 cells (shABCB6) and unknocked control cells (CTRL). Illumina mRNA-seq sample preparation kit was used to perform paired-end library sequencing with Illumina HiSeq 2500 and sequence analysis was determined using the Illumina data analysis pipeline. Based on the comparison results，we performed the GO and KEGG pathway enrichment analysis. That might suggest the key role of ABCB6 in modulating melanocyte development.
2021-03-06 | GSE168345 | GEO