Ontology highlight
ABSTRACT:
PROVIDER: PRJNA429634 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR6464620.fastq.gz | Fastqsanger.gz | |||
| SRR6464630.fastq.gz | Fastqsanger.gz | |||
| SRR6464640.fastq.gz | Fastqsanger.gz | |||
| SRR6464650.fastq.gz | Fastqsanger.gz | |||
| SRR6464660.fastq.gz | Fastqsanger.gz |
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Project description:Analysis of RNA samples by massive parallel sequencing holds the promise to assay gene expression in both a quantitative and qualitative fashion and therefore allows for digital gene expression (DGE) profiling. We assessed the effect of different experimental approaches by generating small RNA libraries from a biological sample as well as an equimolar pool of synthetic miRNAs and analyzed the results using capillary dideoxy sequencing and next-generation sequencing platforms (Roche/454, AB/SOLiD and Illumina/Solexa). Whereas different sequencing platforms provided highly similar results, large differences in DGE profiles were observed depending on the library preparation method used. Nevertheless, our results indicate that the preferential nature of the library preparation methods is systematic and highly reproducible and we show that DGE is well suited for the quantification of relative expression differences between samples. This SuperSeries is composed of the following subset Series: GSE16369: Limitations and possibilities of small RNA digital gene expression profiling: library preparation comparison (454) GSE16370: Limitations and possibilities of small RNA digital gene expression profiling: library preparation comparison (SOLiD) GSE16371: Limitations and possibilities of small RNA digital gene expression profiling: spleen and liver comparison (SOLiD) GSE16372: Limitations and possibilities of small RNA digital gene expression profiling: synthetic miRNAs replicates (SOLiD) GSE16373: Limitations and possibilities of small RNA digital gene expression profiling: synthetic miRNA replicates (Illumina) Refer to individual Series
2009-07-28 | E-GEOD-16374 | biostudies-arrayexpress
Project description:Analysis of RNA samples by massive parallel sequencing holds the promise to assay gene expression in both a quantitative and qualitative fashion and therefore allows for digital gene expression (DGE) profiling. We assessed the effect of different experimental approaches by generating small RNA libraries from a biological sample as well as an equimolar pool of synthetic miRNAs and analyzed the results using capillary dideoxy sequencing and next-generation sequencing platforms (Roche/454, AB/SOLiD and Illumina/Solexa). Whereas different sequencing platforms provided highly similar results, large differences in DGE profiles were observed depending on the library preparation method used. Nevertheless, our results indicate that the preferential nature of the library preparation methods is systematic and highly reproducible and we show that DGE is well suited for the quantification of relative expression differences between samples. Keywords: Transcriptome analysis Examination of three different library preparation methods for small RNAs, two replicates per library method
2009-07-28 | E-GEOD-16370 | biostudies-arrayexpress
Project description:Analysis of RNA samples by massive parallel sequencing holds the promise to assay gene expression in both a quantitative and qualitative fashion and therefore allows for digital gene expression (DGE) profiling. We assessed the effect of different experimental approaches by generating small RNA libraries from a biological sample as well as an equimolar pool of synthetic miRNAs and analyzed the results using capillary dideoxy sequencing and next-generation sequencing platforms (Roche/454, AB/SOLiD and Illumina/Solexa). Whereas different sequencing platforms provided highly similar results, large differences in DGE profiles were observed depending on the library preparation method used. Nevertheless, our results indicate that the preferential nature of the library preparation methods is systematic and highly reproducible and we show that DGE is well suited for the quantification of relative expression differences between samples. Keywords: Transcriptome analysis Examination of three different library preparation methods for small RNAs, two replicates per library method
2009-07-28 | E-GEOD-16369 | biostudies-arrayexpress
Project description:Analysis of RNA samples by massive parallel sequencing holds the promise to assay gene expression in both a quantitative and qualitative fashion and therefore allows for digital gene expression (DGE) profiling. We assessed the effect of different experimental approaches by generating small RNA libraries from a biological sample as well as an equimolar pool of synthetic miRNAs and analyzed the results using capillary dideoxy sequencing and next-generation sequencing platforms (Roche/454, AB/SOLiD and Illumina/Solexa). Whereas different sequencing platforms provided highly similar results, large differences in DGE profiles were observed depending on the library preparation method used. Nevertheless, our results indicate that the preferential nature of the library preparation methods is systematic and highly reproducible and we show that DGE is well suited for the quantification of relative expression differences between samples. Keywords: Transcriptome analysis Examination library method on preparation of equimolar pool of miRNAs, three replicates
2009-07-28 | E-GEOD-16372 | biostudies-arrayexpress
Project description:Analysis of RNA samples by massive parallel sequencing holds the promise to assay gene expression in both a quantitative and qualitative fashion and therefore allows for digital gene expression (DGE) profiling. We assessed the effect of different experimental approaches by generating small RNA libraries from a biological sample as well as an equimolar pool of synthetic miRNAs and analyzed the results using capillary dideoxy sequencing and next-generation sequencing platforms (Roche/454, AB/SOLiD and Illumina/Solexa). Whereas different sequencing platforms provided highly similar results, large differences in DGE profiles were observed depending on the library preparation method used. Nevertheless, our results indicate that the preferential nature of the library preparation methods is systematic and highly reproducible and we show that DGE is well suited for the quantification of relative expression differences between samples. Keywords: Transcriptome analysis Examination library method on preparation of equimolar pool of miRNAs, three replicates, sequenced on Illumina GA II
2009-07-28 | E-GEOD-16373 | biostudies-arrayexpress
Project description:Exosomes, endosome-derived membrane microvesicles, contain a specific set of RNA transcripts that are involved in cell-cell communication and hold a great potential as disease biomarkers. To systemically characterize exosomal RNA profiles, we performed RNA sequencing analysis using three human plasma samples and evaluated efficacies of small RNA library preparation protocols from 3 manufacturers. We tested the six samples (A1 and A2, B1 and B2, C1 and C2) using two small RNA library preparation kits: NEBNext Multiplex Small RNA library Prep Set from New England Biolab (NEB) and NEXTflex Small RNA Sequencing Kit from Bioo Scientific (BS). We also tested IlluminaM-bM-^@M-^Ys TrueSeq Small RNA Sample Preparation Kit (ILMN) in sample A1 and A2. Together, we tested these plasma samples by sequencing 14 indexed libraries. This study allowed direct comparison of current small RNA library preparation protocols and identified the most suitable strategy for future exosomal RNA sequencing analysis.
2013-05-15 | E-GEOD-45722 | biostudies-arrayexpress
Project description:Small RNA-seq is increasingly being used for profiling of small RNAs. Quantitative characteristics of long RNA-seq have been extensively described, but small RNA-seq involves fundamentally different methods for library preparation, with distinct protocols and technical variations that have not been fully and systematically studied. Using common sets of reference samples, we evaluated the accuracy, reproducibility and bias of small RNA-seq library preparation for five distinct protocols and across nine different laboratories. As part of this larger study, we assessed sequencing bias and reproducibility using an equimolar pool of 1,152 small RNA sequences ranging from 15-90 nt, and primarily comprised of annotated human microRNAs. We observed extensive protocol-specific and sequence-specific bias that was largely mitigated in protocols employing sequencing adapters with randomized end-nucleotides. We find that sequencing bias is highly reproducible across labs using the same library preparation technologies, and use the data to calculate inter-protocol bias correction factors. These results provide strong evidence for the feasibility of reproducible cross-laboratory small RNA-seq studies, even those involving analysis of data generated using different protocols.
2018-07-09 | GSE94584 | GEO
Project description:Analysis of RNA samples by massive parallel sequencing holds the promise to assay gene expression in both a quantitative and qualitative fashion and therefore allows for digital gene expression (DGE) profiling. We assessed the effect of different experimental approaches by generating small RNA libraries from a biological sample as well as an equimolar pool of synthetic miRNAs and analyzed the results using capillary dideoxy sequencing and next-generation sequencing platforms (Roche/454, AB/SOLiD and Illumina/Solexa). Whereas different sequencing platforms provided highly similar results, large differences in DGE profiles were observed depending on the library preparation method used. Nevertheless, our results indicate that the preferential nature of the library preparation methods is systematic and highly reproducible and we show that DGE is well suited for the quantification of relative expression differences between samples. Keywords: Transcriptome analysis
2009-07-29 | GSE16371 | GEO
Project description:Analysis of RNA samples by massive parallel sequencing holds the promise to assay gene expression in both a quantitative and qualitative fashion and therefore allows for digital gene expression (DGE) profiling. We assessed the effect of different experimental approaches by generating small RNA libraries from a biological sample as well as an equimolar pool of synthetic miRNAs and analyzed the results using capillary dideoxy sequencing and next-generation sequencing platforms (Roche/454, AB/SOLiD and Illumina/Solexa). Whereas different sequencing platforms provided highly similar results, large differences in DGE profiles were observed depending on the library preparation method used. Nevertheless, our results indicate that the preferential nature of the library preparation methods is systematic and highly reproducible and we show that DGE is well suited for the quantification of relative expression differences between samples. Keywords: Transcriptome analysis
2009-07-29 | GSE16372 | GEO