Ontology highlight
ABSTRACT:
PROVIDER: PRJNA722106 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR14355650.fastq.gz | Fastqsanger.gz | |||
| SRR14355651.fastq.gz | Fastqsanger.gz | |||
| SRR14355652.fastq.gz | Fastqsanger.gz | |||
| SRR14355653.fastq.gz | Fastqsanger.gz | |||
| SRR14355654.fastq.gz | Fastqsanger.gz |
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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.
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Project description:Performance comparison of small RNA-Seq library preparation methods for biofluid samples
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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. We report here the results of a study using common references (synthetic RNA pools of defined composition, as well as plasma-derived RNA) to evaluate the accuracy, reproducibility and bias of small RNA-seq library preparation for five distinct protocols and across nine different laboratories. We observed protocol-specific and sequence-specific bias, which was ameliorated using adapters for ligation with randomized end-nucleotides, and computational correction factors. Despite this technical bias, relative quantification using small RNA-seq was remarkably accurate and reproducible, even across multiple laboratories using different methods. 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. This SuperSeries is composed of the SubSeries listed below.
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Project description:Evaluating different library preparation methods for Pool-seq
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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 reproducibility and accuracy of relative expression measurements using two pools of synthetic small RNA sequences, where subsets of the sRNAs vary in relative amount between pools A and B. The pools each contain 334 small RNAs, varying by 15 different ratios between pools A and B (10:1, 8:1, 5:1, 4:1, 3:1, 2:1, 1.5:1, 1:1, 1:1.5, 1:2, 1:3, 1:4 1:5, 1:8, 1:10). We find that although the sequencing bias varies extensively between protocols, the relative abundance measured between samples A and B is largely reproducible and accurate across labs and protocols. These results suggest that measurements of differential expression should be comparable across institutions and library preparation technologies.
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Project description:Comparison of library preparation methods using Cryptococcus neoformans var. grubii
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