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  • 1
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    SC3-seq: a method for highly parallel and quantitative measurement of single-cell gene expression (2015)
    Oxford University Press
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    Publication Date: 2015-05-20
    Description: Single-cell mRNA sequencing (RNA-seq) methods have undergone rapid development in recent years, and transcriptome analysis of relevant cell populations at single-cell resolution has become a key research area of biomedical sciences. We here present s ingle- c ell mRNA 3 -prime end seq uencing (SC3-seq), a practical methodology based on PCR amplification followed by 3-prime-end enrichment for highly quantitative, parallel and cost-effective measurement of gene expression in single cells. The SC3-seq allows excellent quantitative measurement of mRNAs ranging from the 10,000-cell to 1-cell level, and accordingly, allows an accurate estimate of the transcript levels by a regression of the read counts of spike-in RNAs with defined copy numbers. The SC3-seq has clear advantages over other typical single-cell RNA-seq methodologies for the quantitative measurement of transcript levels and at a sequence depth required for the saturation of transcript detection. The SC3-seq distinguishes four distinct cell types in the peri-implantation mouse blastocysts. Furthermore, the SC3-seq reveals the heterogeneity in human-induced pluripotent stem cells (hiPSCs) cultured under on-feeder as well as feeder-free conditions, demonstrating a more homogeneous property of the feeder-free hiPSCs. We propose that SC3-seq might be used as a powerful strategy for single-cell transcriptome analysis in a broad range of investigations in biomedical sciences.
    Keywords: Massively Parallel (Deep) Sequencing
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 2
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    New insights into the performance of human whole-exome capture platforms (2015)
    Oxford University Press
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    Publication Date: 2015-06-24
    Description: Whole exome sequencing (WES) is increasingly used in research and diagnostics. WES users expect coverage of the entire coding region of known genes as well as sufficient read depth for the covered regions. It is, however, unknown which recent WES platform is most suitable to meet these expectations. We present insights into the performance of the most recent standard exome enrichment platforms from Agilent, NimbleGen and Illumina applied to six different DNA samples by two sequencing vendors per platform. Our results suggest that both Agilent and NimbleGen overall perform better than Illumina and that the high enrichment performance of Agilent is stable among samples and between vendors, whereas NimbleGen is only able to achieve vendor- and sample-specific best exome coverage. Moreover, the recent Agilent platform overall captures more coding exons with sufficient read depth than NimbleGen and Illumina. Due to considerable gaps in effective exome coverage, however, the three platforms cannot capture all known coding exons alone or in combination, requiring improvement. Our data emphasize the importance of evaluation of updated platform versions and suggest that enrichment-free whole genome sequencing can overcome the limitations of WES in sufficiently covering coding exons, especially GC-rich regions, and in characterizing structural variants.
    Keywords: Massively Parallel (Deep) Sequencing
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 3
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    Blocking of targeted microRNAs from next-generation sequencing libraries (2015)
    Oxford University Press
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    Publication Date: 2015-12-02
    Description: Highly abundant microRNAs (miRNAs) in small RNA sequencing libraries make it difficult to obtain efficient measurements of more lowly expressed species. We present a new method that allows for the selective blocking of specific, abundant miRNAs during preparation of sequencing libraries. This technique is specific with little off-target effects and has no impact on the reproducibility of the measurement of non-targeted species. In human plasma samples, we demonstrate that blocking of highly abundant hsa-miR-16–5p leads to improved detection of lowly expressed miRNAs and more precise measurement of differential expression overall. Furthermore, we establish the ability to target a second abundant miRNA and to multiplex the blocking of two miRNAs simultaneously. For small RNA sequencing, this technique could fill a similar role as do ribosomal or globin removal technologies in messenger RNA sequencing.
    Keywords: Massively Parallel (Deep) Sequencing
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 4
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    The Subread aligner: fast, accurate and scalable read mapping by seed-and-vote (2013)
    Oxford University Press
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    Publication Date: 2013-05-29
    Description: Read alignment is an ongoing challenge for the analysis of data from sequencing technologies. This article proposes an elegantly simple multi-seed strategy, called seed-and-vote, for mapping reads to a reference genome. The new strategy chooses the mapped genomic location for the read directly from the seeds. It uses a relatively large number of short seeds (called subreads) extracted from each read and allows all the seeds to vote on the optimal location. When the read length is 〈160 bp, overlapping subreads are used. More conventional alignment algorithms are then used to fill in detailed mismatch and indel information between the subreads that make up the winning voting block. The strategy is fast because the overall genomic location has already been chosen before the detailed alignment is done. It is sensitive because no individual subread is required to map exactly, nor are individual subreads constrained to map close by other subreads. It is accurate because the final location must be supported by several different subreads. The strategy extends easily to find exon junctions, by locating reads that contain sets of subreads mapping to different exons of the same gene. It scales up efficiently for longer reads.
    Keywords: Massively Parallel (Deep) Sequencing
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 5
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    Fast and accurate read mapping with approximate seeds and multiple backtracking (2013)
    Oxford University Press
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    Publication Date: 2013-04-14
    Description: We present Masai, a read mapper representing the state-of-the-art in terms of speed and accuracy. Our tool is an order of magnitude faster than RazerS 3 and mrFAST, 2–4 times faster and more accurate than Bowtie 2 and BWA. The novelties of our read mapper are filtration with approximate seeds and a method for multiple backtracking. Approximate seeds, compared with exact seeds, increase filtration specificity while preserving sensitivity. Multiple backtracking amortizes the cost of searching a large set of seeds by taking advantage of the repetitiveness of next-generation sequencing data. Combined together, these two methods significantly speed up approximate search on genomic data sets. Masai is implemented in C++ using the SeqAn library. The source code is distributed under the BSD license and binaries for Linux, Mac OS X and Windows can be freely downloaded from http://www.seqan.de/projects/masai .
    Keywords: Massively Parallel (Deep) Sequencing
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 6
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    Utilizing mapping targets of sequences underrepresented in the reference assembly to reduce false positive alignments (2015)
    Oxford University Press
    Details
    Publication Date: 2015-11-17
    Description: The human reference assembly remains incomplete due to the underrepresentation of repeat-rich sequences that are found within centromeric regions and acrocentric short arms. Although these sequences are marginally represented in the assembly, they are often fully represented in whole-genome short-read datasets and contribute to inappropriate alignments and high read-depth signals that localize to a small number of assembled homologous regions. As a consequence, these regions often provide artifactual peak calls that confound hypothesis testing and large-scale genomic studies. To address this problem, we have constructed mapping targets that represent roughly 8% of the human genome generally omitted from the human reference assembly. By integrating these data into standard mapping and peak-calling pipelines we demonstrate a 10-fold reduction in signals in regions common to the blacklisted region and identify a comprehensive set of regions that exhibit mapping sensitivity with the presence of the repeat-rich targets.
    Keywords: Massively Parallel (Deep) Sequencing
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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