Searching journal content for articles similar to Tarazona et al. 21 (12): 2213.

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  1. Method: TransMeta simultaneously assembles multisample RNA-seq reads
    • Ting Yu,
    • Xiaoyu Zhao,
    • and Guojun Li
    Genome Res. July 2022 32: 1398-1407; Published in Advance July 20, 2022, doi:10.1101/gr.276434.121
    ..., -guided methods are more commonly used because they are usually more accurate (Shao and Kingsford 2017).Transcriptomic studies involve multiple samples. Constructing a consensus transcriptome from multiple samples is critical in an RNA-seq experiment for the subsequent quantification and differential...
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  2. Research: Differences in molecular sampling and data processing explain variation among single-cell and single-nucleus RNA-seq experiments
    • John T. Chamberlin,
    • Younghee Lee,
    • Gabor T. Marth,
    • and Aaron R. Quinlan
    Genome Res. February 2024 34: 179-188; Published in Advance February 14, 2024, doi:10.1101/gr.278253.123
    ...longer genes results in increased statistical power to detect differential expression in these genes and vice versa. This phenomenon is similar to the fragmentation bias in conventional RNA-seq, in which longer transcripts yield more fragments that can be sequenced and, in turn, more stable expression...
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  3. Method: Recalibrating differential gene expression by genetic dosage variance prioritizes functionally relevant genes
    • Philipp Rentzsch,
    • Aaron Kollotzek,
    • Kaushik Ram Ganapathy,
    • Pejman Mohammadi,
    • and Tuuli Lappalainen
    Genome Res. October 2025 35: 2316-2325; Published in Advance September 17, 2025, doi:10.1101/gr.280360.124
    ...different bioinformatics methods to test DE have been developed, adapting rigorous statistical tests to the particularities and assumptions of DNA microarrays and later RNA-seq. Some of the currently most popular methods for differential gene expression analysis are DESeq2 (Love et al. 2014), edge...
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  4. Method: End Sequence Analysis Toolkit (ESAT) expands the extractable information from single-cell RNA-seq data
    • Alan Derr,
    • Chaoxing Yang,
    • Rapolas Zilionis,
    • Alexey Sergushichev,
    • David M. Blodgett,
    • Sambra Redick,
    • Rita Bortell,
    • Jeremy Luban,
    • David M. Harlan,
    • Sebastian Kadener,
    • Dale L. Greiner,
    • Allon Klein,
    • Maxim N. Artyomov,
    • and Manuel Garber
    Genome Res. October 2016 26: 1397-1410; Published in Advance July 28, 2016, doi:10.1101/gr.207902.116
    ...(ESAT) designed for the analysis of short reads obtained from endsequence RNA-seq. In this context, we refer to both 3′ and 5′ selective methods as end-sequencing and will mostly treat them as similar for all computational matters. ESAT addresses misannotated or sample-specific transcript boundaries...
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  5. Resource: Synthetic spike-in standards for RNA-seq experiments
    • Lichun Jiang,
    • Felix Schlesinger,
    • Carrie A. Davis,
    • Yu Zhang,
    • Renhua Li,
    • Marc Salit,
    • Thomas R. Gingeras,
    • and Brian Oliver
    Genome Res. September 2011 21: 1543-1551; Published in Advance August 4, 2011, doi:10.1101/gr.121095.111
    ...), and in a study using quantitative PCR as the benchmark, RNA-seq showed better performance for genes with high expression, while two-channel microarrays were more sensitive in identifying differential expression between genes with low expression (Bloom et al. 2009). Usingmeasurements on a pool of synthetic mi...
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  6. Methods: RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays
    • John C. Marioni,
    • Christopher E. Mason,
    • Shrikant M. Mane,
    • Matthew Stephens,
    • and Yoav Gilad
    Genome Res. September 2008 18: 1509-1517; Published in Advance June 11, 2008, doi:10.1101/gr.079558.108
    ...RNA-seq: An assessment of technical reproducibility and comparison with gene expression arrays John C. Marioni 1 , 6 , Christopher E. Mason 2 , 3 , 6 , Shrikant M. Mane 4 , Matthew Stephens 1 , 5 , 7 , and Yoav Gilad 1 , 7...
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  7. Method: Accurate fusion transcript identification from long- and short-read isoform sequencing at bulk or single-cell resolution
    • Qian Qin,
    • Victoria Popic,
    • Kirsty Wienand,
    • Houlin Yu,
    • Emily White,
    • Akanksha Khorgade,
    • Asa Shin,
    • Christophe Georgescu,
    • Catarina D. Campbell,
    • Arthur Dondi,
    • Niko Beerenwinkel,
    • Francisca Vazquez,
    • Aziz M. Al'Khafaji,
    • and Brian J. Haas
    Genome Res. April 2025 35: 967-986; Published in Advance March 14, 2025, doi:10.1101/gr.279200.124
    ...normalization for sequencing depth, the rate of recovery of fusion reads was roughly equivalent, consistent with the sequencing libraries being derived from the single sample (Supplemental Fig. S2A). For comparison of fusion detection with PacBio long isoform reads versus Illumina short-read RNA-seq, we further...
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  8. Review: A systematic guide for identifying transcription factors that directly regulate the expression of a gene of interest
    • Andrew D. Bates,
    • Dawid Grzela,
    • Maciej Studzian,
    • Louise Brennan,
    • Moli Williams,
    • Conor Fawcett,
    • Beth Hammond,
    • Manreen Grewal,
    • Marcin Ratajewski,
    • Lukasz Pulaski,
    • and Urszula L. McClurg
    Genome Res. March 2026 36: 433-459; Published in Advance February 17, 2026, doi:10.1101/gr.281154.125
    ...in any eukaryotic organism, TSSPlant (Shahmuradov et al. 2017) designed for plant TSS prediction, and machine learning-enhanced options like DeePromoter (Oubounyt et al. 2019) designed exclusively for mammalian TSSs. Newer CamoTSS specifically calls TSS from actual RNA-seq data (Hou et al. 2023).Most...
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  9. Research: Developmental transcriptomics in Pristionchus reveals the environmental responsiveness of a plasticity gene-regulatory network
    • Shelley Reich,
    • Tobias Loschko,
    • Julie Jung,
    • Samantha Nestel,
    • Ralf J. Sommer,
    • and Michael S. Werner
    Genome Res. July 2025 35: 1560-1573; Published in Advance June 9, 2025, doi:10.1101/gr.279783.124
    ...between species is notoriously challenging (Munro et al. 2022) owing to both evolutionary divergence and the need to normalize RNA-seq reads between different gene annotations. We took a conservative approach and mapped the reads of each species to its own transcriptome and then performed a differential...
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  10. Research: Pangenome analysis reveals families of ubiquitin-ligase adaptors as key genomic divergence drivers that lead to hybrid incompatibility
    • Dongying Xie,
    • Pohao Ye,
    • Yiming Ma,
    • and Zhongying Zhao
    Genome Res. March 2026 36: 506-521; Published in Advance February 17, 2026, doi:10.1101/gr.280885.125
    ...). In contrast, C. briggsae exhibits a contraction in gene families containing these domains (Fig. 4E). Taken together, these results suggest a presumably differential selection pressure imposed by pathogens or other stresses between the two species.Previous studies demonstrated that fast-evolving genes tend...
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