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zadetkov: 224
41.
  • Nephron progenitor commitme... Nephron progenitor commitment is a stochastic process influenced by cell migration
    Lawlor, Kynan T; Zappia, Luke; Lefevre, James ... eLife, 01/2019, Letnik: 8
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    Progenitor self-renewal and differentiation is often regulated by spatially restricted cues within a tissue microenvironment. Here, we examine how progenitor cell migration impacts regionally induced ...
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42.
  • Sierra: discovery of differ... Sierra: discovery of differential transcript usage from polyA-captured single-cell RNA-seq data
    Patrick, Ralph; Humphreys, David T.; Janbandhu, Vaibhao ... Genome Biology, 07/2020, Letnik: 21, Številka: 1
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    Abstract High-throughput single-cell RNA-seq (scRNA-seq) is a powerful tool for studying gene expression in single cells. Most current scRNA-seq bioinformatics tools focus on analysing overall ...
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43.
  • splatPop: simulating popula... splatPop: simulating population scale single-cell RNA sequencing data
    Azodi, Christina B; Zappia, Luke; Oshlack, Alicia ... Genome Biology, 12/2021, Letnik: 22, Številka: 1
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    Population-scale single-cell RNA sequencing (scRNA-seq) is now viable, enabling finer resolution functional genomics studies and leading to a rush to adapt bulk methods and develop new ...
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44.
  • Large-scale manipulation of... Large-scale manipulation of promoter DNA methylation reveals context-specific transcriptional responses and stability
    de Mendoza, Alex; Nguyen, Trung Viet; Ford, Ethan ... Genome Biology, 07/2022, Letnik: 23, Številka: 1
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    Abstract Background Cytosine DNA methylation is widely described as a transcriptional repressive mark with the capacity to silence promoters. Epigenome engineering techniques enable direct testing of ...
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45.
  • JAFFAL: detecting fusion ge... JAFFAL: detecting fusion genes with long-read transcriptome sequencing
    Davidson, Nadia M; Chen, Ying; Sadras, Teresa ... Genome Biology, 01/2022, Letnik: 23, Številka: 1
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    In cancer, fusions are important diagnostic markers and targets for therapy. Long-read transcriptome sequencing allows the discovery of fusions with their full-length isoform structure. However, due ...
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46.
  • Detecting copy number alter... Detecting copy number alterations in RNA-Seq using SuperFreq
    Flensburg, Christoffer; Oshlack, Alicia; Majewski, Ian J Bioinformatics, 11/2021, Letnik: 37, Številka: 22
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    Abstract Motivation Calling copy number alterations (CNAs) from RNA sequencing (RNA-Seq) is challenging, because of the marked variability in coverage across genes and paucity of single nucleotide ...
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47.
  • Toblerone: detecting exon d... Toblerone: detecting exon deletion events in cancer using RNA-seq [version 1; peer review: 2 approved]
    Lonsdale, Andrew; Halman, Andreas; Brown, Lauren ... F1000 research, 2023, Letnik: 12
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    Cancer is driven by mutations of the genome that can result in the activation of oncogenes or repression of tumour suppressor genes. In acute lymphoblastic leukemia (ALL) focal deletions in IKAROS ...
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48.
  • MINTIE: identifying novel s... MINTIE: identifying novel structural and splice variants in transcriptomes using RNA-seq data
    Cmero, Marek; Schmidt, Breon; Majewski, Ian J ... Genome Biology, 10/2021, Letnik: 22, Številka: 1
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    Calling fusion genes from RNA-seq data is well established, but other transcriptional variants are difficult to detect using existing approaches. To identify all types of variants in transcriptomes ...
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49.
  • Bpipe: a tool for running a... Bpipe: a tool for running and managing bioinformatics pipelines
    SADEDIN, Simon P; POPE, Bernard; OSHLACK, Alicia Bioinformatics (Oxford, England), 06/2012, Letnik: 28, Številka: 11
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    Bpipe is a simple, dedicated programming language for defining and executing bioinformatics pipelines. It specializes in enabling users to turn existing pipelines based on shell scripts or command ...
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50.
  • From RNA-seq reads to diffe... From RNA-seq reads to differential expression results
    Oshlack, Alicia; Robinson, Mark D; Young, Matthew D Genome biology, 01/2010, Letnik: 11, Številka: 12
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    Many methods and tools are available for preprocessing high-throughput RNA sequencing data and detecting differential expression.
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