Genome Biology
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Published on Jan 25, 2019in Genome Biology 13.21
Jean-Philippe Fortin1
Estimated H-index: 1
(Genentech),
Jenille Tan4
Estimated H-index: 4
(Genentech)
+ 4 AuthorsScott E. Martin3
Estimated H-index: 3
(Genentech)
Background Genome-wide loss-of-function screens using the CRISPR/Cas9 system allow the efficient discovery of cancer cell vulnerabilities. While several studies have focused on correcting for DNA cleavage toxicity biases associated with copy number alterations, the effects of sgRNAs co-targeting multiple genomic loci in CRISPR screens have not been discussed.
1 Citations Source Cite
Published on Feb 5, 2019in Genome Biology 13.21
Emanuel Gonçalves10
Estimated H-index: 10
,
Fiona Behan1
Estimated H-index: 1
+ 7 AuthorsMathew J. Garnett25
Estimated H-index: 25
BACKGROUND:CRISPR-Cas9 genome editing is widely used to study gene function, from basic biology to biomedical research. Structural rearrangements are a ubiquitous feature of cancer cells and their impact on the functional consequences of CRISPR-Cas9 gene-editing has not yet been assessed. RESULTS:Utilizing CRISPR-Cas9 knockout screens for 250 cancer cell lines, we demonstrate that targeting structurally rearranged regions, in particular tandem or interspersed amplifications, is highly detrimenta...
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Published on Feb 11, 2019in Genome Biology 13.21
Caroline Pont17
Estimated H-index: 17
(Institut national de la recherche agronomique),
Stefanie Wagner3
Estimated H-index: 3
(University of Bordeaux)
+ 3 AuthorsJérôme Salse33
Estimated H-index: 33
(Institut national de la recherche agronomique)
How contemporary plant genomes originated and evolved is a fascinating question. One approach uses reference genomes from extant species to reconstruct the sequence and structure of their common ancestors over deep timescales. A second approach focuses on the direct identification of genomic changes at a shorter timescale by sequencing ancient DNA preserved in subfossil remains. Merged within the nascent field of paleogenomics, these complementary approaches provide insights into the evolutionar...
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Published on Feb 11, 2019in Genome Biology 13.21
Kenta Sato1
Estimated H-index: 1
(University of Tokyo),
Koki Tsuyuzaki2
Estimated H-index: 2
,
Itoshi Nikaido2
Estimated H-index: 2
(University of Tsukuba)
Recent technical improvements in single-cell RNA sequencing (scRNA-seq) have enabled massively parallel profiling of transcriptomes, thereby promoting large-scale studies encompassing a wide range of cell types of multicellular organisms. With this background, we propose CellFishing.jl, a new method for searching atlas-scale datasets for similar cells and detecting noteworthy genes of query cells with high accuracy and throughput. Using multiple scRNA-seq datasets, we validate that our method de...
2 Citations Source Cite
Published on Jan 22, 2019in Genome Biology 13.21
Weijun Liu4
Estimated H-index: 4
(Washington University in St. Louis),
Xiaowei Wang22
Estimated H-index: 22
(Washington University in St. Louis)
We perform a large-scale RNA sequencing study to experimentally identify genes that are downregulated by 25 miRNAs. This RNA-seq dataset is combined with public miRNA target binding data to systematically identify miRNA targeting features that are characteristic of both miRNA binding and target downregulation. By integrating these common features in a machine learning framework, we develop and validate an improved computational model for genome-wide miRNA target prediction. All prediction data c...
2 Citations Source Cite
Published on Feb 1, 2019in Genome Biology 13.21
Michael C. Schatz50
Estimated H-index: 50
,
Andrew Cosgrove1
Estimated H-index: 1
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Published on Feb 4, 2019in Genome Biology 13.21
Shuhua Fu2
Estimated H-index: 2
(University of Iowa),
Anqi Wang1
Estimated H-index: 1
(University of Iowa),
Kin Fai Au15
Estimated H-index: 15
(Ohio State University)
Background Third-generation sequencing technologies have advanced the progress of the biological research by generating reads that are substantially longer than second-generation sequencing technologies. However, their notorious high error rate impedes straightforward data analysis and limits their application. A handful of error correction methods for these error-prone long reads have been developed to date. The output data quality is very important for downstream analysis, whereas computing re...
1 Citations Source Cite
Published on Mar 1, 2019in Genome Biology 13.21
Jun Cheng2
Estimated H-index: 2
(Ludwig Maximilian University of Munich),
Thi Yen Duong Nguyen (Technische Universität München)+ 4 AuthorsJulien Gagneur25
Estimated H-index: 25
(Technische Universität München)
Predicting the effects of genetic variants on splicing is highly relevant for human genetics. We describe the framework MMSplice (modular modeling of splicing) with which we built the winning model of the CAGI5 exon skipping prediction challenge. The MMSplice modules are neural networks scoring exon, intron, and splice sites, trained on distinct large-scale genomics datasets. These modules are combined to predict effects of variants on exon skipping, splice site choice, splicing efficiency, and ...
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Published on Jan 11, 2019in Genome Biology 13.21
Pierre Murat16
Estimated H-index: 16
(University of Cambridge),
Giovanni Marsico14
Estimated H-index: 14
(University of Cambridge)
+ 3 AuthorsShankar Balasubramanian63
Estimated H-index: 63
(University of Cambridge)
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Published on Jan 4, 2019in Genome Biology 13.21
Stuart Lee15
Estimated H-index: 15
(Monash University),
Dianne Cook25
Estimated H-index: 25
(Monash University),
Michael S. Lawrence85
Estimated H-index: 85
(Genentech)
Bioconductor is a widely used R-based platform for genomics, but its host of complex genomic data structures places a cognitive burden on the user. For most tasks, the GRanges object would suffice, but there are gaps in the API that prevent its general use. By recognizing that the GRanges class follows “tidy” data principles, we create a grammar of genomic data transformation, defining verbs for performing actions on and between genomic interval data and providing a way of performing common data...
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