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Abstract Summary Advances in high-throughput DNA sequencing technologies and decreasing costs have fueled the identification of small genetic variants (such as single nucleotide variants and indels) across tumors. Despite efforts to standardize variant formats and vocabularies, many sources of variability persist across databases and computational tools that annotate variants, hindering their integration within cancer genomic analyses. In this context, we present OpenVariant, an easily extendable Python package that facilitates seamless reading, parsing and refinement of diverse input file formats in a customizable structure, all within a single process. Availability and implementation OpenVariant is an open-source package available at https://github.com/bbglab/openvariant. Documentation may be found at https://openvariant.readthedocs.io.
ADN, High-Throughput Nucleotide Sequencing, Computational Biology, DNA, Genomics, Sequence Analysis, DNA, Polymorphism, Single Nucleotide, Biologia computacional, Computational biology, Applications Note, Neoplasms, Databases, Genetic, Humans, Software, Seqüència de nucleòtids, Tumors
ADN, High-Throughput Nucleotide Sequencing, Computational Biology, DNA, Genomics, Sequence Analysis, DNA, Polymorphism, Single Nucleotide, Biologia computacional, Computational biology, Applications Note, Neoplasms, Databases, Genetic, Humans, Software, Seqüència de nucleòtids, Tumors
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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