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easyPubMed - Search and Retrieve Scientific Publication Records from PubMed

Query NCBI Entrez and retrieve PubMed records in XML or text format. Process PubMed records by extracting and aggregating data from selected fields. A large number of records can be easily downloaded via this simple-to-use interface to the NCBI PubMed API.

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7.85 score 26 stars 3 dependents 204 scripts 559 downloads

mutSignatures - Decipher Mutational Signatures from Somatic Mutational Catalogs

Cancer cells accumulate DNA mutations as result of DNA damage and DNA repair processes. This computational framework is aimed at deciphering DNA mutational signatures operating in cancer. The framework includes modules that support raw data import and processing, mutational signature extraction, and results interpretation and visualization. The framework accepts widely used file formats storing information about DNA variants, such as Variant Call Format files. The framework performs Non-Negative Matrix Factorization to extract mutational signatures explaining the observed set of DNA mutations. Bootstrapping is performed as part of the analysis. The framework supports parallelization and is optimized for use on multi-core systems. The software was described by Fantini D et al (2020) <doi:10.1038/s41598-020-75062-0> and is based on a custom R-based implementation of the original MATLAB WTSI framework by Alexandrov LB et al (2013) <doi:10.1016/j.celrep.2012.12.008>.

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5.91 score 14 stars 58 scripts 412 downloads

TCGAretriever - Retrieve Genomic and Clinical Data from CBioPortal Including TCGA Data

The Cancer Genome Atlas (TCGA) is a program aimed at improving our understanding of Cancer Biology. Several TCGA Datasets are available online. 'TCGAretriever' helps accessing and downloading TCGA data hosted on 'cBioPortal' via its Web Interface (see <https://www.cbioportal.org/> for more information).

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4.18 score 328 downloads

colorhcplot - Colorful Hierarchical Clustering Dendrograms

Build dendrograms with sample groups highlighted by different colors. Visualize results of hierarchical clustering analyses as dendrograms whose leaves and labels are colored according to sample grouping. Assess whether data point grouping aligns to naturally occurring clusters.

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3.70 score 9 scripts 339 downloads