The Sequence Alignment/Map format and SAMtools
Heng Li,Bob Handsaker,Alec Wysoker,T. J. Fennell,Jue Ruan,Nils Homer,Gabor T. Marth,Gonçalo R. Abecasis,Richard Durbin +8 more
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TLDR
SAMtools as discussed by the authors implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments.Abstract:
Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments.
Availability: http://samtools.sourceforge.net
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Citations
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Journal ArticleDOI
A Genome-wide Map of CTCF Multivalency Redefines the CTCF Code
Hirotaka Nakahashi,Kyong Rim Kieffer Kwon,Wolfgang Resch,Laura Vian,Marei Dose,Diana A. Stavreva,Ofir Hakim,Nathanael Pruett,Steevenson Nelson,Arito Yamane,Jason Qian,Wendy Dubois,Scott Welsh,Robert D. Phair,B. Franklin Pugh,Victor V. Lobanenkov,Gordon L. Hager,Rafael Casellas +17 more
TL;DR: It is found that CTCF reads sequence diversity through ZF clustering and associates with a wide array of DNA modules via combinatorial clustering of its 11 ZFs.
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TL;DR: The development of a virome capture sequencing platform for vertebrate viruses (VirCapSeq-VERT) that increases the sensitivity of sequence-based virus detection and characterization and is ideally suited for analyses of virome composition and dynamics.
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MAP-RSeq: Mayo Analysis Pipeline for RNA sequencing
Krishna R. Kalari,Asha Nair,Jaysheel D. Bhavsar,Daniel R. O'Brien,Jaime I. Davila,Matthew A. Bockol,Jinfu J. Nie,Xiaojia Tang,Saurabh Baheti,Jay B. Doughty,Sumit Middha,Hugues Sicotte,E. Aubrey Thompson,Yan W. Asmann,Jean-Pierre A. Kocher +14 more
TL;DR: The developed MAP-RSeq workflow is a comprehensive computational workflow that can be used for obtaining genomic features from transcriptomic sequencing data, for any genome, and has thus far enabled clinicians and researchers to understand the transcriptomic landscape of diseases for better diagnosis and treatment of patients.
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TL;DR: This first high-resolution characterization of a virus-associated cancer genome identified previously uncharacterized mutation patterns, intra-chromosomal rearrangements and fusion genes, as well as genetic heterogeneity within the tumor.
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T Cell–Inflamed versus Non-T Cell–Inflamed Tumors: A Conceptual Framework for Cancer Immunotherapy Drug Development and Combination Therapy Selection
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References
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