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10.1101/gr.214155.116 http://scihub22266oqcxt.onion/10.1101/gr.214155.116 C5411762!5411762!28360232     free     free     free       Genome+Res 2017 ; 27 (5): 665-76 Nephropedia Template TP {{tp|p=28360232|t=2017. Genome graphs and the evolution of genome inference |pdf=|usr=}}{{28360232}} gab.com Text Genome graphs and the evolution of genome inference JO: Genome Res http://www.kidney.de/pget.php?&tw=1&pmid=28360232 #FOAvip The human reference genome is part of the foundation of modern human biology and a monumental scientific achievement. However, because it excludes a great deal of common human variation, it introduces a pervasive reference bias into the field of human genomics. To reduce this bias, it makes sense to draw on representative collections of human genomes, brought together into reference cohorts. There are a number of techniques to represent and organize data gleaned from these cohorts, many using ideas implicitly or explicitly borrowed from graph-based models. Here, we survey various projects underway to build and apply these graph-based structures?which we collectively refer to as genome graphs?and discuss the improvements in read mapping, variant calling, and haplotype determination that genome graphs are expected to produce. Twit Text FOAVip Genome graphs and the evolution of genome inference ????Genome Res http://www.kidney.de/pget.php?&tw=1&pmid=28360232 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28360232 #FOAvip English Wikipedia <ref>{{Cite pmid|28360232}}</ref> Genome graphs and the evolution of genome inference #MMPMID28360232 Paten B; Novak AM; Eizenga JM; Garrison E Genome Res 2017[May]; 27 (5): 665-76 PMID28360232show ga The human reference genome is part of the foundation of modern human biology and a monumental scientific achievement. However, because it excludes a great deal of common human variation, it introduces a pervasive reference bias into the field of human genomics. To reduce this bias, it makes sense to draw on representative collections of human genomes, brought together into reference cohorts. There are a number of techniques to represent and organize data gleaned from these cohorts, many using ideas implicitly or explicitly borrowed from graph-based models. Here, we survey various projects underway to build and apply these graph-based structures?which we collectively refer to as genome graphs?and discuss the improvements in read mapping, variant calling, and haplotype determination that genome graphs are expected to produce. äGenome graphs and the evolution of genome inference (epmc).pdf DeepDyve Pubget Overpricing