From: Charles Plessy Date: Thu, 9 May 2019 00:56:57 +0000 (+0900) Subject: More minor corrections X-Git-Url: https://source.charles.plessy.org/?a=commitdiff_plain;h=ed7eb5efb3953f4f30d783469ad36b353ad6380c;p=setup%2F.git More minor corrections --- diff --git a/tags/assembly.mdwn b/tags/assembly.mdwn index f244ca89..2d3c63a7 100644 --- a/tags/assembly.mdwn +++ b/tags/assembly.mdwn @@ -8,11 +8,11 @@ Prior assembly, MinIONQC ([[Lanfear and coll., 2018|biblio/30052755]]) allows for the comparison of multiple Nanopore runs on the same plot, to assess if read length is satisfactory. -The Flye assembler ([[Kolmogorov and coll. (2018)|biblio/30936562]]) creates an +The Flye assembler ([[Kolmogorov and coll., 2018|biblio/30936562]]) creates an A-Bruijn (assembly) graph from draft contigs using long error-prone reads, untangles the graph by resolving repeats, and then uses it to refine the contings and increase their accuracy. (The predecessor of Flye, ABruijn, was -reported by [[Istace and coll. (2017)|biblio/28369459]] to be able to assemble +reported by [[Istace and coll. (2017)|biblio/28369459]] to be able to assemble mitochondrial genomes, unlike Canu and other assemblers.) After assembly, the contigs can be further polished with Racon ([[Vaser, Sović, @@ -20,7 +20,7 @@ Nagarajan and Šikić, 2017|biblio/28100585]]). When coverage is too low for efficient reference-free assembly, related references can be used as a guide. The Ragout software ([[Kolmogorov and -coll., 2014|biblio/24931998), [[Kolmogorov and coll., 2018|biblio/30341161]]) +coll., 2014|biblio/24931998]]), [[Kolmogorov and coll., 2018|biblio/30341161]]) can take multiple reference genomes to guide the assembly of one target. Polymorphisms unique to the target genome can be recovered, but chromosome fusions are typically hard to detect. Compared to version 1, version 2 infers @@ -38,7 +38,7 @@ Relase notes of HM2 version 20180603 suggest to use “_HapCUT2 or other phasing tools to get the high-quality haplotype assembly based on the reference haploid assembly_”. -SALSA (Simple AssembLy ScAffolder, [Ghurye and coll., 2017|biblio/28701198]]) +SALSA (Simple AssembLy ScAffolder, [[Ghurye and coll., 2017|biblio/28701198]]) takes Hi-C data and contigs as input and scaffolds them under the hypothesis that most contact points are due to local (same-chromosome) proximity. Version 2 of SALSA uses unitigs and the assembly graph as input ([[Ghurye and coll.,