What is Minia ? https://github.com/GATB/minia
Minia is a short-read assembler based on a de Bruijn graph, capable of assembling a human genome on a desktop computer in a day. The output of Minia is a set of contigs. Minia produces results of similar contiguity and accuracy to other de Bruijn assemblers (e.g. Velvet).
Version: 2.4 https://github.com/fenderglass/Flye
Flye is a de novo assembler for long and noisy reads, such as those produced by PacBio and Oxford Nanopore Technologies. The core read overlapping algorithm uses A-Bruijn graph to find the mappings between reads and does not require reads to be error-corrected, which resutlts into a faster assembly.
Flye transforms an initial set of draft contigs into a repeat graph. It is somewhat similar to de Bruijn graphs, but can tollerate higher noise level of long reads. Similarly to short read assemblers, Flye maps the original reads back on the graph and uses bridging information to accurately resolve repeats. The package also includes a polisher module, which produces the final assembly of high nucleotide-level quality.
https://github.com/soedinglab/plass
Plass (Protein-Level ASSembler) is a software to assemble short read sequencing data on a protein level. The main purpose of Plass is the assembly of complex metagenomic datasets. It assembles 10 times more protein residues in soil metagenomes than Megahit. Plass is GPL-licensed open source software that is implemented in C++ and available for Linux and macOS. The software is designed to run on multiple cores. Plass was used to create a Soil Reference Catalog (SRC) and a Marine Eukaryotic Reference Catalog (MERC).
Steinegger M, Mirdita M and Soeding J. Protein-level assembly increases protein sequence recovery from metagenomic samples manyfold. biorxiv, doi: doi.org/10.1101/386110 (2018).
Overview of Agalma https://bitbucket.org/caseywdunn/agalma
Agalma is a set of analysis pipelines for transcriptome assembly and analysis, phylogenetic analysis, expression analysis (including phylogenetic analysis of gene expression data). It builds alignments of homologous genes and preliminary species trees from genomic and transcriptome data. Agalma includes support for transcriptome assembly (paired-end Illumina data), and can also import gene predictions from other sources (eg, assembled non-Illumina transcriptomes or gene models from annotated genomes). Please carefully read the details on data requirements before proceeding with your analyses.
Agalma provides a completely automated analysis workflow, and records rich diagnostics. You can then evaluate these diagnostics to spot problems and examine the success of your analyses, the quality of the original data, and the appropriateness of the default parameters. You can then rerun subsets of the pipelines with optimized parameters as needed.
