github.com - gapFinisher is based on the controlled use of a previously published gap filling tool FGAP and works on all standard Linux/UNIX command lines. They compare the performance of gapFinisher against two other published gap filling tools PBJelly and...
github.com - gapFinisher to process SSPACE-LongRead output to fill gaps after the scaffolding. gapFinisher is based on the controlled use of a previously published gap filling tool FGAP and works on all standard Linux/UNIX command...
github.com - The pipeline can use information from scaffolded assemblies (for example from HiC or 10X Genomics), or even from diverged (~65-100 Mya) reference genomes for ordering the contigs and thus support the assembly process. This typically results in...
github.com - The pipeline was developed based on a popular workflow framework Nextflow, composed of four core procedures including reads alignment, assembly, identification and quantification. It contains various unique features such as well-designed...
github.com - ausarg/pipesnake is a bioinformatics best-practice analysis pipeline for phylogenomic reconstruction starting from short-read 'second-generation' sequencing data.
The pipeline is built using Nextflow, a workflow tool to run tasks across...
github.com - Simka is a de novo comparative metagenomics tool. Simka represents each dataset as a k-mer spectrum and compute several classical ecological distances between them.
Developper: Gaëtan Benoit, PhD, former member of...
github.com - CoverM aims to be a configurable, easy to use and fast DNA read coverage and relative abundance calculator focused on metagenomics applications.
CoverM calculates coverage of genomes/MAGs coverm genome (help) or individual...
Metagenomics is rapidly moving beyond short-read sequencing. With the increasing adoption of long-read technologies, researchers can generate more contiguous assemblies—but converting these reads into reliable metagenome-assembled genomes (MAGs)...
http://shinyheatmap.com/ - Background: Transcriptomics, metabolomics, metagenomics, and other various next-generation sequencing (-omics) fields are known for their production of large datasets. Visualizing such big data has posed technical challenges in biology, both in...