BOL: Related items

TARDIS: Toolkit for automated and rapid discovery of structural variants

Neel — Fri, 09 Jun 2017 04:43:31 -0500

tardis

Toolkit for Automated and Rapid DIscovery of Structural variants

Requirements

zlib (http://www.zlib.net)
mrfast (https://github.com/BilkentCompGen/mrfast)
htslib (included as submodule; http://htslib.org/)
Fetching tardis

git clone https://github.com/BilkentCompGen/tardis.git --recursive

https://github.com/BilkentCompGen/tardis

Address of the bookmark: https://github.com/BilkentCompGen/tardis

GMASS: a novel measure for genomeassembly structural similarity

Abhimanyu Singh — Sun, 14 Apr 2019 20:35:40 -0500

The GMASS score is a novel measure for representing structural similarity between two assemblies. It will contribute to the understanding of assembly output and developing de novo assemblers.

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2710-z

Address of the bookmark: http://bioinfo.konkuk.ac.kr/GMASS/htdocs/syncircos.php

Syri compares alignments between two chromosome-level assemblies and identifies synteny and structural rearrangements.

Shruti Paniwala — Wed, 01 Jun 2022 02:01:13 -0500

Syri compares alignments between two chromosome-level assemblies and identifies synteny and structural rearrangements.

Address of the bookmark: https://github.com/schneebergerlab/syri

QuasiModo - Quasispecies Metric Determination on Omics

Neel — Sat, 26 Jun 2021 15:22:56 -0500

This repository contains the scripts and pipeline that reproduces the results of the HCMV benchmarking study. In this study we evaluated genome assemblers and variant callers on 10 in vitro generated, mixed strain HCMV sequence samples, each consisting of two lab strains in different abundance ratios. This tool can also be used to evaluate assemblies and variant calling results on other similar datasets.

https://academic.oup.com/bib/article/22/3/bbaa123/5868070

Address of the bookmark: https://github.com/hzi-bifo/Quasimodo

UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment

BioStar — Mon, 05 Aug 2024 23:01:29 -0500

UnCoVar: Workflow for Transparent and Robust Virus Variant Calling, Genome Reconstruction and Lineage Assignment

Using state of the art tools, easily extended for other viruses
Tool and database updates for critical components via Conda
Built using modern design patterns with Conda and Snakemake
Extensible and easy to customize
Submission Ready Genomes
Customizable reporting with comprehensive visualization

https://ikim-essen.github.io/uncovar/

Github https://github.com/IKIM-Essen/uncovar

Address of the bookmark: https://ikim-essen.github.io/uncovar/

VG: variation graph data structures, interchange formats, alignment, genotyping, and variant calling methods

Jit — Tue, 28 Jan 2020 03:53:24 -0600

Variation graphs provide a succinct encoding of the sequences of many genomes. A variation graph (in particular as implemented in vg) is composed of:

nodes, which are labeled by sequences and ids
edges, which connect two nodes via either of their respective ends
paths, describe genomes, sequence alignments, and annotations (such as gene models and transcripts) as walks through nodes connected by edges

Address of the bookmark: https://github.com/vgteam/vg

progressiveCactus

Abhimanyu Singh — Thu, 18 May 2017 05:29:29 -0500

Progressive Cactus is a whole-genome alignment package.

Distribution package for the Prgressive Cactus multiple genome aligner. Dependencies are linked as submodules

https://github.com/glennhickey/progressiveCactus

Address of the bookmark: https://github.com/glennhickey/progressiveCactus

Supernova: generates phased, whole-genome de novo assemblies from a Chromium-prepared library.

Jit — Sun, 31 May 2020 01:59:30 -0500

Supernova generates phased, whole-genome de novo assemblies from a Chromium-prepared library.

Please see Achieving Success with De Novo Assembly and System Requirements before creating your Chromium libraries for assembly.

Supernova should be run using 38-56x coverage of the genome.
• Somewhat higher coverage is sometimes advantageous.
• Supernova will exit if it finds that coverage is far from the recommended range.
• Note that at most 2.14 billion reads are allowed.
• Please note that we have not extensively tested genomes larger than human, and any genome above approximately 4 GB should be considered experimental and is not supported.

Address of the bookmark: https://support.10xgenomics.com/de-novo-assembly/software/pipelines/latest/using/running

Automatic Filtering, Trimming, Error Removing and Quality Control for fastq data

Rahul Nayak — Mon, 13 Nov 2017 05:10:23 -0600

Automatic Filtering, Trimming, Error Removing and Quality Control for fastq data
AfterQC can simply go through all fastq files in a folder and then output three folders: good, bad and QC folders, which contains good reads, bad reads and the QC results of each fastq file/pair.
Currently it supports processing data from HiSeq 2000/2500/3000/4000, Nextseq 500/550, MiniSeq...and other Illumina 1.8 or newer formats

Address of the bookmark: https://github.com/OpenGene/AfterQC

MinION_GC: An R script to do some QC on MinION data

Radha Agarkar — Sun, 03 Dec 2017 15:19:18 -0600

Other tools focus on getting data out of the fastq or fast5 files, which is slow and computationally intensive. The benefit of this approach is that it works on a single, small, .txt summary file. So it's a lot quicker than most other things out there: it takes about a minute to analyse a 4GB flowcell on my laptop.

https://github.com/roblanf/minion_qc

Address of the bookmark: https://github.com/roblanf/minion_qc