BOL: Related items

Purge Haplotigs: Pipeline to help with curating heterozygous diploid genome assemblies

Rahul Nayak — Mon, 17 Dec 2018 03:17:20 -0600

Some parts of a genome may have a very high degree of heterozygosity. This causes contigs for both haplotypes of that part of the genome to be assembled as separate primary contigs, rather than as a contig and an associated haplotig. This can be an issue for downstream analysis whether you're working on the haploid or phased-diploid assembly.

Identify pairs of contigs that are syntenic and move one of them to the haplotig 'pool'. The pipeline uses mapped read coverage and Minimap2 alignments to determine which contigs to keep for the haploid assembly. Dotplots are optionally produced for all flagged contig matches, juxtaposed with read-coverage, to help the user determine the proper assignment of any remaining ambiguous contigs. The pipeline will run on either a haploid assembly (i.e. Canu, FALCON or FALCON-Unzip primary contigs) or on a phased-diploid assembly (i.e. FALCON-Unzip primary contigs + haplotigs). Here are two examples of how Purge Haplotigs can improve a haploid and diploid assembly.

Address of the bookmark: https://bitbucket.org/mroachawri/purge_haplotigs

Environmental Genomics Group SciLifeLab/KTH Stockholm

BioStar — Thu, 01 Dec 2022 01:12:43 -0600

Useful Metagenomics resources

Address of the bookmark: https://github.com/envgen

Variant Calling Pipeline

LEGE — Sat, 19 Oct 2024 12:23:40 -0500

The variantcalling.nf nextflow script will take any number of samples with paired-end reads in FASTQ format, map reads using Bowtie2, process BAM files, and finally call variants using BCFtools v1.21 and/or Freebayes v1.3.6. If part of the pipeline is unsuccessful for a sample then these errors are ignored.

Pipeline flowchart:

Dependencies (version tested)

Nextflow (24.04.4)
Java (18.0.2.1)
Python (3.10)
Perl (5.32.1)
Bowtie2 (2.5.3)
SAMtools (1.19.2)
GATK4 (4.5)
BCFtools (1.21)
Freebayes (1.3.6)

Address of the bookmark: https://github.com/Tom-Jenkins/nextflow-pipelines/blob/main/docs/variant-calling.md

Omega2: metagenome assembly pipeline

Jit — Mon, 10 Jul 2017 05:56:07 -0500

Omega found overlaps between reads using a prefix/suffix hash table. The overlap graph of reads was simplified by removing transitive edges and trimming short branches. Unitigs were generated based on minimum cost flow analysis of the overlap graph and then merged to contigs and scaffolds using mate-pair information. In comparison with three de Bruijn graph assemblers (SOAPdenovo, IDBA-UD and MetaVelvet), Omega provided comparable overall performance on a HiSeq 100-bp dataset and superior performance on a MiSeq 300-bp dataset. In comparison with Celera on the MiSeq dataset, Omega provided more continuous assemblies overall using a fraction of the computing time of existing overlap-layout-consensus assemblers. This indicates Omega can more efficiently assemble longer Illumina reads, and at deeper coverage, for metagenomic datasets.

Address of the bookmark: http://omega.omicsbio.org/

ONT assembly and Illumina polishing pipeline

Jit — Thu, 23 Nov 2017 10:13:42 -0600

This pipeline performs the following steps:

Assembly of nanopore reads using Canu.
Polish canu contigs using racon (optional).
Map a paired-end Illumina dataset onto the contigs obtained in the previous steps using BWA mem.
Perform correction of contigs using pilon and the Illumina dataset.

Address of the bookmark: https://github.com/nanoporetech/ont-assembly-polish

ARC: pipeline which facilitates iterative, reference guided de novo assemblies

Jit — Thu, 26 Jul 2018 09:20:26 -0500

ARC is a pipeline which facilitates iterative, reference guided de novo assemblies with the intent of:

Reducing time in analysis and increasing accuracy of results by only considering those reads which should assemble together.
Reducing/removing reference bias as compared to mapping based approaches.

The software is designed to work in situations where a whole-genome assembly is not the objective, but rather when the researcher wishes to assemble discreet 'targets' contained within next-generation shotgun sequence data. ARC decomplexifies the traditionally difficult problem of assembly by breaking the reads into small, manageable subsets which can then be assembled quickly and efficiently in parallel. Applications include those in which the researcher wishes to de novo assemble specific content and a set of semi-similar reference targets is available to initialize the assembly process.

https://ibest.github.io/ARC/

Address of the bookmark: https://ibest.github.io/ARC/

multiPhATE: bioinformatics pipeline for functional annotation of phage isolates

Abhimanyu Singh — Thu, 16 May 2019 00:17:39 -0500

multiple-genome Phage Annotation Toolkit and Evaluator (multiPhATE). multiPhATE is a throughput pipeline driver that invokes an annotation pipeline (PhATE) across a user-specified set of phage genomes. This tool incorporates a de novo phage gene-calling algorithm and assigns putative functions to gene calls using protein-, virus-, and phage-centric databases.

Address of the bookmark: https://github.com/carolzhou/multiPhATE

DeepVariant : an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.

Jit — Sat, 25 Jan 2020 13:28:09 -0600

DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.

DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data. DeepVariant relies on Nucleus, a library of Python and C++ code for reading and writing data in common genomics file formats (like SAM and VCF) designed for painless integration with the TensorFlow machine learning framework.

https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html

https://www.biorxiv.org/content/10.1101/092890v6

Address of the bookmark: https://github.com/google/deepvariant

sunbeam: A robust, extensible metagenomics pipeline

Jit — Thu, 18 Jun 2020 06:58:52 -0500

Sunbeam is a pipeline written in snakemake that simplifies and automates many of the steps in metagenomic sequencing analysis. It uses conda to manage dependencies, so it doesn't have pre-existing dependencies or admin privileges, and can be deployed on most Linux workstations and clusters. To read more, check out our paper in Microbiome.

https://sunbeam.readthedocs.io/en/latest/

Address of the bookmark: https://github.com/sunbeam-labs/sunbeam

Liftoff: An accurate GFF3/GTF lift over pipeline

Neel — Sun, 20 Dec 2020 01:36:37 -0600

Liftoff is a tool that accurately maps annotations in GFF or GTF between assemblies of the same, or closely-related species. Unlike current coordinate lift-over tools which require a pre-generated “chain” file as input, Liftoff is a standalone tool that takes two genome assemblies and a reference annotation as input and outputs an annotation of the target genome.

Address of the bookmark: https://github.com/agshumate/Liftoff