BOL: Related items

MAKER

Jitendra Narayan — Sun, 07 Feb 2016 15:59:24 -0600

MAKER is a portable and easily configurable genome annotation pipeline.Its purpose is to allow smaller eukaryotic and prokaryotic genome projects to independently annotate their genomes and to create genome databases. MAKER identifies repeats, aligns ESTs and proteins to a genome, produces ab-initio gene predictions and automatically synthesizes these data into gene annotations having evidence-based quality values.

More at http://www.yandell-lab.org/software/maker.html

Address of the bookmark: http://www.yandell-lab.org/software/maker.html

GKNO

Neel — Fri, 20 May 2016 18:56:37 -0500

gkno opens the world of complex bioinformatic analysis to people of all level of computational expertise. This site contains documentation, tutorials and information on all the tools that comprise gkno.

http://gkno.me/how-to/install.html

http://gkno.me/software.html

Address of the bookmark: http://gkno.me/

NCBI Prokaryotic Genome Annotation Pipeline

Jit — Tue, 16 May 2017 08:56:03 -0500

NCBI Prokaryotic Genome Annotation Pipeline is designed to annotate bacterial and archaeal genomes (chromosomes and plasmids).

Genome annotation is a multi-level process that includes prediction of protein-coding genes, as well as other functional genome units such as structural RNAs, tRNAs, small RNAs, pseudogenes, control regions, direct and inverted repeats, insertion sequences, transposons and other mobile elements.

NCBI has developed an automatic prokaryotic genome annotation pipeline that combines ab initio gene prediction algorithms with homology based methods. The first version of NCBI Prokaryotic Genome Automatic Annotation Pipeline (PGAAP; see Pubmed Article) developed in 2005 has been replaced with an upgraded version that is capable of processing a larger data volume. You can find a more detailed description of the new version of the pipeline in NCBI Handbook chapter. NCBI's annotation pipeline depends on several internal databases and is not currently available for download or use outside of the NCBI environment.

https://www.ncbi.nlm.nih.gov/genome/annotation_prok/

Address of the bookmark: https://www.ncbi.nlm.nih.gov/genome/annotation_prok/

funannotate: Eukaryotic Genome Annotation Pipeline

Jit — Wed, 19 Sep 2018 07:47:22 -0500

Funannotate is a genome prediction, annotation, and comparison software package. It was originally written to annotate fungal genomes (small eukaryotes ~ 30 Mb genomes), but has evolved over time to accomodate larger genomes. The impetus for this software package was to be able to accurately and easily annotate a genome for submission to NCBI GenBank. Existing tools (such as Maker) require significant manually editing to comply with GenBank submission rules, thus funannotate is aimed at simplifying the genome submission process.

Address of the bookmark: https://github.com/nextgenusfs/funannotate

Basic Structure of Snakemake Pipeline Run !

Abhi — Thu, 14 Oct 2021 07:01:38 -0500

/user/snakemake-demo$ ls

config.json data envs scripts slurm-240702.out Snakefile

data = mock data for the snakefile to use
Snakefile = name of the snakemake “formula” file
- Note: The default file that snakemake looks for in the current working directory is the Snakefile. If you would like to override that you can specify it following the -s
  - snakemake -s snakefile.py
envs = directory for storing the conda environments that the workflow will use.
scripts = directory for storing python scripts called by the snakemake formula.
config.json = json format file with extra parameters for our snakemake file to use.
cluster.json = json format file with specification for running on the HPC
samples.txt = file we will use later relating to the config.json file.

Run the snakemake file as a dry run (the example workflow shown above).

This will build a DAG of the jobs to be run without actually executing them.
snakemake --dry-run

User can execute rules of interest.

snakemake --dry-run all VS. snakemake --dry-run call VS. snakemake --dry-run bwa

Run the snakemake file in order to produce an image of the DAG of jobs to be run.

snakemake --dag | dot -Tsvg > dag.svg OR snakemake --dag | dot -Tsvg > dag.svg

Run the snakemake (this time not as a dry run)

snakemake --use-conda

YAMP: Yet Another Metagenomic Pipeline

BioStar — Sat, 06 Jul 2024 04:26:00 -0500

YAMP is constructed on Nextflow, a framework based on the dataflow programming model, which allows writing workflows that are highly parallel, easily portable (including on distributed systems), and very flexible and customisable, characteristics which have been inherited by YAMP. New modules can be added easily and the existing ones can be customised -- even though we have already provided default parameters deriving from our own experience.

Address of the bookmark: https://github.com/alesssia/YAMP

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/

CAUSEL: an epigenome- and genome-editing pipeline for establishing function of noncoding GWAS variants

BioJoker — Tue, 09 Apr 2019 07:23:37 -0500

Validated a widely accessible approach that can be used to establish functional causality for noncoding sequence variants identified by GWASs.

https://www.nature.com/articles/nm.3975

Address of the bookmark: https://www.nature.com/articles/nm.3975