BOL: Related items

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

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

MetaPlotR: a Perl/R pipeline for plotting metagenes of nucleotide modifications and other transcriptomic sites

Neel — Mon, 05 Nov 2018 08:12:45 -0600

An increasing number of studies are mapping protein binding and nucleotide modifications sites throughout the transcriptome. Often, these sites cluster in certain regions of the transcript, giving clues to their function. Hence, it is informative to summarize where in the transcript these sites occur. A metagene is a simple and effective tool for visualizing the distribution of sites along a simplified transcript model. In this work, we introduce MetaPlotR, a Perl/R pipeline for creating metagene plots.

Address of the bookmark: https://github.com/olarerin/metaPlotR

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

SLR-superscaffolder: A scaffold assemble pipeline for stLFR reads.

Jit — Fri, 14 Feb 2020 14:23:30 -0600

This is a scaffold assembler designed for stLFR reads[1]. It uses the link-reads information from stLFR reads to assemble contigs to scaffolds.

Here is an illustration of this pipeline:

Address of the bookmark: https://github.com/BGI-Qingdao/SLR-superscaffolder

SqueezeMeta: a fully automated metagenomics pipeline, from reads to bins

BioStar — Mon, 17 Aug 2020 05:25:10 -0500

SqueezeMeta is a full automatic pipeline for metagenomics/metatranscriptomics, covering all steps of the analysis. SqueezeMeta includes multi-metagenome support allowing the co-assembly of related metagenomes and the retrieval of individual genomes via binning procedures. Thus, SqueezeMeta features several unique characteristics:

Co-assembly procedure with read mapping for estimation of the abundances of genes in each metagenome
Co-assembly of a large number of metagenomes via merging of individual metagenomes
Includes binning and bin checking, for retrieving individual genomes
The results are stored in a database, where they can be easily exported and shared, and can be inspected anywhere using a web interface.
Internal checks for the assembly and binning steps inform about the consistency of contigs and bins, allowing to spot potential chimeras.
Metatranscriptomic support via mapping of cDNA reads against reference metagenomes

Address of the bookmark: https://github.com/jtamames/SqueezeMeta

JUDI: Just Do It

Jit — Mon, 06 Sep 2021 02:44:35 -0500

judi comes from the idea of bringing the power and efficiency of doit to execute any kind of task under many combinations of parameter settings.

https://github.com/ncbi/JUDI

Address of the bookmark: https://github.com/ncbi/JUDI

SqueezeMeta: a fully automated metagenomics pipeline, from reads to bins

BioStar — Sat, 06 Jul 2024 04:29:16 -0500

Co-assembly procedure with read mapping for estimation of the abundances of genes in each metagenome
Co-assembly of a large number of metagenomes via merging of individual metagenomes
Includes binning and bin checking, for retrieving individual genomes
The results are stored in a database, where they can be easily exported and shared, and can be inspected anywhere using a web interface.
Internal checks for the assembly and binning steps inform about the consistency of contigs and bins, allowing to spot potential chimeras.
Metatranscriptomic support via mapping of cDNA reads against reference metagenomes

Address of the bookmark: https://github.com/jtamames/SqueezeMeta

seqloc 0.6

Gudiya Pal — Sun, 28 Dec 2014 12:51:29 -0600

The Bio.SeqLoc modules in seqloc are designed to represent positions and locations (ranges of positions) on sequences, particularly nucleotide sequences. My original motivation for writing these packages was handing the locations of genes in eukaryotic genomes.

Handle sequence locations for bioinformatics http://www.ingolia-lab.org/seqloc-tutorial.html

Address of the bookmark: http://www.stackage.org/snapshot/nightly-2014-12-28/package/seqloc-0.6