BOL: Related items

DIAL

Abhimanyu Singh — Wed, 01 Mar 2017 08:42:28 -0600

A computational pipeline for identifying single-base substitutions between two closely related genomes without the help of a reference genome. DIAL works even when the depth of coverage is insufficient for de novo assembly, and it can be extended to determine small insertions/deletions. Our main motivation is to use this tool to survey the genetic diversity of endangered species as the identified sequence differences can be used to design genotyping arrays to assist in the species' management.

http://www.bx.psu.edu/~ratan/

Address of the bookmark: http://www.bx.psu.edu/miller_lab/

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

Bioinformatician in pipeline development

Tue, 17 Dec 2024 23:43:54 -0600

Are you interested in working with pipeline development in bioinformatics, with the support of competent and friendly colleagues in an international environment? Are you looking for an employer that invests in sustainable employeeship and offers safe, favourable working conditions? We welcome you to apply for a position as Bioinformatician in pipeline development at Uppsala University.

National Bioinformatics Infrastructure Sweden (NBIS) (nbis.se) plays an important role in advancing life science research in Sweden by providing expert support and developing cutting-edge bioinformatics infrastructure. Operating as a truly national initiative, NBIS employs more than 120 bioinformaticians, system developers, and data stewards across multiple locations in Sweden. It serves as the bioinformatics platform at SciLifeLab, a national resource that facilitates research in molecular biosciences by offering access to state-of-the-art technologies and technical expertise. With strong ties to data-producing facilities and ongoing collaborations with leading research groups, NBIS is ideally positioned to support world-class bioinformatics analyses. Furthermore, NBIS is the Swedish node in ELIXIR, the European infrastructure for biological information.

NBIS is seeking an experienced bioinformatician to support both Swedish and international projects. As part of our dynamic team, you will work closely with researchers to process large-scale biological data and contribute to advancing our data analysis infrastructure. Strong problem-solving skills, attention to detail, and the ability to troubleshoot complex bioinformatics pipelines are essential for success in this role. Flexibility and a willingness to learn are also important, as NBIS continually adapts to meet the evolving needs of the Swedish research community.

More at https://www.uu.se/en/about-uu/join-us/jobs-and-vacancies/job-details?query=778701

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

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

dnaPipeTE: a pipeline designed to find, annotate and quantify Transposable Elements

Jit — Mon, 12 Aug 2019 21:56:08 -0500

dnaPipeTE (for de-novo assembly & annotation Pipeline for Transposable Elements), is a pipeline designed to find, annotate and quantify Transposable Elements in small samples of NGS datasets. It is very useful to quantify the proportion of TEs in newly sequenced genomes since it does not require genome assembly and works on small datasets (< 1X).

https://github.com/clemgoub/dnaPipeTE/wiki/dnaPipeTE-WIKI-home

Address of the bookmark: https://github.com/clemgoub/dnaPipeTE

gapFinisher: A reliable gap filling pipeline for SSPACE-LongRead scaffolder output

Rahul Nayak — Thu, 14 May 2020 15:13:30 -0500

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 lines.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6733440/

Address of the bookmark: https://github.com/kammoji/gapFinisher

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

LncPipe:A Nextflow-based pipeline for comprehensive analyses of long non-coding RNAs from RNA-seq datasets

LEGE — Fri, 17 Sep 2021 01:57:02 -0500

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 lncRNAs annotation strategy, optimized calculating efficiency, diversified classification and interactive analysis report. LncPipe allows users additional control in interuppting the pipeline, resetting parameters from command line, modifying main script directly and resume analysis from previous checkpoint.

Ref https://www.lncrnablog.com/lncpipe-a-nextflow-based-pipeline-for-identification-and-analysis-of-long-non-coding-rnas-from-rna-seq-data/

Address of the bookmark: https://github.com/likelet/LncPipe