BOL: Related items

maftools

Surabhi Chaudhary — Fri, 17 Dec 2021 03:18:28 -0600

With advances in Cancer Genomics, Mutation Annotation Format (MAF) is being widely accepted and used to store somatic variants detected. The Cancer Genome Atlas Project has sequenced over 30 different cancers with sample size of each cancer type being over 200. Resulting data consisting of somatic variants are stored in the form of Mutation Annotation Format. This package attempts to summarize, analyze, annotate and visualize MAF files in an efficient manner from either TCGA sources or any in-house studies as long as the data is in MAF format.

https://www.bioconductor.org/packages/devel/bioc/vignettes/maftools/inst/doc/maftools.html

Address of the bookmark: https://github.com/PoisonAlien/maftools

List of bioinformatics workflow management tools !

Rahul Nayak — Sat, 20 Mar 2021 00:15:25 -0500

Here are list of Workflow Managers

BigDataScript – A cross-system scripting language for working with big data pipelines in computer systems of different sizes and capabilities. [ paper-2014 | web ]
Bpipe – A small language for defining pipeline stages and linking them together to make pipelines. [ web ]
Common Workflow Language – a specification for describing analysis workflows and tools that are portable and scalable across a variety of software and hardware environments, from workstations to cluster, cloud, and high performance computing (HPC) environments. [ web ]
Cromwell – A Workflow Management System geared towards scientific workflows. [ web ]
Galaxy – a popular open-source, web-based platform for data intensive biomedical research. Has several features, from data analysis to workflow management to visualization tools. [ paper-2018 | web ]
Nextflow (recommended) – A fluent DSL modelled around the UNIX pipe concept, that simplifies writing parallel and scalable pipelines in a portable manner. [ paper-2018 | web ]
Ruffus – Computation Pipeline library for python widely used in science and bioinformatics. [ paper-2010 | web ]
SeqWare – Hadoop Oozie-based workflow system focused on genomics data analysis in cloud environments. [ paper-2010 | web ]
Snakemake – A workflow management system in Python that aims to reduce the complexity of creating workflows by providing a fast and comfortable execution environment. [ paper-2018 | web ]
Workflow Descriptor Language – Workflow standard developed by the Broad. [ web ]

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/

Orthoflow: workflow for phylogenetic inference of genome-scale datasets of protein-coding genes

LEGE — Wed, 21 Feb 2024 06:13:08 -0600

Orthoflow is a workflow for phylogenetic inference of genome-scale datasets of protein-coding genes. Our goal was to make it straightforward to work from a combination of input sources including annotated contigs in Genbank format and FASTA files containing CDSs. It uses several state of the art inference methods for orthology inference, either based on HMM profiles or de novo inference of orthogroups. Through the use of OrthoSNAP, many additional ortholog alignments can be generated from multi-copy gene families. For phylogenetic inference, users can choose a supermatrix approach and/or gene tree inference followed by supertree reconstruction. Users can specify a range of alignment filtering settings to retain high-quality alignments for phylogenetic inference. The workflow produces a detailed report that, in addition to the phylogenetic results, includes a range of diagnostics to verify the quality of the results.

Address of the bookmark: https://github.com/rbturnbull/orthoflow

Sequanix: a dynamic graphical interface for Snakemake workflows

BioStar — Wed, 12 Feb 2020 01:20:34 -0600

A Python library dedicated to NGS analysis (e.g., tools to visualise standard NGS formats).
A set of pipelines dedicated to NGS in the form of Snakefiles (Makefile-like with Python syntax based on snakemake framework) with more than 80 re-usable rules (see Rules).
Original tools to help in the creation of such pipelines including HTML reports.
Standalone applications:
1. sequana_coverage ease the extraction of genomic regions of interest and genome coverage information
2. sequana_taxonomy performs a quick taxonomy of your FastQ. This requires dedicated databases to be downloaded.
3. Sequanix: GUI for snakemake workflows, a GUI for Snakemake workflows (hence Sequana pipelines as well)
More at https://sequana.readthedocs.io/en/master/

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

snakepipes: A toolkit based on snakemake and python for analysis of NGS data

Jit — Thu, 30 May 2019 04:06:13 -0500

snakePipes are flexible and powerful workflows built using snakemake that simplify the analysis of NGS data.

DNA-mapping*
ChIP-seq*
RNA-seq*
ATAC-seq*
scRNA-seq
Hi-C
Whole Genome Bisulfite Seq/WGBS

(*Also available in "allele-specific" mode)

snakePipes can be installed via conda :

'conda install -c mpi-ie -c bioconda -c conda-forge snakePipes'.

Source code (https://github.com/maxplanck-ie/snakepipes) and documentation (https://snakepipes.readthedocs.io/en/latest/) are available online.

Address of the bookmark: https://github.com/maxplanck-ie/snakepipes

Postdoctoral Associate - Bioinformatics at Duke University Medical Center

Sat, 10 Aug 2013 18:38:38 -0500

The Department of Biostatistics and Bioinformatics at Duke University Medical Center is seeking a Postdoctoral Associate for a one year appointment to work on several high-dimensional research projects. The specific goals of the project are to identify genes or molecular markers that are predictive of clinical outcomes in renal and prostate cancer.

Candidates must have: a PhD degree in statistics, biostatistics or bioinformatics, extensive experience in analyzing high-dimensional data (microarray, SNP, CNVs) and of validation approaches. In addition, experience in penalized regression methods, data base manipulation; and strong programming skills in order to conduct Monte Carlo studies and applications (R). Candidate must have excellent communication skills (verbal, written and presentation), a strong proficiency in Linux system.

This position is available immediately and will be filled as soon as possible. Appointment could be extended beyond the first year based on additional funding.

For more information about the Department of Biostatistics and Bioinformatics, please visit our website: http://www.biostat.duke.edu.

For more info: http://biostat.duke.edu/sites/biostat.duke.edu/files/Halabi%20-%20Postdoc%20Job%20Posting%202013%20updated.pdf

Duke University is an Equal Opportunity/Affirmative Action Employer.

A-allele of SLC24A5 gene is found to be responsible for variation in skin color of South-East Asians and Europeans

Rahul Agarwal — Tue, 12 Nov 2013 21:02:27 -0600

Key finding:

rs1426654 SNP of SLC24A5 gene is decider of skin pigmentation variation in South Asia
rs1426654-A allele is widely spread throughout the Indian subcontinent
Skin pigmentation is also account by the combination of processes like selection and demographic history of populations affected by their language and origin
Sign of positive selection in Europeans, Middle East, Pakistan, Central Asia and North India but not in South India
In European , A-allele is almost reached to fixation

Paper:

http://www.plosgenetics.org/article/info%3Adoi%2F10.1371%2Fjournal.pgen.1003912

SNPGenie

Jit — Thu, 30 Mar 2017 17:38:02 -0500

SNPGenie is a Perl script for estimating evolutionary parameters, mainly from pooled next-generation sequencing (NGS) single-nucleotide polymorphism (SNP) variant data. SNP reports (acceptable in a variety of formats) much each correspond to a single population, with variants called relative to a single reference sequence (one sequence in one FASTA file). Just run the main script, snpgenie.pl, in a directory containing the necessary input files, and we take care of the rest! For the earlier version, see Hughes Lab Bioinformatics Resource.

Address of the bookmark: https://github.com/hugheslab/snpgenie

Platypus: A Haplotype-Based Variant Caller For Next Generation Sequence Data

Shruti Paniwala — Thu, 25 Oct 2018 06:14:55 -0500

Platypus is a tool designed for efficient and accurate variant-detection in high-throughput sequencing data. By using local realignment of reads and local assembly it achieves both high sensitivity and high specificity. Platypus can detect SNPs, MNPs, short indels, replacements and (using the assembly option) deletions up to several kb. It has been extensively tested on whole-genome, exon-capture, and targeted capture data, it has been run on very large datasets as part of the Thousand Genomes and WGS500 projects, and is being used in clinical sequencing trials in the Mainstreaming Cancer Genetics programme.

Tutorial https://github.com/andyrimmer/Platypus/blob/master/misc/README.txt

Address of the bookmark: http://www.well.ox.ac.uk/platypus