BOL: Related items

Applied Statistics for Bioinformatics using R

Neel — Thu, 30 Aug 2018 03:45:39 -0500

The purpose of this book is to give an introduction into statistics in order to solve some problems of bioinformatics. Statistics provides procedures to explore and visualize data as well as to test biological hypotheses. The book intends to be introductory in explaining and programming elementary statistical concepts, thereby bridging the gap between high school levels and the specialized statistical literature

Bioinformatics 101 - Running BLAST

Tue, 03 Sep 2013 14:59:50 -0500

How to format the database for BLAST, run the command, view the output file, and use BioPerl and Perl to parse the output. By David Francis, Ohio State University. Delivered live at the Tomato Disease Workshop 2010. For more information, please visit http://www.extension.org/pages/32521/bioinformatics-101-video.

Post Doc Computational Biology, Bioinformatics - Network Biology & Data Science, NGS (m/f/d)

Sat, 15 Feb 2020 06:13:35 -0600

https://www.jobvector.de/jobs-stellenangebote/biologie-life-sciences/forschung-entwicklung/post-doc-computational-biology-bioinformatics-network-biology-data-science-ngs-129867.html?suid=e522e9793b41817e52ac58d6963b94e2519920df

Requirements
Doctoral degree in Bioinformatics, Computational Biology, (Bio)physics/-mathematics, Biochemistry/Biology or similar with strong quantitative and numeric focus
Ability to numerically process complex and large data sets
Good programming skills (R/Bioconductor and/or Python preferred, Linux is a plus)
Experience in analyzing next-generation sequencing data sets using network biology
Scientific publication record in applied bioinformatics
Familiarity with single cell NGS analyses and other –omics techniques is a plus, but not essential

Bioinformatics Head (Bioinformatics Manager III), Cancer Genomics Research Laboratory at Frederick National Laboratory

Wed, 18 Aug 2021 00:19:48 -0500

Frederick National Laboratory seeking an enthusiastic, creative, and seasoned bioinformatics professional to join our leadership team and direct the exceptional Bioinformatics Group at the Cancer Genomics Research Laboratory (CGR). CGR has a diverse team of bioinformatics and computational scientists that support all areas of bioinformatics and data analysis (infrastructure, data QC, pipeline development and maintenance, data curation and sharing, methodology development, statistical analyses, machine learning approaches, and scientific interpretation).

More at https://leidosbiomed.csod.com/ats/careersite/jobdetails.aspx?site=4&c=leidosbiomed&id=2040

Mycology Research Resources for Bioinformaticians: Unlocking the Fungal Kingdom

Neel — Fri, 13 Dec 2024 11:21:45 -0600

Mycology, the study of fungi, is a field that bridges ecology, medicine, and biotechnology. With advancements in bioinformatics, researchers now have unprecedented opportunities to explore the fungal kingdom at molecular, genetic, and ecological levels. From understanding pathogenic fungi to harnessing fungal enzymes for industrial applications, the potential is vast.

To fully leverage these opportunities, bioinformaticians require specialized tools and databases. This blog highlights essential resources for mycology research, focusing on databases, tools, and platforms tailored for fungal biology.

1. Fungal Databases

1.1. MycoCosm

Website: MycoCosm
Developed by the DOE Joint Genome Institute, MycoCosm is a comprehensive portal for fungal genomics. It offers genomic and transcriptomic data for a wide range of fungi, including saprobes, pathogens, and symbionts.

Key Features: Genome browsers, comparative genomics tools, and functional annotations.
Best For: Large-scale studies on fungal evolution and ecology.

1.2. FungiDB

Website: FungiDB
FungiDB is an integrated genomic resource for fungal pathogens and non-pathogens. It provides access to genome sequences, transcriptomic data, and functional annotations.

Key Features: Advanced search options, BLAST, and pathway analysis tools.
Best For: Studying fungal pathogenesis and host-pathogen interactions.

1.3. Index Fungorum

Website: Index Fungorum
This nomenclatural database provides information on the scientific names of fungi. It’s an essential resource for taxonomists and researchers focused on fungal biodiversity.

Key Features: Taxonomic hierarchy and synonymy tracking.
Best For: Identifying and classifying fungal species.

1.4. UNITE

Website: UNITE
UNITE is a specialized database for fungal ITS (Internal Transcribed Spacer) sequences, often used in fungal identification and phylogenetics.

Key Features: Curated reference datasets and community annotations.
Best For: Environmental mycology and microbial ecology studies.

2. Analytical Tools

2.1. Funannotate

Repository: GitHub - Funannotate
Funannotate is a genome annotation tool designed for fungi. It supports tasks like gene prediction, functional annotation, and orthology analysis.

Best For: Annotating newly sequenced fungal genomes.

2.2. BUSCO (Benchmarking Universal Single-Copy Orthologs)

Website: BUSCO
BUSCO evaluates genome assembly and annotation completeness using orthologs. It includes a fungal-specific dataset.

Best For: Assessing the quality of fungal genome assemblies.

2.3. Pathogen-Host Interactions Database (PHI-base)

Website: PHI-base
PHI-base is a manually curated resource containing information on pathogen-host interactions, including fungal pathogens.

Best For: Exploring virulence factors and host-pathogen relationships.

3. Visualization Platforms

3.1. Cytoscape

Website: Cytoscape
A powerful tool for visualizing molecular interaction networks, Cytoscape can be used to study protein-protein interactions, gene networks, and metabolic pathways in fungi.

Best For: Network biology and functional genomics.

3.2. iTOL (Interactive Tree of Life)

Website: iTOL
iTOL is an interactive tool for visualizing phylogenetic trees.

Best For: Displaying fungal phylogenies and comparing evolutionary relationships.

4. Community Resources

4.1. Mycological Society of America (MSA)

Website: MSA
The MSA promotes fungal research and provides access to resources, conferences, and publications.

Best For: Networking with fungal researchers and accessing recent studies.

4.2. OpenFungi

Website: OpenFungi
OpenFungi is an open-source initiative providing fungal genomic and transcriptomic datasets for research and education.

Best For: Sharing and accessing public fungal datasets.

5. Genomics Workflows

5.1. Galaxy

Website: Galaxy Project
Galaxy offers a web-based platform for reproducible bioinformatics workflows, including tools for fungal genome and transcriptome analysis.

Best For: User-friendly analysis pipelines without requiring coding skills.

5.2. Snakemake

Repository: Snakemake
A flexible pipeline management tool that supports fungal data processing and analysis.

Best For: Custom workflows for large-scale fungal datasets.

Conclusion

Fungal research is a rapidly growing field with vast implications for medicine, agriculture, and industry. For bioinformaticians, the availability of specialized resources—databases, tools, and community platforms—opens doors to innovative discoveries. Whether you are investigating fungal genomics, studying host-pathogen interactions, or exploring fungal biodiversity, the resources outlined above will empower your research journey.

Dive into these resources and help unravel the mysteries of the fungal kingdom!

List of bioinformatics packages for NGS analysis !

Rahul Nayak — Sat, 20 Mar 2021 00:28:51 -0500

Package suites gather software packages and installation tools for specific languages or platforms. We have some for bioinformatics software.

Bioconductor – A plethora of tools for analysis and comprehension of high-throughput genomic data, including 1500+ software packages. [ paper-2004 | web ]
Biopython – Freely available tools for biological computing in Python, with included cookbook, packaging and thorough documentation. Part of the Open Bioinformatics Foundation. Contains the very useful Entrez package for API access to the NCBI databases. [ paper-2009 | web ]
Bioconda – A channel for the conda package manager specializing in bioinformatics software. Includes a repository with 3000+ ready-to-install (with conda install) bioinformatics packages. [ paper-2018 | web ]
BioJulia – Bioinformatics and computational biology infastructure for the Julia programming language. [ web ]
Rust-Bio – Rust implementations of algorithms and data structures useful for bioinformatics. [ paper-2016 ]
SeqAn – The modern C++ library for sequence analysis.

Troyanskaya Lab

Tue, 04 Feb 2020 06:40:36 -0600

The goal of our research is to interpret and distill this complexity through accurate analysis and modeling of molecular pathways, particularly those in which malfunctions lead to the manifestation of disease. We are inventing integrative methods for systems-level pathway modeling through integrative analysis of genome-scale datasets. We apply these approaches in studying challenging biological problems, such as how pathways function in diverse cell types and how they change dynamically.

https://function.princeton.edu/

Frequent parameters for bioinformatics tools !

BioStar — Tue, 27 Oct 2020 19:42:32 -0500

Third party executable parameters and options.

Trimmomatic

“ILLUMINACLIP:...:2:30:10”

“LEADING:15”

“TRAILING:15”

“SLIDINGWINDOW:4:20”

“MINLEN:20”

“TOPHRED33”

Filtlong

--min_length 500

--min_mean_q 85

--min_window_q 65

FastQ Screen

--aligner bowtie2' (bwa for PacBio)

--subset 1000 (for PacBio)

SPAdes

--careful

--disable-gzip-output

--cov-cutoff auto

--phred-offset 33

HGAP

Pbalign.task_options.min_accuracy: 70

Pbalign.task_options.no_split_subreads: false

Genomic_consensus.task_options.min_confidence: 40

falcon_ns.task_options.HGAP_GenomeLength_str:

6000000

Pbcoretools.task_options.read_length: 0

Genomic_consensus.task_options.use_score: 0

Pbalign.task_options.min_length: 50

Pbalign.task_options.algorithm_options: --minMatch 12

--bestn 10 --minPctSimilarity 70.0

Pbalign.task_options.hit_policy: randombest

Pbcoretools.task_options.other_filters: rq >= 0.7

Pbalign.task_options.concordant: false

Genomic_consensus.task_options.min_coverage: 5

falcon_ns.task_options.HGAP_SeedCoverage_str: 30

falcon_ns.task_options.HGAP_AggressiveAsm_bool: false

Genomic_consensus.task_options.algorithm: best

falcon_ns.task_options.HGAP_SeedLengthCutoff_str: -1

Genomic_consensus.task_options.diploid: false

MeDuSa

-random 100

Prokka

--usegenus

--force

--addgenes

--rfam

--rawproduct

cmsearch (taxonomy, 16S)

--rfam

--noali

blastn (taxonomy, 16S)

-evalue 1E-10

blastn (MLST)

-ungapped

-dust no

-evalue 1E-20

-word_size 32

-culling_limit 2

-perc_identity 95

blastp (VF)

-culling_limit 2

RGI (ABR)

--input_type contig

bowtie2 (mapping)

--sensitive

minimap2 (mapping)

-a

-x map-ont

samtools mpileup (SNP detection)

-uRI

bcftools call (SNP detection)

--variants-only

--skip-variants indels

--output-type v

--ploidy 1

-c

SNPsift filter (SNP detection)

"( QUAL >= 30 ) & (( na FILTER ) | (FILTER = 'PASS')) &

( DP >= 20 ) & ( MQ >= 20 )"

SNPeff ann (SNP detection)

-nodownload

-no-intron

-no-downstream

-no SPLICE_SITE_REGION

-upDownStreamLen 250

bcftools consensus

(phylogenetic tree)

--haplotype 1

fasttreemp

-nt

-boot 100

roary

-e

-n

-cd 100

-g 100000

R 3.5.0 has been Released!

Jit — Thu, 26 Apr 2018 11:31:58 -0500

The latest version of R is a major release! It comes with a ton of new features, including performance and speed improvements
All R packages will now be byte-compiled, hence boosting packages installed from GitHub
You may need to re-install all previously installed R packages; old scripts however will continue to work normally

More at https://cran.r-project.org/doc/manuals/r-release/NEWS.html

VCFtools: perform common tasks with VCF files such as file validation, file merging, intersecting, complements

Rahul Nayak — Tue, 07 Aug 2018 10:01:46 -0500

VCFtools contains a Perl API (Vcf.pm) and a number of Perl scripts that can be used to perform common tasks with VCF files such as file validation, file merging, intersecting, complements, etc. The Perl tools support all versions of the VCF specification (3.2, 3.3, 4.0, 4.1 and 4.2), nevertheless, the users are encouraged to use the latest versions VCFv4.1 or VCFv4.2. The VCFtools in general have been used mainly with diploid data, but the Perl tools aim to support polyploid data as well. Run any of the Perl scripts with the --help switch to obtain more help.

Many of the Perl scripts require that the VCF files are compressed by bgzip and indexed by tabix (both tools are part of the tabix package, available for download here). The VCF files can be compressed and indexed using the following commands

bgzip my_file.vcf
tabix -p vcf my_file.vcf.gz

http://vcftools.sourceforge.net/perl_module.html

Address of the bookmark: http://vcftools.sourceforge.net/perl_module.html