You need to sequence DNA for a project. Which bioinformatics tools should you use?

The sequencing technologies evolved very fast. Bioinformatics tools and platforms also evolved together. I would choose a software which handle from sequencing platform till end of interpretation. DRAGEN/ZBOLT/A100 machines do end to end process. It helps to automate production environment effectively.

Looking into DNA sequencing tools, one must consider things like: Read length, Accuracy, Coverage depth, Cost per base, Throughput. NGS This massively parallel method sequences millions of fragments simultaneously, allowing for the sequencing of hundreds to thousands of genes at once. NextSeq This tool is useful when a short turnaround time is needed. MiSeq This low-output machine is used for testing libraries or for modest metagenomics or other targeted sequencing experiments. HiSeq This tool can generate an order of magnitude more reads than MiSeq, but it also takes an order of magnitude more time.

Bowtie2: An ultrafast and memory-efficient tool for aligning sequencing reads to large genomes. BWA (Burrows-Wheeler Aligner):A software package for mapping low-divergent sequences against a large reference genome. BLAST (Basic Local Alignment Search Tool): A suite of programs for comparing nucleotide or protein sequences to sequence databases. Minimap2:A versatile sequence alignment program for mapping genomic and spliced nucleotide sequences. ClustalW: A widely used multiple sequence alignment program for DNA, RNA, or protein sequences. MUSCLE (Multiple Sequence Comparison by Log-Expectation): A tool for creating multiple sequence alignments.

Alignment is a time-consuming process. Choose a workflow like nextflow or snakemake to efficiently use parallel computing (resources). bwa-mem is widely used for alignment purposes. STAR is a popular program for RNA sequencing alignement.

PFAM: A large collection of protein families, each represented by multiple sequence alignments and hidden Markov models (HMMs). UniProtKB: A comprehensive resource of protein sequence and functional information, including manually curated and automatically annotated records. NCBI Gene Database: Provides information on the molecular biology and genetics of a wide range of organisms, including gene annotations and functional descriptions. Gene Ontology (GO) Annotation Tools: Tools like AmiGO and QuickGO allow users to explore and retrieve GO annotations for genes and gene products. KEGG (Kyoto Encyclopedia of Genes and Genomes): Provides information on biological pathways, diseases, and drugs, including pathway annotations for genes.

Ensembl Variant Effect Predictor (VEP) that predict the functional consequences of genetic variants in your data. Use databases like gnomAD and Exac to also look for allelic frequency. ANNOVAR is a popular tool to annotate the variants. vcfanno also an effective option.

Depending on the type of genomic data you hold there are multiple bioinformatic tools that can do a good job. Most commonly in microbial spaces whether that be bacterial or viral, I have used Geneious to annotate. Other less known tools, such as PROKSEE have also been helpful.

Although sample specific data visualisations tools help lot. I personally like UCSC genome browser. It provides wider amounts of evidences and annotations in a given genomic positions. The visuals and custom usage features are awesome.

UCSC Genome Browser: A widely used web-based tool for visualizing and exploring genomic data. It supports a variety of genome assemblies and annotations. IGV (Integrative Genomics Viewer): A high-performance desktop tool for visualizing and exploring large-scale genomic data, including alignment files (BAM), variant calls, and annotations. JBrowse: An interactive and feature-rich JavaScript-based genome browser that allows for the visualization of genomic data.

The choice of tools depends on various factors such as the nature of your data (e.g short-read vs long-read sequencing) BLAST, BWA aid in sequence alignment. While SPAdes is prominent for sequence assembly. Variant calling tool like GATK identify genomic variations and for visualization options like IGV and R programming libraries.

There are many interactive tools out there that produce a myriad of results. It really comes down to what you want to produce, and how you want to use your data for that goal. An example of a powerful visualization tool that we use in the microbial realm is Krona which generates a dynamic HTML5 visualizations of hierarchical data, such as the taxonomic abundance found in a metagenome.

For aligning two DNA or protein sequences, one can use EMBOSS needle. For multiple sequence alignments, Clustal Omega works well.