The genetic material of every living organism is composed of nucleotides, called DNA/RNA. Genes are a part of this genome that codes for proteins. Various genes cause various metabolic activities. Defects in genes result in dysfunctionalities and diseases.
The identification and analysis of genes are necessary for early detection of flaws at a genetic level. By employing the bioinformatical software and tools, one can study about the metagenomics, genes and biological molecules.
In this article, we have briefly discussed the best gene analysis software and tools that can be employed for effective molecular studies at the fundamental level.
What are The Best Gene Analysis Software and Tools for Cutting-Edge Research?
Many Gene analysis software and tools are available for carrying out biological computations. However, some tools are high quality result producing.
The graphical representations and images are publication-ready. Go for the tools that produce good-quality results and are cited in well-received journals. The accuracy and purpose of analysis must be met after the executions.
Given below is the list of gene analysis software. You can use them according to the purpose of research- prediction, annotation, gene expression, functional properties and more. Most of the tools mentioned in this list are free gene analysis software.
1. BLAST
Basic Local Alignment Search Tool or BLAST is an open source employed for local search and alignment of gene sequences. It is available on the official website of the National Center for Biotechnological Information. Runs on web browser, can be downloaded also.
The different versions of the tool are available which makes it incredibly dynamic. Different specialised searches such as smartBLAST, Primer-BLAST, CD search, CDART, multiple alignment, MOLE-BLAST, global align, and VecScreen are available.
Web BLAST for nucleotide-nucleotide sequence, translated nucleotide-protein sequence, protein-translated nucleotide sequence, and protein-protein sequences are available. Search can be performed by entering the organism’s common name, scientific name or taxonomy ID.
KEY FEATURES
- The output results are graphical summaries
- Pictorial representations for quick understanding
- Different parameters for filtering the results
- Highly precise, publication-ready and accurate results
- Cloud servers and BLAST API are available
2. MetaGene
MetaGene is a publicly accessible and free-to-use tool. A prokaryotic gene finding software for the identification of protein-coding regions. The tool utilises di-codon frequencies estimated by the guanine and cytosine content of the given query sequence with other parameters.
It can predict the entire range of genes in prokaryotes depending on the anonymous genomics sequences of a few hundred bases. The sensitivity is 95% and 90% specificity for artificial shotgun sequences.
It automatically selects the proper set for a given sequence using the domain classification method. Domain classification method works properly and assigns domain information to more than 90% of the artificial shotgun sequence.
KEY FEATURES
- There are two sets of code on frequency interpolation- bacteria and archaea
- It predicts all the annotated genes and a notable number of novel genes
- Domain classification method adopted
- It can be applied to metagenomics projects and field expansion
3. Glimmer
Glimmer is a gene-finding system in microbes- bacteria, archaea, and viruses. Available for download on local machines. It is OSI Certified open source software and free to use. Performs the annotation of thousands of microbial genomes.
Glimmer uses a dynamic programming algorithm to find the set of ORFs with the maximum score. It uses Interpolated Markov models IMMs for gene composition capturing. Gene regions are identified in the coding regions and distinguished from the non-coding regions.
There are two versions available- the eukaryotic version (GlimmerHMM site) and the metagenomic version (Glimmer-MG site). Both versions are separate but use Glimmer-style IMMs for a distinction between coding and non-coding DNA.
KEY FEATURES
- Gene identification and annotation in DNA
- Individual version for eukaryotic and prokaryotic genes
- Achieve the greatest sensitivity for every read length
- Identifies sequences with high precision
4. FragGeneScan
FragGeneScan is a popular gene analysis bioinformatics tool. Used for finding fragmented genes in short reads. The software combines sequencing error models and codon usages in an HMM to improve the prediction of protein–encoding regions in short reads.
Identifies genes on three conditions of gene longer than 60 bp, the gene has a start codon or is in a match state, the gene has a stop codon or match state. It is also used for gene prediction in prokaryotes for genomes and incomplete assemblies.
KEY FEATURES
- Built on Hidden Markov Model HMM
- Identifies genes on different parameters
- Incorporates codon usage bias, sequencing error models and start/stop codon patterns in a unified model
- Identifies the best path of hidden state for a given short read
5. GeneMark
Developed by the Georgia Institute of Technology, GeneMark is a composition of gene prediction programmes with popularity among the science community. The different versions of the software are available for download on Linux and macOS platforms.
Gene prediction occurs in microbes, prokaryotes, metagenomes, metatranscriptomes, and more. Also predicts the gene in eukaryotes, transcripts, viruses, phages and plasmids.
The novel genomics sequences can be analysed by GeneMarkS with Heuristic models.
The versions are- GeneMarkS-2, GeneMark-ES/ET/EP, GeneMarkS, GeneMark.hmm eukaryotic, MetaGeneMark, ParseRNAseq, GeneTack, MetaGeneTack, GeneMarkS-T.
KEY FEATURES
- Genome assembly quality assessment tool (QUAST)
- Metagenomic analysis and assembly tool (MetAMOS)
- Eukaryotic genome annotation pipeline (MAKER2)
- Eukaryotic RNA-Seq-based genome annotation pipeline (BRAKER1)
- Eukaryotic Protein based genome annotation pipeline (BRAKER2)
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6. GENSCAN
GENSCAN, developed by Standford University is a program that predicts complete gene structures in genomic DNA. It is freely available for academic purposes. Compatible with UNIX platforms only. The MIT server also provides access to the GENESCAN program.
It predicts the locations and exons-introns structures of genes in different organisms on their genomic DNA. Sequences up to 1MBP can be accepted onto the server. The parameters for execution such as exon cutoff, organism, and output formats are available.
For larger sequences (>1MBP) the local copy of the program can be requested. The Platform is automated, less time-consuming, higher limit of sensitivity for the detection of low clonal cell numbers.
KEY FEATURES
- Several parameter settings before execution
- Available on web browsers and on local machines depending on the size of query
- Automated pipeline, less labour intensive, sensitivity limit
- Output format- peptides or CDS peptides
7. GenomeScan
Genomescan is another platform for gene analysis developed by MIT. It performs executions for homologous gene structures on the genomes of various organisms. It also predicts exon-intron structures of genes in genomic sequences.
The input file includes protein homology details when predicting the genes. Using BLASTX, such proteins can be detected or run the GENSCAN (followed by BLASTP) and then using those results as input GenomeScan. The file format is expected to be FastA (<1MBP).
Various parameter settings such as organism type, print output options, DNA sequences or protein sequences files are available.
KEY FEATURES
- Available on the web browser, extension of GENSCAN
- Numerous parameter settings before executions
- Accepts DNA/protein sequences (FastA format)
- Automated, fast and reliable results
Also Check: 30+ Best Bioinformatics Software & Tools
8. Geneid
Geneid developed by Genome Bioinformatics Research Lab for gene prediction in anonymous genomic sequences. Uses the Position Weight Arrays (PWAs) for scoring. Splicing of sites followed by start/stop codon prediction and scoring using PWAs. Exons are identified next.
From the exons, the gene structure is inferred and assembled. Supports integration of gff files with predictions from multiple sites. Accuracy is comparable to other similar tools. The speed and memory offered are good. It takes 3 hours to analyze the whole human genome (1GB/hr)
KEY FEATURES
- The accuracy of the results is comparable to the ab initio gene prediction tools
- Multiple parameters supported, efficient in memory and speed usage, quick results
- Offer integration of predictions from blast, HSPs, ESTs and annotating genomic sequences
- Output files can be customized to different detail levels, several formats
9. GeMoMa
Gene Model Mapper GeMoMa is available on the public web server and free to use. It is a homology-based gene prediction bioinformatics tool. It uses the protein-coding genes annotation file as a reference genome for inferring the annotation of protein-coding genes in the target/unknown genome.
Utilizes protein sequence and intron position conservation. It allows splicing site prediction with the help of RNA-seq evidence incorporation. The web server allows a limited number of reference genes.
Prefer command line program for unlimited use of the platform or integrate GeMoMa with Galaxy platform.
KEY FEATURES
- Huge flexibility in the use of modular homology-based prediction
- Customize the parameters as per your requirements
- Decrease ct and increase p to obtain more contigs in final results
- Multiple reference genomes can be used, RNA-seq data is not necessarily required
10. ATGpr
ATGpr is available freely on the public web server for the identification of starter codons in cDNA sequences. It determines if there are any initiation codons present or absent in cDNA and which ATG codon is the initiation codon when found to be present.
The genes that code for proteins can be identified effectively with the help of this tool in unknown genomes of varying organisms. One of the most frequently used and well-cited bioinformatics software available for analysis.
KEY FEATURES
- Effective in detecting the initiator codon in a cDNA sequence
- The results are fast and reliable
- Protein coding genes can be identified with ease
- Uses linear discriminant analysis method
In this article, we have brought attention to the best gene analysis software present there for gene expression analysis and general gene analysis. Most of them are gene prediction tools from the genome of known/unknown organisms.
Gene detection and functional analysis are critical for understanding the mechanisms of genetic structure and how it works!
