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In bioinformatics, a sequence alignment is a way of arranging the sequences of DNA, RNA, or protein to identify regions of similarity that may be a consequence of functional, structural, or evolutionary relationships between the sequences. Aligned sequences of nucleotide or amino acid residues are typically represented as rows within a matrix. Gaps are inserted between the residues so that identical or similar characters are aligned in successive columns. Sequence alignments are also used for non-biological sequences, such as calculating the distance cost between strings in a natural language or in financial data.
A nucleic acid sequence is a succession of bases within the nucleotides forming alleles within a DNA or RNA (GACU) molecule. This succession is denoted by a series of a set of five different letters that indicate the order of the nucleotides. By convention, sequences are usually presented from the 5' end to the 3' end. For DNA, with its double helix, there are two possible directions for the notated sequence; of these two, the sense strand is used. Because nucleic acids are normally linear (unbranched) polymers, specifying the sequence is equivalent to defining the covalent structure of the entire molecule. For this reason, the nucleic acid sequence is also termed the primary structure.
In bioinformatics and biochemistry, the FASTA format is a text-based format for representing either nucleotide sequences or amino acid (protein) sequences, in which nucleotides or amino acids are represented using single-letter codes.
In bioinformatics, sequence assembly refers to aligning and merging fragments from a longer DNA sequence in order to reconstruct the original sequence. This is needed as DNA sequencing technology might not be able to 'read' whole genomes in one go, but rather reads small pieces of between 20 and 30,000 bases, depending on the technology used. Typically, the short fragments (reads) result from shotgun sequencing genomic DNA, or gene transcript (ESTs).
BioJava is an open-source software project dedicated to provide Java tools to process biological data. BioJava is a set of library functions written in the programming language Java for manipulating sequences, protein structures, file parsers, Common Object Request Broker Architecture (CORBA) interoperability, Distributed Annotation System (DAS), access to AceDB, dynamic programming, and simple statistical routines. BioJava supports a huge range of data, starting from DNA and protein sequences to the level of 3D protein structures. The BioJava libraries are useful for automating many daily and mundane bioinformatics tasks such as to parsing a Protein Data Bank (PDB) file, interacting with Jmol and many more. This application programming interface (API) provides various file parsers, data models and algorithms to facilitate working with the standard data formats and enables rapid application development and analysis.
The Biopython project is an open-source collection of non-commercial Python tools for computational biology and bioinformatics, created by an international association of developers. It contains classes to represent biological sequences and sequence annotations, and it is able to read and write to a variety of file formats. It also allows for a programmatic means of accessing online databases of biological information, such as those at NCBI. Separate modules extend Biopython's capabilities to sequence alignment, protein structure, population genetics, phylogenetics, sequence motifs, and machine learning. Biopython is one of a number of Bio* projects designed to reduce code duplication in computational biology.
In bioinformatics, a sequence logo is a graphical representation of the sequence conservation of nucleotides or amino acids . A sequence logo is created from a collection of aligned sequences and depicts the consensus sequence and diversity of the sequences. Sequence logos are frequently used to depict sequence characteristics such as protein-binding sites in DNA or functional units in proteins.
A Phred quality score is a measure of the quality of the identification of the nucleobases generated by automated DNA sequencing. It was originally developed for the computer program Phred to help in the automation of DNA sequencing in the Human Genome Project. Phred quality scores are assigned to each nucleotide base call in automated sequencer traces. The FASTQ format encodes phred scores as ASCII characters alongside the read sequences. Phred quality scores have become widely accepted to characterize the quality of DNA sequences, and can be used to compare the efficacy of different sequencing methods. Perhaps the most important use of Phred quality scores is the automatic determination of accurate, quality-based consensus sequences.
UGENE is computer software for bioinformatics. It works on personal computer operating systems such as Windows, macOS, or Linux. It is released as free and open-source software, under a GNU General Public License (GPL) version 2.
Phred is a computer program for base calling, that is to say, identifying a nucleobase sequence from fluorescence "trace" data generated by an automated DNA sequencer that uses electrophoresis and 4-fluorescent dye method. When originally developed, Phred produced significantly fewer errors in the data sets examined than other methods, averaging 40–50% fewer errors. Phred quality scores have become widely accepted to characterize the quality of DNA sequences, and can be used to compare the efficacy of different sequencing methods.
Phrap is a widely used program for DNA sequence assembly. It is part of the Phred-Phrap-Consed package.
FASTQ format is a text-based format for storing both a biological sequence and its corresponding quality scores. Both the sequence letter and quality score are each encoded with a single ASCII character for brevity.
The Variant Call Format (VCF) is a standard text file format used in bioinformatics for storing gene sequence variations. The format was developed in 2010 for the 1000 Genomes Project and has since been used by other large-scale genotyping and DNA sequencing projects. VCF is a common output format for variant calling programs due to its relative simplicity and scalability. Many tools have been developed for editing and manipulating VCF files, including VCFtools, which was released in conjunction with the VCF format in 2011, and BCFtools, which was included as part of SAMtools until being split into an independent package in 2014.
DNA nanoball sequencing is a high throughput sequencing technology that is used to determine the entire genomic sequence of an organism. The method uses rolling circle replication to amplify small fragments of genomic DNA into DNA nanoballs. Fluorescent nucleotides bind to complementary nucleotides and are then polymerized to anchor sequences bound to known sequences on the DNA template. The base order is determined via the fluorescence of the bound nucleotides This DNA sequencing method allows large numbers of DNA nanoballs to be sequenced per run at lower reagent costs compared to other next generation sequencing platforms. However, a limitation of this method is that it generates only short sequences of DNA, which presents challenges to mapping its reads to a reference genome. After purchasing Complete Genomics, the Beijing Genomics Institute (BGI) refined DNA nanoball sequencing to sequence nucleotide samples on their own platform.
SAMtools is a set of utilities for interacting with and post-processing short DNA sequence read alignments in the SAM, BAM and CRAM formats, written by Heng Li. These files are generated as output by short read aligners like BWA. Both simple and advanced tools are provided, supporting complex tasks like variant calling and alignment viewing as well as sorting, indexing, data extraction and format conversion. SAM files can be very large, so compression is used to save space. SAM files are human-readable text files, and BAM files are simply their binary equivalent, whilst CRAM files are a restructured column-oriented binary container format. BAM files are typically compressed and more efficient for software to work with than SAM. SAMtools makes it possible to work directly with a compressed BAM file, without having to uncompress the whole file. Additionally, since the format for a SAM/BAM file is somewhat complex - containing reads, references, alignments, quality information, and user-specified annotations - SAMtools reduces the effort needed to use SAM/BAM files by hiding low-level details.
Sequence Alignment Map (SAM) is a text-based format originally for storing biological sequences aligned to a reference sequence developed by Heng Li and Bob Handsaker et al. It was developed when the 1000 Genomes Project wanted to move away from the MAQ mapper format and decided to design a new format. The overall TAB-delimited flavour of the format came from an earlier format inspired by BLAT’s PSL. The name of SAM came from Gabor Marth from University of Utah, who originally had a format under the same name but with a different syntax more similar to a BLAST output. It is widely used for storing data, such as nucleotide sequences, generated by next generation sequencing technologies, and the standard has been broadened to include unmapped sequences. The format supports short and long reads (up to 128 Mbp) produced by different sequencing platforms and is used to hold mapped data within the Genome Analysis Toolkit (GATK) and across the Broad Institute, the Wellcome Sanger Institute, and throughout the 1000 Genomes Project.
Binary Alignment Map (BAM) is the comprehensive raw data of genome sequencing; it consists of the lossless, compressed binary representation of the Sequence Alignment Map-files.
Compressed Reference-oriented Alignment Map (CRAM) is a compressed columnar file format for storing biological sequences aligned to a reference sequence, initially devised by Markus Hsi-Yang Fritz et al.
The BED format is a text file format used to store genomic regions as coordinates and associated annotations. The data are presented in the form of columns separated by spaces or tabs. This format was developed during the Human Genome Project and then adopted by other sequencing projects. As a result of this increasingly wide use, this format had already become a de facto standard in bioinformatics before a formal specification was written.
References
- ↑ Li H.; Handsaker B.; Wysoker A.; Fennell T.; Ruan J.; Homer N.; Marth G.; Abecasis G.; Durbin R; 1000 Genome Project Data Processing Subgroup (2009) (2009). "The Sequence alignment/map (SAM) format and SAMtools". Bioinformatics. 25 (16): 2078–2079. doi:10.1093/bioinformatics/btp352. PMC 2723002 . PMID 19505943.
{{cite journal}}: CS1 maint: numeric names: authors list (link) - ↑ Accelrys (1998-10-02). "QUANTA: Protein Design. 3. Reading and Writing Sequence Data Files". Université de Montréal . Retrieved 2020-03-27.
- ↑ Glez-Peña, Daniel; Gómez-López, Gonzalo; Reboiro-Jato, Miguel; Fdez-Riverola, Florentino; Pisano, David G (2011-01-24). "PileLine: a toolbox to handle genome position information in next-generation sequencing studies". BMC Bioinformatics. 12: 31. doi: 10.1186/1471-2105-12-31 . ISSN 1471-2105. PMC 3037855 . PMID 21261974.
- ↑ Chisom, Halimat (2023-03-31). "File Formats Every Bioinformatician — Established or Upcoming — Must Know (and then some)". Medium. Retrieved 2023-11-11.
