ANNOVAR (ANNOtate VARiation) is a bioinformatics software tool for the interpretation and prioritization of single nucleotide variants (SNVs), insertions, deletions, and copy number variants (CNVs) of a given genome.
It has the ability to annotate human genomes hg18, hg19, hg38, and model organisms genomes such as: mouse (Mus musculus), zebrafish (Danio rerio), fruit fly (Drosophila melanogaster), roundworm (Caenorhabditis elegans), yeast (Saccharomyces cerevisiae) and many others. The annotations could be used to determine the functional consequences of the mutations on the genes and organisms, infer cytogenetic bands, report functional importance scores, and/or find variants in conserved regions. ANNOVAR along with SNP effect (SnpEFF) and Variant Effect Predictor (VEP) are three of the most commonly used variant annotation tools.
Background
The cost of high throughput DNA sequencing has reduced drastically from around $100 million/human genome in 2001 to around $1000/human genome in 2017. Due to this increase in accessibility, high throughput DNA sequencing has become more widely used in research and clinical settings. Some common areas that utilize high throughput DNA sequencing extensively are: Whole Exome Sequencing, Whole Genome Sequencing (WGS), and genome wide association studies (GWAS).
There are a growing number of tools available seeking to comprehensively manage, analyze and interpret the enormous amount of data generated from high-throughput DNA sequencing. The tools are required to be efficient and robust enough to analyze a large number of variants (more than 3 million in human genome) though sensitive enough to identify rare and clinically relevant variants that are likely harmful/deleterious. ANNOVAR was developed by Kai Wang in 2010 at the Center for Applied Genomics in Children's Hospital of Philadelphia. It is a type of variant annotation tool that compiles deleterious genetic variant prediction scores from programs such as PolyPhen, ClinVar, and CADD and annotates the SNVs, insertions, deletions, and CNVs of the provided genome. ANNOVAR is one of the first efficient, configurable, extensible and cross-platform compatible variant annotation tools created.
In terms of the larger bioinformatics workflow, ANNOVAR fits in near the end, after DNA sequencing reads having between mapped, aligned, and variants have been predicted from an alignment file (BAM), also known as variant calling. This process will produce a resultant VCF file, a tab-separated text file in a tabular like structure, containing genetic variants as rows. This file can then be used as input into the ANNOVAR software program for the variant annotation process, outputting interpretations of the variants identified from the upstream bioinformatics pipeline.
Types of functional annotation of genetic variants
Gene-based annotation This approach identifies whether the input variants cause protein coding changes and the amino acids that are affected by the mutations. The input file can be composed of exons, introns, intergenic regions, splice acceptor/donor sites, and 5′/3′ untranslated regions. The focus is to explore the relationship between non-synonymous mutations (SNPs, indels, or CNVs) and their functional impact on known genes. Especially, gene-based annotation will highlight the exact amino acid change if the mutation is in the exonic region and the predicted effect on the function of the known gene. This approach is useful for identifying variants in known genes from Whole Exome Sequencing data.
Region-based annotation This approach identifies deleterious variants in specific genomic regions based on the genomic elements around the gene. Some categories region-based annotation will take into account are:
Is the variant in a known conserved genomic region?: Mutations occur during mitosis and meiosis. If there is no selective pressure for specific nucleotide sequences, then all areas of a genome would be mutated at equal rates. The genomic regions that are highly conserved indicate genomic sequences that are essential to the organism's survival and/or reproductive success. Thus, if the variant disrupts a highly conserved region, the variant is likely highly deleterious. Is the variant in a predicted transcription factor binding site?: DNA is transcribed into messenger RNA (mRNA) by RNA polymerase II. This process can be modulated transcription factors which can enhance or inhibit binding of RNApol II. If the variant disrupts a transcription factor binding site then transcription of the gene could be altered causing changes in gene expression level and/or protein production amount. This changes could cause phenotypic variations. Is the variant in a predicted miRNA target site?: MicroRNA (miRNA) is a type of RNA that complementary binds to targeted mRNA sequence to suppress or silence the translation of the mRNA. If the variant disrupts the miRNA target location, the miRNA could have altered binding affinity to the corresponding gene transcript thus changing the mRNA expression level of the transcript. This could further impact protein production levels which could cause phenotypic variations. Is the variant predicted to interrupt a stable RNA secondary structure?: RNA can function at the RNA level as non-coding RNA or be translated into proteins for downstream processes. RNA secondary structures are extremely important in determining the correct half-life and function of those RNA. Two RNA species with tightly regulated secondary structures are ribosomal RNA (rRNA) and transfer RNA (tRNA) which are essential in translation of mRNA to protein. If the variant disrupts the stability of the RNA secondary structure, the half-life of the RNA could be shortened thus lowering the concentration of RNA in the cell.
Non-coding regions encompasses 99% of the human genome and region-based annotation is extremely useful in identifying variants in those regions. This approach can be used on WGS data.
Filter-based annotation This approach identifies variants that are documented in specific databases. The variants could be obtained from dbSNP, 1000 Genomes Project, or user-supplied list. Additional information could be obtained from the frequency of the variants from the above databases or the predicted deleterious scores created by PolyPhen, CADD, ClinVar or many others. The more infrequent a variant appears in the public database, the more deleterious it is likely to be. Results from different deleterious score prediction tools can combined together by the researcher to make a more accurate call on the variant.
Taken together, these approaches complement one another to filter through over 4 million variants in a human genome. Common, low-deleterious score variants are eliminated to reveal the rare, high-deleterious score variants which could be causal for congenital diseases.
Technical information ANNOVAR is a command-line tool written in the Perl programming language and can be run on any operating system that has a Perl interpreter installed. If used for non-commercial purposes, it is available free as an open-source package that is downloadable through the ANNOVAR website. ANNOVAR can process most next-generation sequencing data which has been run through a variant calling software. +Overview of the main scripts in the programScriptPurposeDescriptionInputOutputRequirementsannotate_variation.plvariant annotatorThe core script, which functionally annotates the genetic variants via (1) gene-based, (2) region-based, and/or (3) filter-based annotation..avinput.avinputData sources are downloaded for annotation, e.g. hg38, UCSC, 1000 Genomes Project.convert2annovar.plfile converterConverts various file formats to the custom ANNOVAR input file format.See "Conversion to the ANNOVAR input file format" section..avinputtable_annovar.plautomated variant annotatorA wrapper around annotate_variation.pl that can take VCF format along with the ANNOVAR format, performs annotation and outputs an Excel-compatible file. Ideal for beginners..avinput, CSV, TSV, VCFCSV, TSV, VCF, TXTData sources are downloaded for annotation, e.g. hg38, UCSC, 1000 Genomes Project.variants_reduction.plvariant reducerPerforms stepwise variant reduction on a large set of input variants to narrow down to a subset of functionally important variants. Filtering procedures include: Applies a stepwise procedure of filtering to identify subsets of variants that are likely to be related to a disease. Such filtering procedures include:
identifying non-synonymous and splicing variants removing variants in segmental duplication regions identifying conserved genomic regions removing variants from 1000 Genomes Project, ESP6500 and dbSNP.avinput.avinputGene-based annotation data sources and various filter-based annotation data sources are downloaded.
File formats The ANNOVAR software accepts text-based input files, including VCF (Variant Call Format), the gold standard for describing genetic loci.
The program's main annotation script, annotate_variation.pl requires a custom input file format, the ANNOVAR input format (.avinput). Common file types can be converted to ANNOVAR input format for annotation using a provided script (see below). It is a simple text file where each line in the file corresponds to a variant and within each line are tab-delimited columns representing the basic genomic coordinate fields (chromosome, start position, end position, reference nucleotides, and observed nucleotides), followed by optional columns
The ANNOVAR file input contains the following basic fields:
Chr Start End Ref Alt
For basic "out-of-the-box" usage:
A popular function of the ANNOVAR tool is the use of the table_annovar.pl script which simplifies the workflow into one single command-line call, given that the data sources for annotation have already been downloaded. File conversion from VCF file is handled within the function call, followed by annotation and output to an Excel-compatible file. The script takes a number of parameters for annotation and outputs a VCF file with the annotations as key-value pairs inside of the INFO column of the VCF file for each genetic variant, e.g. "genomic_function=exonic".
Conversion to the ANNOVAR input file format File conversion to the ANNOVAR input format is possible using the provided file format conversion script convert2annovar.pl. The program accepts common file formats outputted by upstream variant calling tools. Subsequent functional annotation scripts annotate_variation.pl use the ANNOVAR input file. File formats that are accepted by the convert2annovar.pl include the following:
Variant Call Format Samtools genotype-calling pileup format Illumina export format from GenomeStudio SOLiD GFF genotype-calling format Complete Genomics variant format
Generating input files based on specific variants, transcripts, or genomic regions:
When investigating candidate loci that are linked to diseases, using the above variant calling file formats as input to ANNOVAR is a standard workflow for functional annotation of genetic variants outputted from an upstream bioinformatics pipeline. ANNOVAR can also be used to in other scenarios, such as interrogating a set of genetic variants of interest based on a list of dbSNP identifiers as well as variants within specific genomic or exomic regions.
In the case of dbSNP identifiers, providing to the convert2annovar.pl script a list of identifiers (e.g. rs41534544, rs4308095, rs12345678) in a text file along with the reference genome of interest as a parameter, ANNOVAR will output an ANNOVAR input file with the genomic coordinate fields for those variants which can then be used for functional annotation.