VCF OptionsThis Desction let you select fields from your VCF File(s). Mutation TypesWith this field you can choose beetween mohozygous or heterzygous variants. Homozygous (Ex. 1/1, 1/2, 2/3 and etc) = for recessive models on inheritance Heterozygous (Ex. 0/1, 0/2, 0/2 and etc) = for dominant models on inheritanceUsage: This is usefull if you want you want to search for recessive and dominant models of inheritance.

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ChrWith this field you can choose to see only variants from a single chromossome.Ex. 22-PosThis option let you choose variants in certain regions of a chromossome based in a string.Ex. Chr 1: Pos:0(this will return all variants beetween the positions 0 of Chromossome 1). Filter TypeWith this option you can select variants based on the FILTER column of your VCF.Ex. PASS, LowQual, repeat, SnpClusterUsage: You can select variants that are only PASS in you VCF file(s). dbSNP BuildWith this option you can choose only variants after a certain build of last version of dbSNPEx. = 130 (will get only variants after dbsnp 130)NOTE: dbSNP 129 is generally regarded as the last “clean” dbSNP without “contamination” from 1000 Genomes Project and other large-scale next-generation sequencing projects.

Many published papers utilize dbSNP129 only.Source:. Read DepthThis option should be choosen based on the mean coverage of the individuals (exomes, genomes) that you selected under the previous section “Individuals”Ex. = 30 (This will select only variants with more than 29 reads of coverage and can be used for filtering an exome with 80X of coverage).

QualQUAL phred-scaled quality score for the assertion made in ALT.10log10 prob(call in ALT is wrong). If ALT is ”.” (no variant) then this is -10log10 p(variant), and if ALT is not ”.” this is -10log10 p(no variant). High QUAL scores indicate high confidence calls. Although traditionally people use integer phred scores, this field is permitted to be a floating point to enable higher resolution for low confidence calls if desired. If unknown, the missing value should be specified. (Numeric)This option let you choose beetwen the quality score of the variant based on the value provided by VCF.Ex.

= 50Source: www.1000genomes.org/wiki/Analysis/Variant Call Format/vcf-variant-call-format-version-41. Records per geneThis option let you choose how many different variants per gene you want to see in your resultsEx. Annovar OptionsList of fields that can be filtered in Mendel,MD: all from annovar, snpeff and VEP.Annovar FieldsSource:. Func.refGene.

Gene.refGene. ExonicFunc.refGene. AAChange.refGene. phastConsElements46way.

genomicSuperDups. esp6500siall.

1000g2012aprall. LJB2SIFT. LJB2PolyPhen2HDIV. LJB2PP2HDIVPred. LJB2PolyPhen2HVAR. LJB2PolyPhen2HVARPred. LJB2LRT.

LJB2LRTPred. LJB2MutationTaster. LJB2MutationTasterPred. Mysterious island movie. LJBMutationAssessor. LJBMutationAssessorPred. LJB2FATHMM.

LJB2GERP. LJB2PhyloP. LJB2SiPhy. cosmic65. avsift. PhastConsElements46wayDescription: Conserved elements produced by the phastCons program based on a whole-genome alignment of vertebrates.There is no specific recommended cutoff for highly conserved elements.PhastCons (which has been used in previous Conservation tracks) is a hidden Markov model-based method that estimates the probability that each nucleotide belongs to a conserved element, based on the multiple alignment.

It considers not just each individual alignment column, but also its flanking columns. By contrast, phyloP separately measures conservation at individual columns, ignoring the effects of their neighbors. As a consequence, the phyloP plots have a less smooth appearance than the phastCons plots, with more “texture” at individual sites.

The two methods have different strengths and weaknesses. PhastCons is sensitive to “runs” of conserved sites, and is therefore effective for picking out conserved elements. PhyloP, on the other hand, is more appropriate for evaluating signatures of selection at particular nucleotides or classes of nucleotides (e.g., third codon positions, or first positions of miRNA target sites).Usage: With this option you can select only varinats that are conserved among 46 vertebrate speciesSources. LJB2SIFTDescription:SIFT predicts whether an amino acid substitution affects protein function.

SIFT prediction is based on the degree of conservation of amino acid residues in sequence alignments derived from closely related sequences, collected through PSI-BLAST. SIFT can be applied to naturally occurring nonsynonymous polymorphisms or laboratory-induced missense mutations.Usage:Ex. LJB2PolyPhen2HDIVDescription: Whole-exome PolyPhen scores built on HumanDiv database (for complex phenotypes)PolyPhen-2 (Polymorphism Phenotyping v2) is a tool which predicts possible impact of an amino acid substitution on the structure and function of a human protein using straightforward physical and comparative considerations. Please, use the form below to submit your query.Usage:Source:Adzhubei IA, Schmidt S, Peshkin L, Ramensky VE, Gerasimova A, Bork P, Kondrashov AS, Sunyaev SR. A method and server for predicting damaging missense mutations.

Nature Methods 7: 248–249. VEP OptionsList of fields:. Allele. Gene. Feature.

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Featuretype. Consequence. cDNAposition. CDSposition. Proteinposition.

Aminoacids. Codons.

Existingvariation. DISTANCE. SIFT. PolyPhen. CELLTYPE. CondelAllele - the variant allele used to calculate the consequenceGene - Ensembl stable ID of affected geneFeature - Ensembl stable ID of featureFeaturetype - type of feature. Currently one of Transcript, RegulatoryFeature, MotifFeature.ConsequencecDNApositionCDSpositionProteinpositionAminoacidsCodonsExistingvariationDISTANCECELLTYPE.

SIFTSIFT predicts whether an amino acid substitution is likely to affect protein function based on sequence homology and the physico-chemical similarity between the alternate amino acids. The data we provide for each amino acid substitution is a score and a qualitative prediction (either ‘tolerated’ or ‘deleterious’). The score is the normalized probability that the amino acid change is tolerated so scores nearer 0 are more likely to be deleterious.

The qualitative prediction is derived from this score such that substitutions with a score. PolyPhen-2PolyPhen-2 predicts the effect of an amino acid substitution on the structure and function of a protein using sequence homology, Pfam annotations, 3D structures from PDB where available, and a number of other databases and tools (including DSSP, ncoils etc.). As with SIFT, for each amino acid substitution where we have been able to calculate a prediction, we provide both a qualitative prediction (one of ‘probably damaging’, ‘possibly damaging’, ‘benign’ or ‘unknown’) and a score. The PolyPhen score represents the probability that a substitution is damaging, so values nearer 1 are more confidently predicted to be deleterious (note that this the opposite to SIFT). The qualitative prediction is based on the False Positive Rate of the classifier model used to make the predictions.We ran PolyPhen-2 version 2.2.2 (available here) and again we followed all instructions from the authors, and used the UniProtKB UniRef100 (release 201112) non-redundant protein set as the protein database, which was downloaded, along with PDB structures, and annotations from Pfam and DSSP(snapshot 03-Jan-2012) in February 2012. When computing the predictions we store results for the classifier models trained on the HumDiv and HumVar datasets.

Both result sets are available through the variation API which defaults to HumVar if no selection is made. (Please refer to the PolyPhen website or publications for more details of the classification system). CondelCondel is a general method for calculating a consensus prediction from the output of tools designed to predict the effect of an amino acid substitution. It does so by calculating a weighted average score (WAS) of the scores of each component method. The Condel authors provided us with a version specialised for finding a consensus between SIFT and PolyPhen and we integrated this into a Variation Effect Predictor (VEP) plugin. Tests run by the authors on the HumVar dataset (a test set curated by the PolyPhen team), show that Condel can improve both the sensitivity and specificity of predictions compared to either SIFT or PolyPhen used alone (please contact the authors for details). The Condel score, along with a qualitative prediction (one of ‘neutral’ or ‘deleterious’), are available in the VEP plugin.

The Condel score is the consensus probability that a substitution is deleterious, so values nearer 1 are predicted with greater confidence to affect protein function.Sources.

SNPnexus currently accepts query input data in three different forms (genomic position, chromosomal region or dbSNP id) and two different human genome assemblies. Users can annotate a single SNP, insertion/deletion (InDel) or block substitution by selecting one of the input formats and supplying the required data into the graphical interface.It also allows users to run batch queries by uploading the appropriately formatted input file or pasting the queries into the interface.The formats are explained in more details below. Users can annotate a newly discovered variant by providing the following data into the interface: type (Chromosome/Contig/Clone), name, relative position, reference nucleotide/s (Allele1), observed nucleotide/s (Allele2), positive (1) or negative (-1) strand.One-based coordinate system is used to describe genomic position. Multi-allelic variations are supported where users can provide '/' separated alleles in the Allele2 field. Here are few examples on hg18 assembly:TypeIdPositionAlelle1Allele2StrandChromosomeAT1ContigNT395CG/A/T1CloneAC99AT1Insertions and Deletions (InDels) and Block Substitutions.

The tool has been modified to support insertions or deletions by using - as the placeholder. Users need to insert Allele1=- to indicate Allele2 insertion in the corresponding genomic position.Similarly, Allele2=- can be used to denote deletion of Allele1 from the given genomic position.

Similar to single nucleotide substitution, the tool also supports block substitution when the user provides Allele1 and Allele2 data of same or different length.Here are few examples for insertion and deletion on hg19 assembly:TypeIdPositionAlelle1Allele2Strand#CommentChromosome39798773C-1# 1-nucleotide deletionChromosome39798773CCC-1# 3-nucleotide deletionChromosome39798773-G1# 1-nucleotide insertionChromosome39798773-GTC1# 3-nucleotide insertionChromosome39798773CCCGGT1# block substitutionNote that, the tool supports multiple nucleotides in place of Allele1 and Allele2. However, for practical reasons, users are not encouraged toprovide very large blocks that can possibly positioned over more than one adjacent functional regions, i.e., adjacent intronic and exonic region, in which case the predicted functionality of the SNP provided by our tool will be based on the first functional region.IUPAC code submission. Finally, users can annotate reference and observed nucleotides complying with IUPAC nucleotide nomenclature to denote ambiguous nucleotides in certain position following the translation table shown below:IUPAC CodeMeaningGGAATTCCRG or AYT or CMA or CKG or TSG or CWA or THA or C or TBG or T or CVG or C or ADG or A or TNG or A or T or CHere are few examples:TypeIdPositionAlelle1Allele2Strand#CommentChromosomeAS1# G or C substitution with AChromosome39798773-R1# G or A insertion. SNPnexus allows users to submit batch query when dealing with large numbers of variations. Users can either paste the variants list directly into the designed text space or upload a file containing the queries.Currently we limit the maximum number of variants in a single batch query to 100,000.We only allow batch query using genomic position and/or dbsnp rs# formats.

No chromosomal region query data is allowed.Each variant must be on a new line with tab-delimited data in one of the following formats:# Genomic position data for novel SNPs# dbSNP rs number for known SNPsExample of a batch query is shown below, which one can paste directly into the textarea provided in the interface:ChromosomeAT1ContigNT395AT1CloneAC99AT1dbsnprs293794dbsnprs1052133Alternatively, users can upload batch query files (.txt) like this. Note that, known SNPs must be preceded by keyword 'dbsnp' to be recognized as dbSNP rs#. The result table containing gene/protein consequences on a particular gene annotation system may have following columns:SNP: or Allele: Examined alleles. For Insertion, reference allele is '-'. For other cases, reference allele is the allele found in reference genome sequence.Observed allele(s) can be multi-allelic separated by ' ' depending on the input Allele2. If input Allele1 does not match with reference allele, then Allele1 becomes the first observed allele.Strand: On which strand the variant is observed (1 or -1)Symbol: Gene symbolGene: Gene name in the corresponding annotation systemTranscript: Transcript name in the corresponding annotation systemEntrez gene: Entrez gene idPredicted function: Predicted function of the SNP/InDel/block substitution based on its location on the transcript.

The result is based on the first nucleotide position of the variation.Possible categories: coding, intronic, intronic (splicesite), 5utr, 3utr, 5upstream, 3downstream, non-coding, non-coding intronic, non-coding intronic (splicesite). More detailed information on the predicted function is available on the 'Note' column.cdnapos: SNP position on cdna, if the predicted function is coding, 3'UTR or 5'UTRcdspos: SNP position on cds, if the predicted function is codingaapos: Position of the first amino acid (possibly) effected in the resultant peptide chain, if the predicted function is codingaachange: Peptide ', observed amino acid(s)1 ,' ', observed amino acid(s)2. Detail (previously Note column): Detailed functional type for the variation.

The SIFT result table containing the predicted effect on protein has following columns:SNP: SNP nameAllele: Transcript: Transcript name in the Ensembl gene annotation systemProtein: Protein name in the Ensembl gene annotation systemaapos: Position of the amino acid affected in the resultant peptide chainwildaa: Reference amino acidmutantaa: Observed amino acidScore: SIFT prediction score for non-synonymous substitution of reference amino acid with observed amino acid. Possible real values: 0 to 1.Prediction: SIFT predicted effect on protein based on the score. Possible values: DAMAGING (score 0.5)Confidence: Degree of reliability about the prediction. Possible values: HIGH, LOWThe PolyPhen result table containing the predicted effect on protein has following columns:SNP: SNP nameAllele: Transcript: Transcript name in the Ensembl gene annotation systemProtein: Protein name in the Ensembl gene annotation systemaapos: Position of the amino acid affected in the resultant peptide chainwildaa: Reference amino acidmutantaa: Observed amino acidScore: PolyPhen prediction score for non-synonymous substitution of reference amino acid with observed amino acid. Possible real values: 0 to 1.Prediction: PolyPhen predicted effect on protein based on the score.

Possible values: PROBABLY DAMAGING, POSSIBLY DAMAGING, BENIGN, UNKNOWN. The Transcription Factor Binding Sites (TFBS) result table has following columns:SNP: SNP nameTFBSid: TFBS idChromosome: Chromosome namechromStart: Start position of the TFBS site in the chromosomechromEnd: End position of the TFBS site in the chromosomeTFBSAccession: TFBS accession number.

Note that, browsing the link provided in the html and excel file requires free registration with website.TFBSSpecies: Transcription factor speciesTFBSname: Transcription factor nameSwissProtAccession: SwissProt accession numberThe First exon and promoter prediction result table has following columns:SNP: SNP nameChromosome: Chromosome namechromStart: Start position of the prediction in the chromosomechromEnd: End position of the prediction in the chromosomeFirstEFName: Name of the item containing the type of prediction (exon, promoter, CpG window)Probability: Prediction score. Possible values: 0 to 1000Strand: + or -The miRBASE result table has following columns:SNP: SNP nameChromosome: Chromosome namechromStart: Start position of the microRNA in the chromosomechromEnd: End position of the microRNA in the chromosomeName: microRNA nameAccession: miRBASE accession numberStrand: + or -Type / Description: miRNA type. Possible values: mature miRNA, miRNAprimarytranscriptThe Vista Enhancer prediction result table has following columns:SNP: SNP nameChromosome: Chromosome namechromStart: Start position of the Vista element in the chromosomechromEnd: End position of the Vista element in the chromosomeVistaItem: Name of the Vista elementScore: Prediction score. The Vertebrate Alignment and Conservation result table contains the following columns:SNP: SNP nameChromosome: Chromosome namechromStart: Start position of the aligned element in the chromosomechromEnd: End position of the aligned element in the chromosomeId: Name of the aligned elementProbability Score: Estimated probability score for conservation as determined from PHAST package.

Possible values: 0 to 1000The Genomic Evolutionary Rate Profiling (GERP) result table contains the following information:SNP: SNP nameChromosome: Chromosome namechromStart: Start position of the aligned element in the chromosomechromEnd: End position of the aligned element in the chromosomeRSScore: Rejected Substitutions score for the conserved element as determined from GERP package. The Genetic Association Database (GAD) result table contains the following columns:SNP: SNP nameGAD Id: GAD idAssociation: Confirmed associationPhenotype: Phenotype descriptionDiseaseClass: Type of diseaseGene: Gene nameReference: Reference of publication of the studyPubmed: Pubmed id of publication of the studySNP reported: Whether the known SNP is directly reported in the study. The CADD result table contains the following columns:SNP: SNP nameID: Query SNP presented in genomic position formatChromosome: Chromosome namePosition: Variant start position in the chromosomeVariant: as reported in the tool's genome-wide scoreRaw Score: 'Raw' unaltered CADD-score for the variation.

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It has relative meaning, with higher values indicating that a variant is more likely to be simulated (or 'not observed') and therefore more likely to have deleterious effects.PHRED: PHRED-like (-10.log 10(rank/total)) scaled CADD-score ranking a variant relative to all possible substitutions of the human genome. A score≥10 indicates that it is predicted to be in the 10% most deleterious substitutions that you can do to the human genome, a score≥20 indicates the 1% most deleterious and so on.The FitCons result table contains the following columns:SNP: SNP nameID: Query SNP presented in genomic position formatChromosome: Chromosome nameRegion Start: Start position of the non-coding regionRegion End: End position of the non-coding regionFitness Score: In the range 0-1.