Optimal informatics solutions engineered for common genome analysis problems. Call Somatic Mutations or Germline Variants. Process Whole Genomes, Exomes, Transcriptomes, and Methylomes, The best bioinformatics, the most reliable results, the lowest total cost.
Secure stance, scalable deployment. Priced by input data volume in the cloud. Also available for unlimited samples and data by license.
Unrivaled sensitivity and precision for research and clinical applications. Individual genomes, exomes or transcriptomes, Trios, Families, Tumor-Normal data, Large cohorts and multi-sample projects.
Engineered Solutions – securely deployed in the cloud
1) Germline Variants - Exomes and Whole Genomes Upload FASTQ or BAM files, Pipeline runs multiple variant calling algorithms using Human genome build 38 as reference. All call sets are integrated with BAYSIC. Output includes SNVs and Indels detected by each caller, and an integrated BAYSIC vcf. BAYSIC is a Bayesian method to integrate call sets for increased precision and sensitivity, and every BAYSIC call is assigned a posterior probability. The user may filter the BAYSIC vcf by posterior probability threshold to select a call set that maximizes precision or sensitivity, and default parameters (pp=0.8) produce a call set that minimizes both false positives and false negatives.
Multiple variant calling methods produce vcfs (e.g., Freebayes, Samtools, Platypus and GATK). All vcfs are integrated using BAYSIC to produce a single call set where every call has a posterior probability. The user may select a posterior probability threshold to filter the BAYSIC vcf according to the user’s tolerance for false positives and false negatives, emphasizing precision or sensitivity. Default parameters of BAYSIC (pp=0.8) produce a call set with few false alarms and few misses. If read quality and length are sufficient, an additional option allows assessement of Copy Number Variants and Structural Variants.
2) Somatic Mutations - Exomes and Whole Genomes Upload FASTQ or BAMs from tumor and normal tissue sequencing, This pipeline first runs multiple somatic mutation detection algorithms. All call sets from multiple somatic mutation detection methods are integrated with BAYSIC producing a single BAYSIC vcf. BAYSIC dramatically improves the accuracy of somatic mutation calls, assigning a posterior probability to every call, and allowing the user to select a call set that optimizes specificity or sensitivity according to user’s tolerance for false alarms and misses. superior to standard single algorithm and discordant calls and improves the overall precision and sensitivity of somatic mutation detection.
Whole genome pipeline for somatic mutations (Tumor-Normal data). Multiple somatic mutation detection algorithms (e.g.,VarScan2, Shimmer, Strelka, Virmid) produce somatic call sets (vcfs). All somatic call sets are integrated with BAYSIC. BAYSIC dramatically improves the precision and specificity of somatic mutation calls without sacrificing sensitivity. Output includes SNVs and Indels detected by each somatic caller, and an integrated BAYSIC vcf that assigns a posterior probability to each somatic call, allowing the user to filter the BAYSIC call set to maximize specificity or sensitivity according to the user’s tolerance for false positive and false negative somatic calls. Default parameters (pp = 0.8) optimize precision and sensitivity jointly. Additional options include Copy Number Variation (CNVs) and Structural Variation (SVs) assessment if input data has sufficient read length and sequence quality.
Integrate the vcf from multiple callers into a BAYSIC vcf for enhanced detection accuracy. BAYSIC will help you minimize false positive and false negative calls, and works for both germline variants and somatic mutations. Maximally accurate variant detection using BAYSIC – greater precision, enhanced sensitivity, fewer errors. More reliable variant calls, more confident genotype assignment.
BAYSIC dramatically improves the accuracy of somatic mutation detection and germline variant calls. BAYSIC combines the vcfs produced by multiple algorithms using an unsupervised and fully Bayesian machine-learning method. Somatic callers include VarScan2, Shimmer, Virmid and Strelka. Germline callers include Samtools, Freebayes, GATK and Platypus. BAYSIC assigns a posterior probability to every call, allowing the user to filter by the posterior probability threshold and select a call set that optimizes specificity or sensitivity according to user’s tolerance for false alarms (false positives) and missed (false negative) calls. Output includes SNVs and Indels detected by each caller, and an integrated BAYSIC vcf that can be used to resolve discordant calls and improve the overall precision and sensitivity of somatic mutations and germline variants.
Explore your genome with Genome Cruiser - filter, sort, annotate and interpret probable effects of variants or somatic mutations. Use genome cruiser to help assess possible functional impacts of detected variants. Focus on variants or somatic mutations associated with traits of interest. Use leading public databases and customized data compilations to interpret the functional significance and potential consequences of detected variants or mutations. Cruise genomic test results to assess potential implications or predicted impacts of detected variants.
Rank variants by probable effect. Match somatic mutations to drug response forecasts or pertinent clinical indications or outcomes catalogued in leading databases. Assess potential therapeutic options given mutational status. Find clinical trials relevant to condition, diagnosis and detected mutations. Genome Cruiser mines leading databases, including ClinVar, SNPeffect, COSMIC, CIVic, DGI, ClinicalTrials.gov, DrugBank, 1000genomes, ESP, GWAScatalog and more
CLIA certified whole genome and exome sequencing. Submit tissue, DNA or RNA. Whole genome or exome CLIA lab sample testing. Get FASTQ, BAM and BAYSIC vcf files. Use Genome Cruiser to explore your sequence data.
Custom microbiome and metagenomic sequencing and analysis solutions. We provide turnkey solutions for microbiome and metagenomics and customize the workflow according to user needs and objectives. A typical16S RNA analysis pipeline includes initial sequence data QC, including quality trimming and minimum read length filtering. Data is then aligned to 16S reference DB, followed by taxonomic assignment, statistical analysis and OTU clustering. Subsequently, alpha diversity, beta diversity, principal component analysis and Rarefaction analysis output are reported. Additional 16S analysis options are available.