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A python package that allows you to easily combine reference genomes and sets of polymorphisms together to create personalized genomes. Personalized genomes can be used to work directly on the genomes of you subjects and be translated into personalized proteomes. Multiple sets of polymorphisms can also be combined together to leverage their independent benefits. Ex: RNA-seq and DNA-seq for the same individual to improve the coverage, RNA-seq of an individual + dbSNP for validation, Combine the results of RNA-seq of several individuals to create a genome only containing the common polymorphisms. pyGeno is also a personal database that give you access to all the information provided by Ensembl (for both reference and personalized genomes) without the need of queries to distant HTTP APIs. It also comes with parsers for several file types and various other useful tools.
PGB / Personal Genome Browser
Provides comprehensive functional annotation and visualization for individual genomes based on the genetic-molecular-phenotypic model. Investigators can easily view individual genetic variants, such as single nucleotide variants (SNVs), INDELs and structural variations (SVs), as well as genomic features and phenotypes associated to the individual genetic variants. The PGB especially highlights potential functional variants using the PGB built-in method or SIFT/PolyPhen2 scores.
Changes the reference human genome (autosomal, sex and mitochondrial chromosomes, build NCBI36/hg18) into an individual genome, taking into account single nucleotide polymorphisms (SNPs), insertions and deletions (indels), copy number variation (CNV) and chromosomal rearrangement. perEditor takes the reference genome in Fasta format and the individual's differences from the reference genome in Variant Call Format (VCF) as inputs. For each difference described in the VCF file, perEditor makes a corresponding change to the reference genome. When the allele information is present in the VCF file, perEditor will keep two genome sequences, representing the two alleles, and make allele-specific changes. After all the data in the VCF file are processed, perEditor outputs the maternal and paternal alleles of the individual genome as Fasta files, ready for mapping ChIP-seq, RNA-seq and other sequence reads.
DNA Compass
Allows exploration and analysis of genomic information. DNA Compass is a feature of DNA Land that enables the navigation of personal genomic information without command-line knowledge. The software can assist individuals who have access to their genomic datasets in searching for a particular single nucleotide polymorphism (SNP) or trait in their raw data. It aims to increase genetic literacy and empower research participants to understand their personal genomic data and advocate for themselves.
A methodology for federated analysis of sequence variants from personal genomes. The key concept in NGS-Logistics is to let users query SNVs across data sets in multiple centers. Users get a full description of the results for the samples to which they have authorized access, while getting relevant summary information for other samples. This summary information is sufficient to carry out key research tasks, such as identifying relevant mutations in a patient population. The footprint on personal genomic data from other patients is kept to a bare minimum.
A simple light-weight distributed annotation system (DAS) tool for visualization of genomic annotation. myKaryoView has been specifically configured to help analyse data derived from personal genomics, although it can also be used as a generic genome browser visualization. Several well-known data sources are provided to facilitate comparison of known genes and normal variation regions. The navigation experience is enhanced by simultaneous rendering of different levels of detail across chromosomes. A simple interface is provided to allow searches for any SNP, gene or chromosomal region.
FGB / Family genome browser
Provides comprehensive analysis and visualization for family genomes. The FGB can visualize family genomes in both individual level and variant level effectively, through integrating genome data with pedigree information. Family genome analysis, including determination of parental origin of the variants, detection of de novo mutations, identification of potential recombination events and identical-by-decent segments, etc., can be performed flexibly.
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