Powered by Big Data
Phase Genomics’ proprietary cloud-based bioinformatic platforms employ novel computational approaches and algorithms to analyze and integrate proximity ligation data. This provides you with the ultra-long-range and quantitative information needed to unlock an added dimension in your cytogenomic, metagenomic, and epigenomic research.
Learn more about using our proximity ligation kits and our computational tools for applications in:
Vist our GitHub page for additional information about some of the computational tools described below.
Unlike whole-genome sequencing (WGS) binning methods, which rely on statistical assumptions about parameters such as k-mer frequency and coverage, Hi-C data enables metagenomic deconvolution based on true biological measurements. Unlike 16S-based analysis, Hi-C data does not rely on any a priori information to make sense of metagenomic communities, and produces proximity-assembled genomes (PAGs) for eukaryotes, prokaryotes, and archaea. Because Hi-C (proximity ligation) provides direct measurements of DNA sequences present in the same cell in vivo, the ProxiMeta Platform also enables host attribution for mobile elements, such as plasmids, phages and antibiotic resistance genes (ARGs). The platform is designed to give you more than just a taxonomic list of what is in your sample or a collection of genome FASTAs; it includes reports that provides more context, allows for genome annotation, genome comparisons, and integration with several other industry-leading deconvolution tools.
ProxiMeta Features and Benefits:
Outputs
Proximo assigns contigs to scaffolds, arranges contigs into a linear ordering, and then orients contigs in such a way as to maximize the likelihood of having generated the observed Hi-C data. This core scaffolding algorithm is combined with a scaffold optimization process that performs tens or even hundreds of thousands of scaffolding attempts in order to find the scaffold solution most concordant with the data. Proximo is also the only Hi-C scaffolding algorithm capable of directly consuming linkage maps or reference genomes, providing the ability to use more of your data as input to generate the best possible scaffolds.
Proximo Features and Benefits:
Contact us to design or get started with a Proximo Genome Scaffolding project.
Proximo Analysis WorkflowInputs
Outputs
Combine Hi-C data with long reads to create two true phased sets of contigs for diploid organisms. Use FALCON-Phase in combination with Proximo to produce complete, fully phased, diploid scaffolds.
Sister chromatids are independent DNA molecules in the nucleus, and as such they form independent Hi-C profiles that can be used to identify which heterozygous sequences originated on the same molecule. FALCON-Phase examines contigs and haplotigs (e.g., the results of FALCON-Unzip or purge_haplotigs) in the context of Hi-C data, using a graph partitioning algorithm that detects likely phase switch errors and corrects them. This results in >96% contig phasing accuracy in known-truth, pedigree-based benchmarks. FALCON-Phase can also be used in conjunction with Proximo to extend phase blocks to the chromosome-scale, delivering two complete, true-phased sets of chromosomes for diploid organisms: the paternal genome and the maternal genome both, from a single analysis.
FALCON-Phase Features and Benefits:
Learn about FALCON-Phase, and how it was used to combine PacBio long-read and Hi-C data to produce the most contiguous diploid human genome assembly.
How do I access FALCON-Phase?
FALCON-Phase Analysis WorkflowInputs
Outputs