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Solvuu

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New York, New York, US

About Solvuu

Solvuu is a technology company. We provide a cloud-based data management platform with standardized access to data, tools, and visualization across biological data formats. We have defined a system rich enough to harmonize all the myriad data formats used in life sciences, specifically bioinformatics, thereby... Show more »

Solvuu is a technology company. We provide a cloud-based data management platform with standardized access to data, tools, and visualization across biological data formats. We have defined a system rich enough to harmonize all the myriad data formats used in life sciences, specifically bioinformatics, thereby liberating scientists to focus on science. Importantly, the technology abstracts away the format of the data, and allows users to treat the data semantically.

Instead of having to learn and utilize numerous tools, each of which works on just one data format, with Solvuu, you can convert, search, analyze and visualize over all data formats through a single interface (Solvuu’s web UI, or command-line-interface).

We provide extensive support for analyzing data, using a broad spectrum of utilities: bioinformatics tools connected into pipelines, SQL style queries, and statistical functions, along with rich, interactive visualization. Collaboration is a key feature of our platform where data can be shared easily and securely.

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Our Services (9)


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Microbial Genome Mapping

Price on request

The development of NGS technologies for assaying microbial genetic material in an environment has become a powerful new approach for rapidly characterizing microbial communities, given a significant percentage of the microbes are uncultivable.

These experimental approaches along with novel computational methods, are enabling us... Show more »

The development of NGS technologies for assaying microbial genetic material in an environment has become a powerful new approach for rapidly characterizing microbial communities, given a significant percentage of the microbes are uncultivable.

These experimental approaches along with novel computational methods, are enabling us to understand the role of microbial shifts in human health and disease, track and monitor contamination of food sources, understand disease susceptibility in plants of agricultural importance, rapidly respond to infectious disease outbreaks, characterize diversity, biogeographic variability for environmental impact assessment and ecological remediation, etc. The Human Microbiome Project and the Earth Microbiome Project have only attested to the growing importance and relevance of microbiome research.

We support data analytics for (i) Meta-taxonomic approaches that profile a community by amplicon sequencing of marker genes (16S rRNA, 18S rRNA, ITS etc), (ii) Direct metagenomic taxonomic classification approaches for quantitative community profiling and identification of organisms with close relatives in the database, (iii) Characterization of uncultivated microbes towards a more qualitative understanding of metabolic capability through assembly and binning of the reads followed by analysis of the binned draft genomes to obtain a comprehensive catalog of genes and functions in all organisms, (iv) Profiling RNAs from a complex microbial environment through meta-transcriptomics, etc.

Whether you are working on a pipeline of therapeutics for various disease indications, characterizing a microbial collection for seed treatment or novel products to kill insects or fungal pathogens, or improving pathogen detection and traceback for infectious disease surveillance, we can help translate your microbiome research into practical applications.

Our integrated data solutions lets you manage and explore your processed data derived from analytical pipelines. Simply upload your BIOM file with taxonomic profiles from 16S or metagenome analysis tools and pipelines, search over your BIOM files, explore and visualize the data.

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Transcriptomics Data Analysis

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RNA-seq with next-generation sequencing (NGS) has become the method of choice for researchers interested in characterizing genome-wide gene and transcript expression in a single experiment.

RNA-seq is widely used for profiling expression of protein-coding and non-coding transcripts (small and long) in both model species (human,... Show more »

RNA-seq with next-generation sequencing (NGS) has become the method of choice for researchers interested in characterizing genome-wide gene and transcript expression in a single experiment.

RNA-seq is widely used for profiling expression of protein-coding and non-coding transcripts (small and long) in both model species (human, mouse, Arabidopsis, maize, etc.) with well-defined transcriptome, and species with no reference transcriptome. RNA-Seq methods can provide precise measurement of gene and transcript levels, determine strand orientation, map alternate transcripts with high confidence, characterize gene fusions, identify single nucleotide variants and help discover novel gene isoforms.

RNA-seq has been utilized for diverse application areas in biology. For example, in pathobiology of cancer to dissect the link between tumor genotypes and molecular subtypes of cancer, to aid in tumor classification and progression, and to characterize multiple drug susceptible tumorigenic pathways towards discovering new biomarkers or therapeutic strategies. In agriculture, RNA-seq methods have been used to assess transcript diversity across different varieties, characterize mode of action of trait genes, and discover new genes or targets for crop/trait improvement (yield and other agronomic traits, disease resistance, insect tolerance, quality traits, etc).

Tertiary analysis of expression datasets is necessary to understand affected genes and pathways and this is typically accomplished through differential expression analysis, enrichment analysis, and co-expression based network analysis, to create a global picture of cellular function.

Our integrated data solutions lets you manage and explore your primary expression data, as well as outputs from tertiary analysis tools. Explore data outputs from transcriptome characterization tools by simply uploading your expression matrix or results from differential expression analysis. Search over your data, subset your data, perform statistical analysis and visualize the data.

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MeDIP-Sequencing (DNA Methylation)

Price on request

Eukaryotic gene regulatory mechanisms that induce or repress the expression of a gene include structural and chemical changes to the chromatin and the DNA, binding of proteins to specific DNA elements, or mechanisms that modulate translation of mRNA.

Epigenetic mechanisms regulate many important biological processes during normal... Show more »

Eukaryotic gene regulatory mechanisms that induce or repress the expression of a gene include structural and chemical changes to the chromatin and the DNA, binding of proteins to specific DNA elements, or mechanisms that modulate translation of mRNA.

Epigenetic mechanisms regulate many important biological processes during normal growth and development, and these mechanisms are deregulated in diseases such as cancer and diabetes.

Several techniques for characterizing the numerous regulatory and epigenomic modifications have been coupled with massively parallel sequencing strategies (NGS methods) to understand gene regulation. These include methods for characterizing interactions between protein, DNA, and RNA to survey transcription factor binding sites and histone modifications (ChIP-Seq), understand DNA methylation (Whole-Genome Bisulfite Sequencing (WGBS), Reduced Representation Bisulfite Sequencing (RRBS), Methylated DNA Immunoprecipitation Sequencing (MeDIP-Seq), understand DNA accessibility changes within the chromatin (ATAC-seq, FAIRE-seq, DNase-seq), chromatin conformation capture methods (3C, 4C, 5C, Hi-C), nucleosome occupancy and positioning (MNase-Seq, CC-Seq and ChIP-Seq), etc.

Explore and integrate results from your favorite peak callers by simply uploading your peaks, filter and annotate peaks, search over and subset your data, perform statistical analyses and visualize the data.

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Reduced Representation Bisulfite Sequencing (RRBS)

Price on request

Eukaryotic gene regulatory mechanisms that induce or repress the expression of a gene include structural and chemical changes to the chromatin and the DNA, binding of proteins to specific DNA elements, or mechanisms that modulate translation of mRNA.

Epigenetic mechanisms regulate many important biological processes during normal... Show more »

Eukaryotic gene regulatory mechanisms that induce or repress the expression of a gene include structural and chemical changes to the chromatin and the DNA, binding of proteins to specific DNA elements, or mechanisms that modulate translation of mRNA.

Epigenetic mechanisms regulate many important biological processes during normal growth and development, and these mechanisms are deregulated in diseases such as cancer and diabetes.

Several techniques for characterizing the numerous regulatory and epigenomic modifications have been coupled with massively parallel sequencing strategies (NGS methods) to understand gene regulation. These include methods for characterizing interactions between protein, DNA, and RNA to survey transcription factor binding sites and histone modifications (ChIP-Seq), understand DNA methylation (Whole-Genome Bisulfite Sequencing (WGBS), Reduced Representation Bisulfite Sequencing (RRBS), Methylated DNA Immunoprecipitation Sequencing (MeDIP-Seq), understand DNA accessibility changes within the chromatin (ATAC-seq, FAIRE-seq, DNase-seq), chromatin conformation capture methods (3C, 4C, 5C, Hi-C), nucleosome occupancy and positioning (MNase-Seq, CC-Seq and ChIP-Seq), etc.

Explore and integrate results from your favorite peak callers by simply uploading your peaks, filter and annotate peaks, search over and subset your data, perform statistical analyses and visualize the data.

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Whole Genome Bisulfite Sequencing

Price on request

Eukaryotic gene regulatory mechanisms that induce or repress the expression of a gene include structural and chemical changes to the chromatin and the DNA, binding of proteins to specific DNA elements, or mechanisms that modulate translation of mRNA.

Epigenetic mechanisms regulate many important biological processes during normal... Show more »

Eukaryotic gene regulatory mechanisms that induce or repress the expression of a gene include structural and chemical changes to the chromatin and the DNA, binding of proteins to specific DNA elements, or mechanisms that modulate translation of mRNA.

Epigenetic mechanisms regulate many important biological processes during normal growth and development, and these mechanisms are deregulated in diseases such as cancer and diabetes.

Several techniques for characterizing the numerous regulatory and epigenomic modifications have been coupled with massively parallel sequencing strategies (NGS methods) to understand gene regulation. These include methods for characterizing interactions between protein, DNA, and RNA to survey transcription factor binding sites and histone modifications (ChIP-Seq), understand DNA methylation (Whole-Genome Bisulfite Sequencing (WGBS), Reduced Representation Bisulfite Sequencing (RRBS), Methylated DNA Immunoprecipitation Sequencing (MeDIP-Seq), understand DNA accessibility changes within the chromatin (ATAC-seq, FAIRE-seq, DNase-seq), chromatin conformation capture methods (3C, 4C, 5C, Hi-C), nucleosome occupancy and positioning (MNase-Seq, CC-Seq and ChIP-Seq), etc.

Explore and integrate results from your favorite peak callers by simply uploading your peaks, filter and annotate peaks, search over and subset your data, perform statistical analyses and visualize the data.

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ChIP-Seq

Chromatin Immunoprecipitation Sequencing
Price on request

Eukaryotic gene regulatory mechanisms that induce or repress the expression of a gene include structural and chemical changes to the chromatin and the DNA, binding of proteins to specific DNA elements, or mechanisms that modulate translation of mRNA.

Epigenetic mechanisms regulate many important biological processes during normal... Show more »

Eukaryotic gene regulatory mechanisms that induce or repress the expression of a gene include structural and chemical changes to the chromatin and the DNA, binding of proteins to specific DNA elements, or mechanisms that modulate translation of mRNA.

Epigenetic mechanisms regulate many important biological processes during normal growth and development, and these mechanisms are deregulated in diseases such as cancer and diabetes.

Several techniques for characterizing the numerous regulatory and epigenomic modifications have been coupled with massively parallel sequencing strategies (NGS methods) to understand gene regulation. These include methods for characterizing interactions between protein, DNA, and RNA to survey transcription factor binding sites and histone modifications (ChIP-Seq), understand DNA methylation (Whole-Genome Bisulfite Sequencing (WGBS), Reduced Representation Bisulfite Sequencing (RRBS), Methylated DNA Immunoprecipitation Sequencing (MeDIP-Seq), understand DNA accessibility changes within the chromatin (ATAC-seq, FAIRE-seq, DNase-seq), chromatin conformation capture methods (3C, 4C, 5C, Hi-C), nucleosome occupancy and positioning (MNase-Seq, CC-Seq and ChIP-Seq), etc.

Explore and integrate results from your favorite peak callers by simply uploading your peaks, filter and annotate peaks, search over and subset your data, perform statistical analyses and visualize the data.

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Genetic Variant Analysis

Price on request

With rapidly falling sequencing costs, whole-exome sequencing (WES) and whole-genome sequencing (WGS) using NGS technologies have become de facto standards to characterize individual genomic landscapes to identify causal genomic variants relevant for understanding disease mechanisms, diagnosis and therapy.

Understand the role of... Show more »

With rapidly falling sequencing costs, whole-exome sequencing (WES) and whole-genome sequencing (WGS) using NGS technologies have become de facto standards to characterize individual genomic landscapes to identify causal genomic variants relevant for understanding disease mechanisms, diagnosis and therapy.

Understand the role of genetic variation in human disease, ancestry, and evolution using community standard GATK-based best practices workflows, or your aligner and variant caller of choice for analyzing Whole Exome Sequencing (WES) and Whole Genome Sequencing (WGS) data. Our intelligent execution engine can handle any number of samples, as it automatically parallelizes jobs and minimizes IO. Our workflows can capture both large and small variants, indels, copy number changes, and large structural variants and help you identify potential causative variants for further analysis.

Use popular tools like ANNOVAR, VEP, VarAFT, SnpEff, etc for variant annotation. Upload your VCF files, annotate and filter your variants with gene and transcript features, functional information, allele frequency, evolutionary features, etc. Integrate your results with curated resources like Online Mendelian Inheritance in Man (OMIM), Human Phenotype Ontology (HPO), catalog of cancer-specific databases like COSMIC, CIViC, ClinVar, cBioPortal, NCI Genomic Data Commons, etc.

Overlay filtered variants with other omics datasets, namely, expression (coding and non-coding genes), epigenomics (methylation, histone modifications), chromatin accessibility, etc and visualize using our genome browser.

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Single Cell Gene Expression Analysis

Price on request

High-throughput “bulk”-omics techniques have advanced our understanding of the molecular states of biological systems. However, they can only capture ensemble averages of cell states and are poorly suited to understand cell types, states, transitions, and locations. Massively parallel single cell genomics assays that can profile... Show more »

High-throughput “bulk”-omics techniques have advanced our understanding of the molecular states of biological systems. However, they can only capture ensemble averages of cell states and are poorly suited to understand cell types, states, transitions, and locations. Massively parallel single cell genomics assays that can profile hundreds of thousands of individual cells is rapidly emerging as a revolutionary technology.

Single-cell genomics methods have the potential to transform many areas of biological research such as physiology, developmental biology, and anatomy – in health and disease. The Human Cell Atlas Project, an international collaborative effort, aims to create a comprehensive reference map of the types and properties of all human cells.

Recently, a number of next-generation sequencing-based assays have been optimized to work at the level of individual cells. While the most widely used of these single-cell techniques is RNA-seq, other techniques that have been adapted for single-cell measurements from “bulk” cell assays include whole-genome bisulfite sequencing, DNase I hypersensitivity sequencing, and ATAC-seq to assay accessible DNA elements. These techniques allow researchers to characterize the genetic and functional properties of individual cells in their native conditions.

Analyzing single-cell RNA-seq data is substantially more difficult than analyzing data from typical RNA-seq experiments. Typical single-cell studies capture hundreds or even thousands of cells, and generate very large data sets. The size and scale of the data can considerably affect performance of most algorithms. Solvuu’s intelligent execution engine is fully scalable, automatically parallelizes jobs, and can implement workflows using open-source tools.

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Sequencing Data Analysis and Management

Price on request

Sequencing Data Analysis Services

Sequencing Data Analysis Services

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Raj Sasidharan

Director of Genomics

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