Nucleome Informatics is a specialised bioinformatics solution service provider based at Hyderabad the IT hub of India.Team Nucleome. has successfully completed genome, transcriptome, metagenome and epigenome data analysis projects. Using a team of experienced bioinformatics analysts, and biologists, TEAM NUCLEOME provides a range of genomic data assembly and analysis services using state-of-the-art software pipelines and high computational infrastructure supported by Dell. Our analysis services can be used alone or in combination with our laboratory services to provide comprehensive data generation and analysis for your project.
Bio IT
Overview
Our Product
Big Data Decoders are proven compatible with leading open source and commercial bioinformatics applications of Nucleome Informatics, Ion Torrent®, Illumina®, PacBio RSII® and Life Technologies® along with other NGS applications.
DrSeq: User-friendly Interface for RNA-Seq data analysis
You can never be satisfied with the analysis done by others on your RNA seq datasets as you know the questions and how to seek possible answers but learning bioinformatics is time taking, and you may lose focus from your expertise. Nucleome presents DrSeq analysis pipeline which can be run by anyone anytime. RNA sequencing data analysis was never so easy and efficient. It’s as simple as filling up online forms. Analyse RNA sequencing data with or without reference genome in 4 easy steps.
Bioinformatics Services
Nucleome Informatics is a specialised bioinformatics solution service provider based at Hyderabad the IT hub of India.TEAM NUCLEOME. has successfully completed genome, transcriptome, metagenome and epigenome data analysis projects. Using a team of experiencedbioinformatics analysts, and biologists, TEAM NUCLEOME provides a range of genomic data assembly and analysis services using state-of-the-art software pipelines and High computational infrastructure supported by Dell. Our analysis services can be used alone or in combination with our laboratory services to provide comprehensive data generation and analysis for your project. Each analysis project is performed in close consultation with the researcher to ensure that the analysis targets the scientific question at hand. Analysis results are delivered via ftp, hard media, or NCBI deposit. Services are provided on a fee-for-service basis and each project is customized to the needs of the investigator.
Metagenomic Sequence Assembly
The field of metagenomics is concerned with the analysis of communities by sampling the DNA of all species in a given microbial community. The assembly of metagenomes poses greater and more complex challenges than single-genome assembly as the relative abundances of the species in a microbiome are not uniform. Voluminous parallel sequencing datasets, especially metagenomic experiments, require distributed computing for de novo assembly and taxonomic profiling.
Using a range of sequence assembly tools tuned to the appropriate genome size and characteristics, we produce an optimized assembly and deliver contigs, scaffolds, and metrics in a variety of standard formats.
De novo and Comparative Genome Assembly
In sequence assembly, two different types can be distinguished:
1. de-novo: assembling short reads to create full-length (sometimes novel) sequences
2. mapping: assembling reads against an existing backbone sequence,
building a sequence that is similar but not necessarily identical to the backbone sequence In terms of complexity and time requirements, de-novo assemblies are orders of magnitude slower and more memory intensive than mapping assemblies. This is mostly due to the fact that the assembly algorithm needs to compare every read with every other read. Referring to the comparison drawn to shredded books: while for mapping assemblies one would have a very similar book as template (perhaps with the names of the main characters and a few locations changed), the de-novo assemblies are more hard-core in a sense as one would not know beforehand whether this would become a science book, a novel, a catalogue, or even several books. Also, every shred would be compared with every other shred. Given a reference sequence, data is aligned and assembled against the reference. Resulting contigs, scaffolds, and variant records are delivered.
Genome Finishing
The next step in the large-scale sequencing process is often referred to as ``finishing.`` In this step, contiguous segments of sequence are ordered and linked to one another and any ambiguities or discrepancies among the individual reads are resolved. Once this is concluded, a relatively rigorous quality check and verification is performed. At this stage any suspicious assemblies are analysed and either verified or disassembled
Epigenomic Analysis (ChIP-Seq and BS-Seq)
Data from ChIP-Seq experiments are aligned to a reference genome and analysed for peak enrichment to identify DNA-protein binding sites. Differential peak analysis between experiments can be used to identify binding sites specific to certain conditions or proteins. DNA methylation patterns are detected by aligning sequence data derived from bisulfite-treated DNA (BS-Seq) to both a reference genome and a version of the reference genome that has been in silico bisulfite converted. This dual alignment analysis enables more accurate identification of methylated sites and their boundaries.
Genome Annotation
Genome annotation is the process of attaching biological information to sequences. It consists of three main steps:
1. Identifying portions of the genome that do not code for proteins
2. Identifying elements on the genome, a process called gene prediction, and attaching biological information to these elements Structural annotation consists of the identification of genomic elements.
1. ORFs and their localisation 2. gene structure 3. coding regions 4. location of regulatory motifs
Functional annotation consists of attaching biological information to genomic elements.
1. biochemical function 2. biological function 3. involved regulation and interactions 4. expression
We provide both automated and manual annotation of prokaryotic and eukaryotic genome sequences.
Transcriptome Analysis
criptome (RNA-Seq) data can be analysed to determine gene or isoform level expression profiles, sequence variation, and differential expression between multiple conditions and/or time points.De novo transcriptome assembly is the method of creating a transcriptome without the aid of a reference genome. Reference based transcriptome analysis can also be done for samples with available annotated genome sequence in public domain. We offer following RNA seq analysis services:
1. Alignment to a reference genome and detection of expressed sequences.
2. Identification and quantitation of exons and genes, splice junctions, single nucleotide variants, small indels, and novel transcripts.
3. Annotated and uniform output including links to databases to make it easier to browse information on specific genes of interest and
4. Study-level analysis for discovery of significant differential expression patterns and associations with molecular pathways.
SNP, Indel, and Structural Variant Detection
Using analysis pipelines developed specifically for variant detection, sequence data is aligned to available reference sequences. SNPs, indels (insertions and deletions), and structural variants are detected, quality-filtered, and annotated (coding, non-coding, synonymous, non-synonymous, etc.). In order to identify novel or rare variants, the variants are compared to a public database of known variants that includes the latest dbSNP and 1000Genomes data as well as other known variants from multiple organisms. Data visualization tools are available to browse the results. Comparative analysis of variants calls is also available.
Pathway & Network Analysis
Given a set of variant positions, genes, or other loci associated with a particular phenotype, we use software packages, including Ingenuity Pathway Analysis (IPA), developed specifically to analyse gene pathways and networks to find associations with functional profiles, tissue or disease specific biomarkers, and other genes in the same pathways and networks. We also use open-source network and visualization tools DAVID, Cytoscape, and Reactome to complement network/pathway analysis to increase the accuracy and sensitivity of network/biomarker identification.
Custom Data Analysis
Our computational infrastructure and expertise enables cutting-edge custom analysis for a broad range of genomics applications. We will customize an analysis plan for each project in close consultation with each investigator.