InsideDNA Bioinformatics and Genomics Consulting & Training

We provide professional bioinformatics and genomics consulting to researchers and scientists. Our first priority is to make you independent and confident in bioinformatics and genomics data analysis. Our next main priority is to ensure that as a result of our collaboration you have high quality research papers and they are accepted to impactful journals.

Because we work a lot with academic researchers, our goal is to have as affordable service as possible. Whether your consumables budget is less 100$ per month or >1000$, we can make your NGS analytics working. Our hourly rate starts as low as $35 per hour and you can find detailed pricing per each type of analysis here.

What we do

Bioinformatics and Genomics Analysis consulting

We work with researchers (faculty, staff, post-docs and graduate students) to provide analysis of their high- throughput sequencing, genomics, gene expression, metabolomics, proteomics, and other biological data. Most importantly, we provide full access to all custom pipelines and mentor all labs members to become confident in bioinformatics analysis.

Genomics and bioinformatics pipeline development

We’ll help to develop custom applications to enhance research for genomics analysis, create custom pipelines, databases and/or visualization, and web services interfaces to large databases, and custom analysis tools.

Establishing cloud infrastructure for genomics and bioinformatics

Cloud services such as those provided by Amazon and Google are increasingly being used by bioinformaticians and genomics researchers around the world. Cloud computing lets you run virtual machines on remote servers, with various levels of support in place for bioinformatics. We can help to kickstart your lab’s use of cloud computing and help with ongoing training.

Consulting prior to experiments and grant proposal writing

We’ll meet with you to discuss the types of analysis and support for bioinformatics and genomics we can provide. We’ll help you to design genomics experiments. We’ll also help to incorporate bioinformatics and genomics data analysis in your research plan in grant proposals.

System administration and bioinformatics workstation server set up and consulting

We support your lab’s in building computing infrastructure. Apart from our SAAS, we can provide tailored solution specifically for your needs whether it's an infrastructure, bioinformatics tool adoption or required tool development. We’ll analyze your requirements for bioinformatics and genomics research and challenges, propose the design of solution and roll out this solution in your lab. Furthermore, we’ll perform all system upgrades, install software as needed.

Training in Bioinformatics and Genomics Training

We run training programs online and offline and assist researchers in learning the computational tools that can be translated back to their labs. We strive to increase skills of researchers worldwide in genomics and bioinformatics and frequently publish step-by-step guides which cover different types of NGS data analysis.

Types of analysis we do

  • General quality control pre-processing
  • Samples quality control
  • Samples quality filtering
  • Reads/samples/barcode demultiplexing
  • CNV discovery and variant control
  • CNV discovery
  • SNP quality control and filtering
  • CNV quality control and filtering
  • Transcriptome analysis
  • Whole transcriptome mapping
  • Mapping quality control
  • Quality score recalibration
  • SNP/indels variant discovery
  • SNP quality control and filtering
  • Comparative genomics
  • De novo CDS detection (non-human only)
  • CDS annotation (human and non-human)
  • Reciprocal BLAST
  • Detection of orthologous groups
  • Postprocessing and filtering of orthologous groups
  • Group-specific phylogeny reconstruction
  • Core genome reconstruction
  • SNP/indels variant discovery in core genome only
  • SNP quality control and filtering in core genome only
  • eQTL mapping
  • Whole transcriptome mapping
  • Mapping quality control
  • Quality score recalibration
  • Normalization to FPKM
  • Genotype data quality control
  • Statistical analysis (linear regression)
  • Evolutionary genomics and viral resistance/evolution
  • Same processing as for comparative genomics/transcriptomics
  • Scans for positively selected CDS
  • Scans for positively selected SNPs
  • Population genetics analysis (Fst, Structure)
  • Genome/Transcriptome de-novo assembly
  • Assembly with 6 different algorithms
  • Comparative analysis of resulting assemblies
  • Exome Mendelian disease
  • Common variants annotation against 3 databases
  • (dbSNP, Ensemble, 1000 Genomes)
  • Variants classification by damage effect (frameshift, nonsense, essential splice site, missense, nonstop, synonymous coding)
  • Segregation-Score Parameter Analysis
  • Variant prioritization
  • Comparative transcriptomics
  • Transcripts normalization and filtering
  • De novo CDS detection (non-human only)
  • CDS annotation (human and non-human)
  • Reciprocal BLAST
  • Detection of orthologous groups
  • Post-processing and filtering of orthologous groups
  • Group-specific phylogeny reconstruction
  • Core genome reconstruction
  • SNP/indels variant discovery in core genome only
  • SNP quality control and filtering in core genome only
  • GWAS
  • Genotype data quality control
  • Benchmark against dbGaP
  • Statistical analysis (linear regression)
  • Phylogenomics
  • Maximum likelihood tree reconstructions
  • Bayesian tree reconstruction
  • Phylogenetic dating (subject to fossils available)
  • Metagenomics (16S or WGS)
  • Assembly of shotgun metagenomics data
  • Annotation of metagenomics sequences
  • Data denoising (16S only)
  • OTU clustering, picking, and taxonomic assignment (16S only)
  • Statistical analysis and visualization of results
  • Metagenomics classification
  • Metagenomics binning
  • Exome mapping and variant calling
  • Whole exome mapping
  • Mapping quality control
  • SNP/indels variant discovery
  • Advanced Mendelian disease
  • Shared identity-by-descent (IBD) mapping
  • Rare-heterozygote-rule-out (RHRO) mapping
  • Identification of regions of maximum pairwise identity-by-descent
  • Rare Heterozygote Rule Out Analysis
  • Manual verification of causal variants with
  • HGMD and OMIM
  • RNA-seq expression analysis
  • Normalization to FPKM
  • Data quality assessment (heatmaps)
  • Co-expression clustering
  • GO enrichment
  • Differential expression analysis
  • Pathways analysis RNA-seq
  • Normalization to FPKM
  • GAGE analysis
  • KEGG pathways mapping
  • Up/down regulation pathways visualization
  • Epigenetics
  • Whole genome bisulfite mapping
  • Mapping quality control and deduplication
  • Identification of differentially methylated regions
  • Functional annotation of DMR
  • GO analysis of DMR
  • GWAS enrichment of DMR
  • Target discovery for drug design
  • Comparative gene expression assays
  • Comparative proteomic profiles
  • Scans for genes/proteins essential for infectious
  • agent and distinct from host genes/proteins
  • Scans for genes and gene modifications associated
  • with a disease
  • Scans for proteins or protein modifications
  • associated with a disease.
  • Identification of regulatory pathways required
  • for disease process