Genome data analysis for medical professionals
User Manual

Reveal a single mutation across millions of nucleotides

Fast, accurate and easy-to-use service helps geneticists and clinical researchers to analyze genome information for inherited disease diagnostics

BINOM, Genome data analysis for medical professionals
Increase your lab efficiency
with our cloud-based service:
a whole genome analysis takes
less than three hours
Vcf, bam, fastq, ab1 support
Enjoy our seamless pipeline
and upload files at any step
of analysis you need
Patient-centric outlay
Easy patient data management,
all relevant files are at your fingertips
Try FitKit
FitKit is an enrichment selection tool created by iBinom

Data analysis pipeline

The iBinom pipeline improves analysis through precision, sensitivity and specificity. This is accomplished by quality control and efficient algorithms finely tuned by our team.
Works with any of the most popular sequencing instrument specification. We guarantee reproducible and ultimately accurate results.
Percentage of low quality and mapped readsAverage length of reads and depth of coverageSAMtools variant caller
v. 1.2
BWA-MEM aligner
v. 0.7.8
Regular GC content

iBinom variant filtration tool

The iBinom filtration system is intuitive and flexible. It shortens the path to detecting the causative variants. Databases are always up-to-date. Files can be re-analysed whenever needed.

Genes and variants

Filter by gene name, coordinates, rsID


Search by internal disease database and ACMG incidental findings list

Data quality

Apply thresholds for VCF coverage depth and calling quality

Variant information

Filter by effect, zygosity and variant type

Population frequency

Filter by frequencies for different cohorts from ExAC, 1000GP3, TwinsUK, ESP6500, ALSPAC

Pathogenicity and conservation scores

Filter by SIFT, polyphen2, mutationtaster, FATHMM and other scores

Variant report

The report shows the most credible variants discovered from the last filtering step. No more endless candidate variants to consider.

The report is designed according to the ACMG's recommendations


Show pathogenicity by deviation to the right on the strip.


Show low mutation frequency by lowering the slope on the graph.

Database and filtering list

Variant effect
Intergenic, Intragenic
Exon Deleted
Synonymous coding, vstart, stop
Non synonymous coding, start
Frame shift
Utr 3, 5
Start lost, stop gained, stop lost
Splice site acceptor, donor
Pathogenicity scores
SIFT, ensembl 66, 15’ jan
MutationAssessor, v2, 13’ sep
MutationTaster, v2, 14’ jul
Phastcons7way vertebrate, 14’ jun
Phylop7way vertebrate, 14’ jun
PolyPhen hvar, v 2.2.2, 12’ feb
Fathmm, v2.3, 14’ nov
SiPhy 29way, 11’ may
GERP++ , 11’ may
Population frequency
UK10K (TwinsUK and ALSPAC), 14’ jun
1000 Genomes, phase 3, 15’ feb
ESP6500, 14’ nov
ExAC v0.3, dec’ 14
Disease databases
Manually curated databases
dbSNP build 144, 15’ jun
Clinvar, 17’ may
dbNSFP, v3.4, 17’ apr
Sequencing quality
Strand bias
BaseQ bias
MapQ bias
End distance bias
Variant quality
Variant type and localization
Homozygote, heterozygote
Chromosome position
Autosomal, sex
dbSNP id


The core team has versatile competencies, education and experience which comprises biotech companies' management and growth, molecular biology and bioinformatics deep knowledge, algorithms and IT strong expertise along with international business skills.


Maxim Kuleshov

Maxim Kuleshov

Bioinformatician – Icahn School of Medicine at Mount Sinai

Ilya Korvigo

Ilya Korvigo

Research engineer at ARRIAM

Kirill Grigorev

Kirill Grigorev

Bioinformatician at the Caribbean Genome Center