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1 - 23 of 23 results

1 - 23 of 23 results

POLYSOLVER / POLYmorphic loci reSOLVER

Enables high precision Human Leukocyte Antigen (HLA)-typing even. POLYSOLVER uses relatively low coverage whole exome sequencing (WES) data and a subsequent mutation detection pipeline that is based on the inferred alleles to detect mutations in HLA genes. The tool is able to infer HLA-type information with 97 per cent sensitivity and 98 per cent precision from exome-capture sequencing data. It can extract sequence and mutation information from other polymorphic regions in the genome.

Applies assembly, allele identification and allelic pair inference to short read sequences, and applied it to data from Illumina platforms. In 15 data sets with adequate coverage for HLA-A, -B, -C, -DRB1 and -DQB1 genes, ATHLATES correctly reported 74 out of 75 allelic pairs with an overall concordance rate of 99% compared with conventional typing.

A HLA genotyping algorithm based on integer linear programming, capable of producing accurate predictions from NGS data not specifically enriched for the HLA cluster. OptiType significantly outperformed previously published in silico approaches with an overall accuracy of 97% enabling its use in a broad range of applications.

Permits to screen raw Illumina high-throughput sequencing (HTS) data for sample swaps for datasets where the Human Leukocyte Antigen (HLA) loci are covered. HLA-MA is based on the HLA typing result of the state-of-the-art method OptiType. It uses information from small but genetically highly variable regions and thus complements approaches that rely on genome or exon-wide variant profiles. The tool takes a relatively short time and can be run before or in parallel with the usual downstream processing.

A software for HLA class I and II predictions from next-generation shotgun (NGS) sequence read data that supports direct read alignment and targeted assembly of sequence reads. This approach circumvents the additional time and cost of generating HLA-specific data and capitalizes on the increasing accessibility and affordability of massively parallel sequencing.

A tool for HLA typing from NGS data based on read-mapping using a comprehensive reference panel containing all known HLA alleles, followed by de novo assembly of the gene-specific short reads. Accurate HLA typing from NGS data holds much promise for applications in clinical laboratories and biomedical research. Preliminary analysis on both public and local datasets indicates a great potential for broad application of this method.

An algorithm for HLA type inference from next-generation sequencing data. HLA-PRG outperforms existing methods by a wide margin and for the first time consistently achieves the accuracy of gold-standard reference methods with one error across 158 alleles tested. HLA-PRG will enable researchers to augment population-scale whole-genome sequencing data with reliable HLA type information and contribute to characterizing HLA signals in important medical phenotypes.

A tool algorithm named to discover the most probable pair of HLA alleles at four-digit resolution or higher, via a unique integration of a candidate allele selection and a likelihood scoring. PHLAT significantly leverages the accuracy and flexibility of high resolution HLA typing based on genome-wide sequencing data. It may benefit both basic and applied research in immunology and related fields as well as numerous clinical applications.

An efficient and accurate human leucocyte antigen (HLA) typing method using high-throughput sequencing data without the need of primer design for HLA loci. In the first step of the HLA-VBSeq pipeline, read sequences are aligned to the reference genomic sequences of the registered HLA allelles in the IMGT/HLA database, in which multiple hits are allowed. Then, HLA-VBSeq optimizes both read alignments to the HLA allele sequences and relative quantities of reads on HLA alleles simultaneously under a statistical framework by variational Bayesian inference. Our approach considers all the possible alignments of reads to HLA allele sequences, and calculates the marginal likelihood of data from gapped alignments of reads to the reference sequences, in which deletions and insertions as well as SNP sites are naturally considered. It does not assume any prior knowledge about HLA allele frequencies, and hence HLA-VBSeq is broadly applicable to human samples obtained from a genetically diverse population.

Predicts HLA haplotype by hierarchically weighting reads and using an iterative, greedy, top down pruning technique. HLAforest uses BioPerl to read in FASTA files. Alignments use Bowtie, although any alignment tool can be used to generate SAM alignments for use as input to HLAforest.

Allows human leucocyte antigen (HLA) haplotype frequency estimation. Hapl-o-Mat preprocesses the input genotype data, resolves genotyping ambiguities, translates alleles to a uniform resolution per locus and then computes the most likely set of haplotypes including their frequencies via the expectation-maximization (EM) algorithm. The software handles large-scale HLA genotype data. Its accuracy and performance were demonstrated on the basis of artificial and real genotype data.

Provides functions for association analysis, zygosity tests, and interaction tests between HLA alleles and diseases. PyHLA is a Python package which implements several methods for HLA association analysis, to fill the gap. It is a tailor-made, easy to use, and flexible tool designed specifically for the association analysis of the HLA types imputed from genome-wide genotyping and NGS data. This method is applicable to small and large sample sizes and can finish the analysis in a timely manner on a personal computer with different platforms. PyHLA is designed for case-control studies and is currently unable to analyze family-base datasets.

Performs alignment of reads to human leukocyte antigen (HLA) sequences from the international ImMunoGeneTics project (IMGT)/HLA database. HLAscan is an alignment-based multi-step HLA typing method considering read distribution. It outperforms the established next generation sequencing (NGS)-based methods but also may complement sequencing-based typing methods when dealing with high-depth (average 90×) short sequence reads. This method could be generally applied for variant calling in highly polymorphic regions.

A NGS data analysis pipeline allowing user to make HLA alleles genotyping quickly and efficiently. HLATyphon supports all cDNA template of HLA locus A, B, C, DPA1, DPB1, DQA1, DQB1 and DRB1 in IMGT/HLA database. Currently the internal HLA allele reference sequences of HLATyphon were from IMGT/HLA database release 3.17.0 including 12,010 alleles.

Assists for the assignment of human leukocyte antigen (HLA) type. Assign can accomplish base calling, edit sequences, import sequence data and compare sample consensus sequences via a HLA / international ImMunoGenTics (IMGT) database of alleles. This software contains sequence quality control analysis and genotyping to ease high-throughput sequencing-based typing (SBT). Analysis of Phred quality values are done to deliver results for a sample and a sequencing run.

SAF / Second Allele Finder

Allows users to analyze a sequencing data. SAF is a program that assists researchers in working on typing Human Leukocyte Antigen (HLA) loci in tissue transplantation, particularly in bone marrow transplantation.

Generates human leukocyte antigen (HLA) full-length allele sequence submissions. Saddlebags was developed to streamline the process of preparing allele submissions for Immuno Polymorphism Database-international ImMunoGeneTics project/HLA (IPD-IMGT/HLA) database. It allows submission of full-length HLA sequences to EMBL European Nucleotide Archive (EMBL-ENA) for subsequent submission at IPD-IMGT/HLA.

Provides a set of tools to calculate the full posterior distribution of human leukocyte antigen (HLA) types given read data. Prohlatype consists of: (i) downloading IMGT-HLA database, (ii) creating an imputed HLA reference sequences via the tool align2fasta, (iii) using the previously generated sequence database to filter user’s data via an aligner (iv) exporting the reads from the filtered bam file to a FASTQ file and (v) allowing users to calculate the likelihood with multi part.

Allows to discover and genotype sequence variants in large populations using pangenome graphs. Graphtyper is a population-scale genotype caller. The software locally realigns sequence reads from a genomic region to a pangenome graph, and concomitantly genotypes sequence variants in all individuals. Using variation-aware realignment, it is capable of characterization of the region’s variation with no Mendelian errors and no falsely reported additional sequence variants around the indel.

Omixon Target HLA Typing

Gives high resolution results with whole genome, exome or very targeted DNA data, or with RNA seq data. Omixon Target HLA Typing offers high possible HLA typing precision using NGS data. There is no need to be an expert in NGS analysis to use the tool.

Provides a next-generation genomic analysis software platform. HISAT-genotype is based on a human reference genome and on the HISAT2 software to represent and find a significantly expanded model of the human reference genome via a graph. This software is designed for processing whole genome sequencing reads generated by Illumina platforms and supports paired-end reads.

Gyper / Graph genotYPER

Allows to align DNA sequencing data. Gyper is a genotyper which provides a partial order graph which represents haplotypes. The software supports six Human Leukocyte Antigen (HLA) genes: HLA-A, HLA-B, HLA-C, HLA-DQA1, HLA-DQB1, and HLA-DRB1.

Provides a method for statistical refinement of low or intermediate resolution HLA (Human Leucocyte Antigen) data, when a full resolution training data set from a similar population is available. HLA Completion tool introduces a methodology, improving upon the Expectation-Maximization (EM)-based approaches currently used within the HLA community. The improvements are achieved by using a parsimonious parameterization for haplotype distributions and by smoothing the maximum likelihood (ML) solution. These improvements make it possible to scale the refinement to a larger number of alleles and loci in a more computationally efficient and stable manner. This HLA refinement method helps to mitigate the limiting factor of cost in HLA typing, and allows for lower/intermediate resolution, or historical data to be statistically refined when it cannot be refined by assay.

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Big data scientist National institute of Plant Gneome Reseaech (NIPGR)

Research Interests Gene fusion detection in Plants Fusion transcripts (i.e., chimeric RNAs) resulting from gene fusions are well known in case of human. But, in plants, this phenomenon is not yet explored. We are planning to discover the fusion transcripts/gene fusions in different type of plants by using RNA-Seq datasets. Further, we are planning to understand the mechanism of gene fusion formation and significance of fusions in plants. Whole genome and transcriptome sequencing data analysis of Plants In this era of Next Generation Sequencing (NGS), there is huge amount of sequencing data available in the public domain. Any novel finding from these available datasets is major challenge for a computational biologist. We are interested in the analysis of whole genome and transcriptome sequencing data of different plants to fetch out the useful information from those datasets, with the help of bioinformatics tools. Currently, we are planning to study the gene clusters of secondary metabolite pathways in different plants. Development of webservers, databases and computational pipelines for plant research Development of database is necessary to compile and share the information with scientific community. We are dedicated to develop useful databases and webserver for plant research. Another area of interest is to develop automated pipelines and tools for the analysis of high throughput genomics data, generated by NGS technologies. Professional & Academic Background Staff Scientist II (May 2017- present): National Institute of Plant Genome Research (NIPGR), New Delhi, India Postdoctoral Research Associate (2015-2017): University Of Virginia, Charlottesville, VA, USA Research Scientist (2014-2015): Sir Ganga Ram Hospital, New Delhi, India PhD Bioinformatics (2009-2014): Bioinformatics Centre, Institute of Microbial Technology (IMTECH), Chandigarh under Jawaharlal Nehru University (JNU), New Delhi, India M.Sc. Life Sciences (2007-2009): Jawaharlal Nehru University (JNU), New Delhi, India B.Sc. Biotechnology (2004-2007): Jamia Millia Islamia (JMI), New Delhi, India Awards and Fellowships Junior and Senior Research Fellowship (2009-2014): Council of Scientific and Industrial Research (CSIR), New Delhi, India GATE (Graduate Aptitude Test in Engineering): Qualified in years 2008 and 2009 Scientific Contributions/ Recognitions Associate editor: Journal of Translational Medicine. Editorial Board Member of Journal: Theoretical Biology and Medical Modelling. Reviewer: PloS One, BMC Genomics, BMC Bioinformatics, BMC Biology, BMC Biotechnology, Frontiers in Physiology and several other journals. Web Resources/ Databases (Developed/ Contributed) A Platform for Designing Genome-Based Personalized Immunotherapy or Vaccine against Cancer (http://www.imtech.res.in/raghava/cancertope/) GenomeABC: A webserver for benchmarking of genome assemblers. (http://crdd.osdd.net/raghava/genomeabc/). Genomics web portal page. (http://crdd.osdd.net/raghava/genomesrs/). Map/Alignment module of CancerDr: Cancer Drug Resistance Database. (http://crdd.osdd.net/raghava/cancerdr/). Short reads and contigs alignment module of PCMDB: Pancreatic cancer methylation database. (http://crdd.osdd.net/raghava/pcmdb/). Burkholderia sp. SJ98 database. (http://crdd.osdd.net/raghava/genomesrs/burkholderia/). Rhodococcus imtechensis RKJ300 database. (http://crdd.osdd.net/raghava/genomesrs/rkj300/). Genotrick: A pipeline for whole genome assembly and annotation of Genomes (http://crdd.osdd.net/raghava/genomesrs/genotrick/) Development of Debian packages in OSDDlinux: A Customized Operating System for Drug Discovery. (http://osddlinux.osdd.net/). A Web-Based Platform for Designing Vaccines against Existing and Emerging Strains of Mycobacterium tuberculosis. (http://crdd.osdd.net/raghava/mtbveb/).

FusionFinder comrad

Mahantesh Biradar

‎Graduate PhD researcher focusing on Cardiovascular Epidemiology & Social Media Enthusiast Research Stash

I'm a Graduate PhD researcher in the area of Biomedical Science and focussing on the Pharmacogenomics/Pharmacogenomics of Diabetes and related complications

HLA genotyping software tools | Whole-exome sequencing data analysis

The human leukocyte antigen (HLA) gene cluster plays a crucial role in adaptive immunity and is thus relevant in many biomedical applications. While next-generation sequencing data are often available for a patient, deducing the HLA genotype is difficult because of substantial sequence similarity within the cluster and exceptionally high variability of the loci.

Source text:
(Szolek et al., 2014) OptiType: precision HLA typing from next-generation sequencing data. Bioinformatics.

Parent category

Related step

Benchmarking

(Bauer et al., 2016) Evaluation of computational programs to predict HLA genotypes from genomic sequencing data. Brief Bioinform.
PMID: 27802932

(Bauer et al., 2016) Evaluation of computational programs to predict HLA genotypes from genomic sequencing data. Brief Bioinform.
PMID: 27802932

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