Analyzes two types of RNA-seq: single cell data and bulk data. URSM adjusts dropout events in single cell data and achieves simultaneously deconvolution in bulk data. This software doesn’t need to calculate on the same subjects the single cell and bulk data. It can (1) obtain reliable estimation of cell type specific gene expression profiles; (2) infer the dropout entries in single cell data; and (3) infer the mixing proportions of different cell types in bulk samples.
Interprets differential expression (DE) detection of RNA-Seq experiments with a small number or non-replicated samples in each class. LPEseq evaluates the baseline error distribution for each of the compared experimental conditions. It can be used on datasets containing replicates and is also efficient for non-replicated datasets. This tool is able to remove outliers derived from the replicates assumption between classes.
Characterizes circRNAs candidates. FUCHS provides the user with directions for further steps to investigate the circRNA’s function and biogenesis. FUCHS is able to identify alternative exon usage within the same circle boundaries, summarize the different circles emerging from the same host-gene, quantify double-breakpoint fragments as indicator for circularity and visualize a circRNA’s read coverage profile independent of any genome browser.
Infers relative poly(A) site used in terminal exons from RNA sequencing data and KAPAC. PAQR is composed of three modules: (1) a script to deduce transcript integrity values, (2) a script to create the coverage profiles for all considered terminal exons, and (3) a script to obtain the relative usage together with the estimated expression of poly(A) sites with sufficient evidence of usage. The software enables evaluation of 3′ end processing in data sets such as those from The Cancer Genome Atlas (TCGA).
Identifies large-scale copy-number variants (CNVs) in scRNA-seq. CONICS provides a method to separate neoplastic cells for downstream analysis. It includes algorithms to triage cells from a scRNA-seq assay, based on the presence of CNVs detected in an orthogonal DNA sequencing experiment. It integrates tumor-normal fold-changes with the minor-allele frequencies of point mutations to estimate false-discovery rates (FDRs) in CNV classification. Additionally, it includes routines to perform downstream phylogeny assessment and gene co-expression analysis.
Estimates 3’ untranslated region (UTR) landscape from RNA-seq. GETUTR has three steps: (1) preprocessing for the extraction of all reads in RNA-seq data, (2) smoothing via algorithms and (3) normalization applied for all genes. Three smoothing algorithms that were tested on their average lengths of 3’ UTR and on the prediction of polyadenylation cleavage site (PCS) are available through this software.
Performs error correction in RNA-Seq data. SEECER is a method based on profile a hidden Markov Model (HMMs). This method does not require a reference genome. It can handle non-uniform coverage and alternative splicing, both key challenges when performing RNA-Seq. This application is applicable to de novo RNA-Seq because it does not rely on a reference genome.
A method for capturing both ribosomal RNA variable regions and their flanking protein-coding genes simultaneously. This approach goes beyond traditional metagenomic analysis by taking into account not only phylogenetic features of 16S rRNA typing but also metagenome-scale genes derived from the same sample. Combined with classical amplicon sequencing and shotgun metagenomic sequencing, RiboFR-Seq can link the annotations of 16S rRNA and metagenomic contigs to make a consensus classification, and can accurately locate multiple 16S rRNA sequences through BRPs and thus can assist to metagenomic assembly and binning.
An easy-to-use web application that allows the user to visualize RNA-seq data and other genomic annotations on RNA secondary structures. SAVoR is designed to help researchers visualize sequencing data in the context of RNA secondary structures.
Enables the storage, use and understanding of genetic data. Sequencing is a collaborative platform permitting to integrate genetic data into software applications, and which thus aims to connect researchers with app developers. Users can securely store their data and utilize personalized apps that can analyze data from several genetic test including 23andMe, Ancestry.com, Family Tree DNA, and Whole Genome Sequencing. DNA-powered apps can be built without having to know genetics.
Improves the sensitivity and efficiency of Single-Cell RNA-Barconding and Sequencing (SCRB-seq). mcSCRB-seq is a highly flexible, fast and efficient library protocol with low set-up costs and hence can be a valuable methodological addition for many laboratories.
Analyzes exogenous and human sequences from RNAseq data. RNA CoMPASS is a parallel computation pipeline that provides a graphic user interface built from several open-source programs such as Novoalign and SAMMate. The application reads both the unmapped reads for pathogen discovery and the mapped reads for host transcriptome analysis. The program supports files generated from single-end, paired-end, and/or directional sequencing strategies.
Allows to analyse, annotate, compare and visualize small RNA sequencing data. SPAR offers to users the possibility to streamline interpretation of small RNA-seq results and to compare with up to hundreds of publicly available datasets. This tool executes unsupervised segmentation to identify sncRNA loci displaying features of specific processing in the provided sequencing data. This pipeline is available through a web application and a standalone software.
Provides a comprehensive integrated pipeline for analyzing small RNA deep sequencing data. CPSS delivers analysis report from ncRNA quantification to miRNA target prediction and annotation of single and multiple datasets. The webserver supports more than 40 species. Each detailed result pages include a search function to find specific terms or values. For Gene Ontology (GO), pathway and protein domain analysis, users can optimize parameters and rerun analysis at each detailed result page.
Allows to execute DNA-seq/RNA-seq pipeline. Halvade is a Hadoop MapReduce implementation that enables sequencing pipelines to be executed in parallel on a multi-node and/or multi-core compute infrastructure. The software depends on existing tools, requiring additional data besides the raw sequenced reads, to run the pipeline. It provides functionalities to partition the reference genome in chunks and to copy external dependencies (files or databases) to the worker nodes.
Provides assistance for internal controls that can assess almost all stages of the RNA-seq workflow. Sequins supports library preparation, sequencing, split-read alignment, transcript assembly, gene expression and alternative splicing. This software is appropriate to evaluate downstream bioinformatic steps, enhance the optimization parameter choice and can be used as normalization factors to compare multiple sample.
Offers a platform for the detection of genomic features into transcripts from next generation RNA sequencing data. RNA-eXpress provides a graphic user interface (GUI) dedicated to the identification of splice variants, transcription start sites, UTRs, introns as well as non-coding RNA features. Users can run feature annotation, comparison, sequence extraction and read counting. The application can supply results as summary statistics, histograms or pie charts.
Generates/analyzes a regulatory network and states transition network and computes informations like entropy. RNA takes as entry an interaction network. It computes some information from the states transition network like the entropy and the derrida coefficient. The layout selected default in the tool is Grid Layout, the grid layout was selected because of some tests of performance made.
Estimates potential RNA modification sites basing on nucleotide mismatches within sRNAs. SPORTS1.0 cleans reads by removing sequence adapters and discarding sequences with length beyond the defined range and those with bases other than ATUCG. It studies sequence mismatch information if mismatches are allowed during alignment process. This tool is useful in biomedical and evolution research that relate to sRNAs.
Consists of a terminology designed for RNA sequencing. ORNASEQ is based on the ontology for biomedical investigations (OBI). It supplies a list of about 160 terms, some of the terms are from several existing ontologies, and more than 20 terms that have been added to OBI. This ontology is useful for the annotation of RNA-based next-generation sequencing and DNA-based next-generation sequencing data.
Provides RNA-RNA interactions (RRIs) identified through high-throughput sequencing technologies. RISE is a comprehensive database of RNA interactome from sequencing experiments. It includes (i) comprehensive curation of RRIs, (ii) a large dataset of RRIs among mRNAs and lncRNAs, (iii) details of the interacting sites and (iv) extensive annotations for each RRI. It provides an assistance for researchers looking for interaction and other functional information on individual RNAs, and analyzing RRI networks of specific pathways or systems.
Annotates and explains available next-generation sequencing (NGS) techniques and their data analysis methods. SequencEnG is an web resource that contains about 60 NGS techniques organized into a knowledge tree based on genetic or epigenetic information being assayed. Interactive data analysis pipelines are available for RNA-seq, ChIP-seq, Hi-C, and Whole Genome Bisulfite Sequencing (WGBS), with lists of major bioinformatics tools for each analysis step in the pipelines. It can be useful for students and researchers entering bioinformatics and the NGS field.
Offers a way to search for data on sequence variants in Finns. SISu provides valuable summary data for researchers and clinicians as well as other people having an interest in genetics in Finland. With SISu, users can examine the attributes and appearance of different variants in Finnish cohorts and see their aggregate distribution in Finland visualized on a map. Users can search for summary data on single nucleotide variants (SNVs) and indels from exomes of over 10 000 individuals sequenced in disease-specific and population genetic studies. The SISu project is an international collaboration between multiple research groups aiming to build tools for genomic medicine. The first version of the SISu search engine was released in 2014. The project is coordinated in the Institute for Molecular Medicine Finland (FIMM) at the University of Helsinki.
RRDB is comprehensive and nonredundant RNA-RNA docking benchmark. This dataset was organized into three different groups according to the interface conformational changes between bound and unbound structures: 47 ‘easy’, 38 ‘medium’, and 38 ‘difficult’ targets. This resource is beneficial for the development and improvement of docking algorithms and scoring functions for RNA-RNA interactions.
An online library of RNA binding proteins and their motifs. These data provide an unprecedented overview of RNA-binding proteins and their targets, and constitute an invaluable resource for determining post-transcriptional regulatory mechanisms in eukaryotes.
Provides a resource for the automatic search of user tailored, three dimensional fragments within a set of RNA structures. RNA FRABASE is a web-accessible database with an engine for automatic search of the 3D fragments. It includes a large collection of structural data about RNA molecules, in both their isolated and complexed form, all of which is derived from their PDB deposited atom coordinates.
Consists of a sequence resources of plant small RNAs from representative species across the plant kingdom. Comparative Sequencing of Plant Small RNAs database is a repository containing data that enables studies of microRNAs (miRNA) and short-interfering RNAs (siRNAs). Five analysis tools are available to query the small RNA data set, with options to identify sequences based on homology, expression levels, conservation, or potential function.
A web-based repository of RNA-Seq gene expression profiles and query tools. The website offers open and easy access to RNA-Seq gene expression profiles and tools to both compare tissues and find genes with specific expression patterns. To enlarge the scope of the RNA-Seq Atlas, the data were linked to common functional and genetic databases, in particular offering information on the respective gene, signaling pathway analysis and evaluation of biological functions by means of gene ontologies. Additionally, data were linked to several microarray gene profiles, including BioGPS normal tissue profiles and NCI60 cancer cell line expression data. Our data search interface allows an integrative detailed comparison between our RNA-Seq data and the microarray information.
Allows users to find different types of gene expression. Brain RNA-seq is an online database that utilizes a sensitive algorithm to detect alternative splicing events in each cell type. This online resource hosts different information presented through several graphs. These graphs contain information on mouse brain and human brain (astrocytes, neurons).
Stores information about recurrent RNA 3D motifs and their interactions, found in experimentally determined RNA structures and in RNA-protein complexes. Besides, the search utility enables searching 'RNA bricks' according to sequence similarity, and makes it possible to identify motifs with modified ribonucleotide residues at specific positions.
Contains a collection of z-score based binding sites specific to RNA binding protein (RBP) motifs across the human and mouse genomes. MotifMap-RNA allows user to filter and sort the results based on clustering of local binding sites or evolutionary conservation, quantified by Bayesian branch length scores (BBLS). It provides four major classes of genomic sequences: UTRs, intronic regions, lncRNAs and miRNAs, for all of which we generated class specific model parameters.
Provides aggregate networks generated with information derived from “Affymetrix Human Genome U133 Plus 2.0 Array” microarray platform. RNA-seq networks is composed of two downloadable files in R format. The first: RNA-Seq aggregates network numbers 30,705 nodes compiled from 50 individual co-expression networks and 1,970 samples. The second: microarray aggregates network, consists of a gathering of 43 individual co-expression networks, 20,283 nodes and 5,134 samples.
Aims to integrate genomic and sequence-based annotation with gene expression regulation, secondary and 3D structure information, protein interactions, and their inter-relationships. NCRO consists in a standardized resource for: (1) annotating data about all forms of non-coding RNAs (ncRNAs) and (2) facilitating knowledge capture in the ncRNA domain. This ontology is useful to better understand unification of ncRNA biology.
Contains known RNA secondary structures of any type and organism. RNA STRAND provides access to detailed information on known secondary structures as well as statistical analyses of structural aspects of various types of RNAs. The database provides a convenient web interface to its major functions and supports searches according to many criteria, including properties of secondary structure elements. RNA STRAND is publicly accessible and supports the submission of new RNA structures by the research community.
Contains RNA-secondary structure predictions and a set of additional parameters for all upstream regions of all genes of diverse bacterial genomes. RNA-SURIBA database provides in addition drawings of the structures of each structure prediction. Tables are named according to the bacterial species and each table consists of columns with the structure predictions, sequences, gene annotation data and calculated parameters for each structure.
Lists potential miRNA response elements (MRE) containing genes that can act in a sponge like fashion (absorbing and releasing miRNA based on the level of the transcript) for a given mRNA based on a set of scoring and ranking criteria. ceRDB, for each mRNA, defines an interaction score by adding up the total number of miRNA binding sites that overlap with the miRNA for a given mRNA. This interaction score is used to sort the results and the top 50 predicted potential ceRNAs are returned. This process is carried out on the fly using PHP interactions with the mySQL database.
Provides a comprehensive MIAME-supportive infrastructure for gene expression data management and makes extensive use of ontologies. Specific details on protocols, biomaterials, study designs, etc. are collected through a user-friendly suite of web annotation forms. Software has been developed to generate MAGE-ML documents to enable easy export of studies stored in RAD to any other database accepting data in this format (e.g. ArrayExpress). This infrastructure enables a large variety of queries that incorporate visualization and analysis tools and have been tailored to serve the specific needs of projects focusing on particular organisms or biological systems.
Presently, I am working as professor & head of Computational Biology, IIIT-Delhi. Before joining IIT Delhi, I worked as Scientist at Bioinformatics Centre, Institute of Microbial Technology (IMTECH), Chandigarh, India. More information is available from following sites Home Page of Gajendra P. S. Raghava's Group (http://www.imtech.res.in/raghava/) , Computational Resources for Drug Discovery (http://crdd.osdd.net/) , A Customized Operating System for Drug Discovery (http://osddlinux.osdd.net/)and and Gajendra Pal Singh Raghava - Wikipedia (https://en.wikipedia.org/wiki/Gajendra_Pal_Singh_Raghava) .
Experienced researcher skill in Liquid Chromatography-Mass Spectrometry (LC-MS), Proteogenomics, Onco-Proteogenomics, Next-Generation Sequencing(NGS), Multiplexed/Co-Fragmented spectrum from the co-eluted peptide with proteogenomics data analysis, Efficient Localization of Phosphorylated peptide from High-resolution mass spectrometry, Advanced Multi-Stage cancer proteogenomics database search for identification of novel mutation,INDELs,Junction and most importantly their Post-Translational Modification for better clinical understanding with multi-omics data, Recombinant DNA, DNA Sequencing, Cheminformatics, and Cancer Research. Strong research professional with a Doctor of Philosophy (Ph.D.) focused in Clinical Biochemistry, Clinical Oncology, Advanced Bioinformatics, Mass Spectrometry, Proteomics from 고려대학교 / Korea University.