Resources

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Below we highlight some of our tools and resources. You may view a list of the associated literature [http://papers.gersteinlab.org/subject/resources/index.html here]. You may also view a [http://papers.gersteinlab.org/subject/coretools/index.html list of the papers associated with our core tools & resources]. Source code is available on our [http://github.gersteinlab.org/ Github page].
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The tools & resources listed below have been '''published and are actively maintained''' by the Gerstein lab. You may view a list of the associated literature [http://papers.gersteinlab.org/subject/coretools/index.html '''here'''].  
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In addition to the tools below, the lab has also published a number of [http://info.gersteinlab.org/More_tools '''tools that are not currently being actively maintained'''].
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You may also access tools that have [http://info.gersteinlab.org/Even_more_tools '''not yet been published''']
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Source code for all software is available on our Github page: [http://github.gersteinlab.org/ Github.gersteinlab.org] (or, equivalently, [http://github.com/gersteinlab github.com/gersteinlab])
=Portals=
=Portals=
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|style="width:15%; text-align:center;"|[http://sv.gersteinlab.org/breakdb/ '''BreakDB''']||style="width:7%; text-align:center;"|2009||This database, which is part of the PEMer package, contains information about structural variants and associated breakpoints.
|style="width:15%; text-align:center;"|[http://sv.gersteinlab.org/breakdb/ '''BreakDB''']||style="width:7%; text-align:center;"|2009||This database, which is part of the PEMer package, contains information about structural variants and associated breakpoints.
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|style="width:15%; text-align:center;"|[http://resource.psychencode.org/ '''PsychENCODE resource''']||style="width:7%; text-align:center;"|2018||This website is a comprehensive functional genomic resource for the human brain from PsychENCODE Phase I, including all derived data, integrative models and links to raw data.
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|style="width:15%; text-align:center;"|[http://funseq.gersteinlab.org/ '''FunSeq''']<br>  - & -  <br>[http://funseq2.gersteinlab.org/ '''FunSeq2''']  [http://github.gersteinlab.org/FunSeq2/  Github] ||style="width:7%; text-align:center;"|2012<br>&<br>2013||These tools can be used to automatically score and annotate the disease-causing potential of SNVs, particularly those which are non-coding. FunSeq can detect recurrent annotation elements in non-coding regions when running with multiple personal genomes. FunSeq2 is an extension of FunSeq that provides a means of prioritizing somatic variants from cancer whole genome sequencing.
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|style="width:15%; text-align:center;"|[http://funseq.gersteinlab.org/ '''FunSeq''']<br>  - & -  <br>[http://funseq2.gersteinlab.org/ '''FunSeq2''']  [http://github.gersteinlab.org/FunSeq2/  Github] ||style="width:7%; text-align:center;"|2013<br>&<br>2014||These tools can be used to automatically score and annotate the disease-causing potential of SNVs, particularly those which are non-coding. FunSeq can detect recurrent annotation elements in non-coding regions when running with multiple personal genomes. FunSeq2 is an extension of FunSeq that provides a means of prioritizing somatic variants from cancer whole genome sequencing.
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|style="width:15%; text-align:center;"|[http://larva.gersteinlab.org/ '''LARVA'''] <br> [https://github.com/gersteinlab/LARVA Github repo] ||style="width:7%; text-align:center;"|2015||LARVA is a computational framework designed to facilitate the study of noncoding variants. It addresses issues that have made it difficult to derive an accurate model of the background mutation rates of noncoding elements in cancer genomes. LARVA integrates a comprehensive set of noncoding functional elements, modeling their mutation count with a beta-binomial distribution to handle overdispersion. Moreover, LARVA uses regional genomic features (such as replication timing) to better estimate local mutation rates and mutational enrichments.
|style="width:15%; text-align:center;"|[http://larva.gersteinlab.org/ '''LARVA'''] <br> [https://github.com/gersteinlab/LARVA Github repo] ||style="width:7%; text-align:center;"|2015||LARVA is a computational framework designed to facilitate the study of noncoding variants. It addresses issues that have made it difficult to derive an accurate model of the background mutation rates of noncoding elements in cancer genomes. LARVA integrates a comprehensive set of noncoding functional elements, modeling their mutation count with a beta-binomial distribution to handle overdispersion. Moreover, LARVA uses regional genomic features (such as replication timing) to better estimate local mutation rates and mutational enrichments.
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|style="width:15%; text-align:center;"|[http://vat.gersteinlab.org/ '''VAT'''] <br> [http://github.gersteinlab.org/vat/ Github repo] ||style="width:7%; text-align:center;"|2012|| A computational framework to functionally annotate variants in personal genomes using a cloud-computing environment.
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|style="width:15%; text-align:center;"|[http://aloft.gersteinlab.org/ '''ALoFT'''] <br> [https://github.com/gersteinlab/aloft Github repo] ||style="width:7%; text-align:center;"|2017|| A method to annotate and predict the disease-causing potential of loss-of-function variants.
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|style="width:15%; text-align:center;"|[http://moat.gersteinlab.org/ '''MOAT'''] <br> [https://github.com/gersteinlab/MOAT Github repo] ||style="width:7%; text-align:center;"|2017|| MOAT (Mutations Overburdening Annotations Tool) is a computational system for identifying significant mutation burdens in genomic elements with an empirical, nonparametric method. Taking a set of variant calls and a set of annotations, MOAT calculates which annotations have observed variant counts that are substantially elevated with respect to a distribution of expected variant counts determined by permutation of the input data.
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|style="width:15%; text-align:center;"|[http://github.gersteinlab.org/uORFs/ '''uORFs'''] <br> [https://github.com/gersteinlab/uORFs Github repo] ||style="width:7%; text-align:center;"|2018|| A catalog of predicted functional upstream open reading frames (uORFs) in humans.
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|style="width:15%; text-align:center;"|[https://github.com/gersteinlab/GRAM '''GRAM'''] <br> [https://github.com/gersteinlab/GRAM Github repo] ||style="width:7%; text-align:center;"|2019|| A GeneRAlized Model to predict the molecular effect of a non-coding variant in a cell type-specific manner. GRAM combines a universal regulatory score defined by transcription factor binding with an easily obtainable modifier defined by transcription factor binding and expression to reflect the particular cell type. To use GRAM, you need to provide a non-coding variant file in BED format and the whole genome expression file (see github repo for details).
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|style="width:15%; text-align:center;"|[http://vat.gersteinlab.org/ '''VAT'''] <br> [http://github.gersteinlab.org/vat/ Github repo] ||style="width:7%; text-align:center;"|2012|| A computational framework to functionally annotate variants in personal genomes using a cloud-computing environment.
 
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|style="text-align: center;"|[http://archive.gersteinlab.org/proj/rnaseq/rseqtools/ '''RSEQtools''']<br>[http://github.gersteinlab.org/RSEQtools/ Github repo]||style="text-align:center;"|2011||A suite of tools that use Mapped Read Format (MRF) for the analysis of RNA-Seq experiments. MRF is a compact data format that enables anonymization of confidential sequence information while maintaining the ability to conduct subsequent functional genomics studies. RSEQtools provides a suite of modules that convert to/from MRF data and perform common tasks such as calculating gene expression values, generating signal tracks of mapped reads, and segmenting that signal into actively transcribed regions.
|style="text-align: center;"|[http://archive.gersteinlab.org/proj/rnaseq/rseqtools/ '''RSEQtools''']<br>[http://github.gersteinlab.org/RSEQtools/ Github repo]||style="text-align:center;"|2011||A suite of tools that use Mapped Read Format (MRF) for the analysis of RNA-Seq experiments. MRF is a compact data format that enables anonymization of confidential sequence information while maintaining the ability to conduct subsequent functional genomics studies. RSEQtools provides a suite of modules that convert to/from MRF data and perform common tasks such as calculating gene expression values, generating signal tracks of mapped reads, and segmenting that signal into actively transcribed regions.
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|style="text-align: center;"|[https://github.com/gersteinlab/texp/blob/master/README.md '''TeXP''']<br>[https://github.com/gersteinlab/texp Github repo]||style="text-align:center;"|2019||TeXP accounts and removes the effects of pervasive transcription when quantifying LINE activity. Our method uses the broad distribution of LINEs to estimate the effects of pervasive transcription. Using TeXP, we processed thousands of transcriptome datasets to uniformly, and unbiasedly measure LINE-1 activity across healthy somatic cells.
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|style="width:15%; text-align:center;"|[http://archive.gersteinlab.org/proj/DynaSIN/index.html '''DynaSIN''']||style="width:7%; text-align:center;"|2011||The Dynamic Structure Interaction Network (DynaSIN) is a resource for studying protein-protein interaction networks in the context of conformational changes.
|style="width:15%; text-align:center;"|[http://archive.gersteinlab.org/proj/DynaSIN/index.html '''DynaSIN''']||style="width:7%; text-align:center;"|2011||The Dynamic Structure Interaction Network (DynaSIN) is a resource for studying protein-protein interaction networks in the context of conformational changes.
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|style="width:15%; text-align:center;"|[https://github.com/gersteinlab/OrthoClust '''OrthoClust''']||style="width:7%; text-align:center;"|2014||A computational framework that integrates the co-association networks of individual species by utilizing the orthology relationships of genes between species. It outputs optimized modules that are fundamentally cross-species, which can either be conserved or species-specific.
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|style="width:15%; text-align:center;"|[http://pubnet.gersteinlab.org/ '''PubNet''']||style="width:7%; text-align:center;"|2005||A web-based tool that extracts several types of relationships returned by PubMed queries and maps them on to networks, allowing for graphical visualization, textual navigation, and topological analysis.  
|style="width:15%; text-align:center;"|[http://pubnet.gersteinlab.org/ '''PubNet''']||style="width:7%; text-align:center;"|2005||A web-based tool that extracts several types of relationships returned by PubMed queries and maps them on to networks, allowing for graphical visualization, textual navigation, and topological analysis.  
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|style="width:15%; text-align:center;"|[http://stress.molmovdb.org/ '''STRESS'''] <br> [https://github.com/gersteinlab/STRESS Github repo] ||style="width:7%; text-align:center;"|2016||STRucturally-identified ESSential residues (STRESS) is a web tool that enables users to submit PDB-formatted protein structures to predict both surface- and interior-allosteric residues. The software behind this tool employs 3D structures to build models of protein conformational change in order to perform allosteric site predictions.
|style="width:15%; text-align:center;"|[http://stress.molmovdb.org/ '''STRESS'''] <br> [https://github.com/gersteinlab/STRESS Github repo] ||style="width:7%; text-align:center;"|2016||STRucturally-identified ESSential residues (STRESS) is a web tool that enables users to submit PDB-formatted protein structures to predict both surface- and interior-allosteric residues. The software behind this tool employs 3D structures to build models of protein conformational change in order to perform allosteric site predictions.
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|style="width:15%; text-align:center;"|[http://intensification.gersteinlab.org// '''Intensification'''] <br> [https://github.com/gersteinlab/Intensification Github repo] ||style="width:7%; text-align:center;"|2016||Intensification is a database that contains the results for 12 repeat protein domains, from the amplification of population-genetic signal by constructing a motif-based multiple sequence alignment (motif-MSA). We make use of the modular structure of repeat motifs to amplify signals of selection from population genetics and traditional inter-species conservation.
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Latest revision as of 16:14, 25 September 2019

The tools & resources listed below have been published and are actively maintained by the Gerstein lab. You may view a list of the associated literature here.

In addition to the tools below, the lab has also published a number of tools that are not currently being actively maintained.

You may also access tools that have not yet been published

Source code for all software is available on our Github page: Github.gersteinlab.org (or, equivalently, github.com/gersteinlab)

Contents

Portals

MolMovDB

NameDescription
File:Morph-icon.jpg‎
MolMovDB

Servers and a suite of accessory tools for the analysis of conformational changes in protein and nucleic acid structures.

Networks

NameDescription

Networks

The Gerstein lab has been a pioneer in applying network analysis to generate knowledge form large-scale experiments. To this end, we have developed a portal for our network research.

Pseudogene.org

NameDescription
File:pseudogene.png‎
Pseudogene.org
Pseudogene.org is a collection of resources related to our efforts to survey eukaryotic genomes for pseudogene sequences, "pseudo-fold" usage, amino-acid composition, and single-nucleotide polymorphisms (SNPs) to help elucidate the relationships between pseudogene families across several organisms.

Structural Variants (SV)

NameDescription

Structural Variants

Software that may be used to investigate Structural Variations (SVs) and Copy Number Variations (CNVs).

Data Sets

NameRelease DateDescription
BreakDB2009This database, which is part of the PEMer package, contains information about structural variants and associated breakpoints.
PsychENCODE resource2018This website is a comprehensive functional genomic resource for the human brain from PsychENCODE Phase I, including all derived data, integrative models and links to raw data.

Evolution

NameRelease DateDescription
Coevolution analysis of protein residues2008An integrated online system that enables comparative analyses of residue coevolution with a comprehensive set of commonly used scoring functions, including statistical coupling analysis (SCA), explicit likelihood of subset variation (ELSC), mutual information and correlation-based methods.

Genome Technology

Gene Regulation

NameRelease DateDescription
Loregic2015Loregic is a computational method integrating gene expression and regulatory network data, to characterize the logical cooperativity of regulatory factors. Loregic uses all 16 possible two-input-one-output logic gates (e.g. AND or XOR) to describe triplets of two factors regulating a common target, and finds the gate that best matches each triplet’s observed gene expression pattern across many conditions. Using human ENCODE ChIP-Seq and TCGA RNA-Seq data, we are able to demonstrate how Loregic characterizes complex circuits involving both proximally and distally regulating transcription factors (TFs) and also miRNAs.

Allele-Specific Effects

NameRelease DateDescription
AlleleDB2016AlleleDB is an online resource for storing and visualizing allele-specific binding (ASB) and gene expression (ASE). Using variants from the 1000-Genomes Project and RNA-seq and ChIP-seq data from related projects, this resource serves as a repository for the catalog of ASB and ASE variants, associated genomic elements and personal genomes used in the study. AlleleDB also interfaces with the UCSC browser for visualization of results.
AlleleSeq2011AlleleSeq is a computational pipeline that is used to study allele-specific expression (ASE) and allele specific binding (ASB). The pipeline first constructs a diploid personal genome sequence, then maps RNA-seq and ChIP-seq functional genomic data onto this personal genome. Consequently, locations in which there are differences in number of mapped reads between maternally- and paternally-derived sequences can be identified, thereby providing evidence for allele-specific events.

ChIP-Seq

NameRelease DateDescription
MUSIC
Github repo
2014

MUSIC is an algorithm for identification of enriched regions at multiple scales in the read depth signals from ChIP-Seq experiments.

PeakSeq
Github repo
2009 A tool for calling peaks corresponding to transcription factor binding sites from ChIP-Seq data scored against a matched control such as input DNA. PeakSeq employs a two-pass strategy in which putative binding sites are first identified in order to compensate for genomic variation in the 'mappability' of sequences, before a second pass filters out sites not significantly enriched compared to the normalized control, computing precise enrichments and significances.

Functional Annotation

NameRelease DateDescription
FunSeq
- & -
FunSeq2 Github
2013
&
2014
These tools can be used to automatically score and annotate the disease-causing potential of SNVs, particularly those which are non-coding. FunSeq can detect recurrent annotation elements in non-coding regions when running with multiple personal genomes. FunSeq2 is an extension of FunSeq that provides a means of prioritizing somatic variants from cancer whole genome sequencing.
LARVA
Github repo
2015LARVA is a computational framework designed to facilitate the study of noncoding variants. It addresses issues that have made it difficult to derive an accurate model of the background mutation rates of noncoding elements in cancer genomes. LARVA integrates a comprehensive set of noncoding functional elements, modeling their mutation count with a beta-binomial distribution to handle overdispersion. Moreover, LARVA uses regional genomic features (such as replication timing) to better estimate local mutation rates and mutational enrichments.
VAT
Github repo
2012 A computational framework to functionally annotate variants in personal genomes using a cloud-computing environment.
ALoFT
Github repo
2017 A method to annotate and predict the disease-causing potential of loss-of-function variants.
MOAT
Github repo
2017 MOAT (Mutations Overburdening Annotations Tool) is a computational system for identifying significant mutation burdens in genomic elements with an empirical, nonparametric method. Taking a set of variant calls and a set of annotations, MOAT calculates which annotations have observed variant counts that are substantially elevated with respect to a distribution of expected variant counts determined by permutation of the input data.
uORFs
Github repo
2018 A catalog of predicted functional upstream open reading frames (uORFs) in humans.
GRAM
Github repo
2019 A GeneRAlized Model to predict the molecular effect of a non-coding variant in a cell type-specific manner. GRAM combines a universal regulatory score defined by transcription factor binding with an easily obtainable modifier defined by transcription factor binding and expression to reflect the particular cell type. To use GRAM, you need to provide a non-coding variant file in BED format and the whole genome expression file (see github repo for details).

Microarrays & Proteomics

NameRelease DateDescription
MOTIPS2010MOTIPS employs an efficient search algorithm to scan a target proteome for potential domain targets and to increase the accuracy of each hit by integrating a variety of pre-computed features, such as conservation, surface propensity, and disorder.
PARE2007Protein Abundance and mRNA Expression (PARE) is a tool for comparing protein abundance and mRNA expression data. In addition to globally comparing the quantities of protein and mRNA, PARE allows users to select subsets of proteins for focused study (based on functional categories and complexes). Furthermore, it highlights correlation outliers, which may warrant further investigation.

RNA-Seq

NameRelease DateDescription
ACT2011The aggregation and correlation toolbox (ACT) is an efficient, multifaceted toolbox for analyzing continuous signal and discrete region tracks from high-throughput genomic experiments, such as RNA-seq or ChIP-chip signal profiles from the ENCODE and modENCODE projects, or lists of single nucleotide polymorphisms from the 1000 genomes project.
FusionSeq
Github repo
2010FusionSeq may be used to identify fusion transcripts from paired-end RNA-sequencing. FusionSeq includes filters to remove spurious candidate fusions with artifacts, such as misalignment or random pairing of transcript fragments, and it ranks candidates according to several statistics. It also includes a module to identify exact sequences at breakpoint junctions.
IQseq
Github repo
2012A tool for isoform quantification with RNA-seq data. Given isoform annotation and alignment of RNA-seq reads, it will use an EM algorithm to infer the most probable expression level for each isoform of a gene.
RSEQtools
Github repo
2011A suite of tools that use Mapped Read Format (MRF) for the analysis of RNA-Seq experiments. MRF is a compact data format that enables anonymization of confidential sequence information while maintaining the ability to conduct subsequent functional genomics studies. RSEQtools provides a suite of modules that convert to/from MRF data and perform common tasks such as calculating gene expression values, generating signal tracks of mapped reads, and segmenting that signal into actively transcribed regions.
TeXP
Github repo
2019TeXP accounts and removes the effects of pervasive transcription when quantifying LINE activity. Our method uses the broad distribution of LINEs to estimate the effects of pervasive transcription. Using TeXP, we processed thousands of transcriptome datasets to uniformly, and unbiasedly measure LINE-1 activity across healthy somatic cells.

Structural Variation

NameRelease DateDescription
AGE
(citation)
2011 AGE is used for defining breakpoints of genomic structural variants at single-nucleotide resolution, using optimal alignments with gap excision.
CNVnator
(citation)
2011 CNVnator may be used to discover, genotype, and characterize typical and atypical CNVs from familial and population genome sequencing.

Networks

NameRelease DateDescription
DynaSIN2011The Dynamic Structure Interaction Network (DynaSIN) is a resource for studying protein-protein interaction networks in the context of conformational changes.
OrthoClust2014A computational framework that integrates the co-association networks of individual species by utilizing the orthology relationships of genes between species. It outputs optimized modules that are fundamentally cross-species, which can either be conserved or species-specific.
PubNet2005A web-based tool that extracts several types of relationships returned by PubMed queries and maps them on to networks, allowing for graphical visualization, textual navigation, and topological analysis.
TopNet2004TopNet is an automated web tool designed compare the topologies of sub-networks, looking for global differences associated with different types of proteins. This automated web tool designed to address this question, calculating and comparing topological characteristics for different sub-networks derived from any given protein network.
tYNA2006(TopNet-like Yale Network Analyzer). A Web system for managing, comparing and mining multiple networks, both directed and undirected. tYNA efficiently implements methods that have proven useful in network analysis, including identifying defective cliques, finding small network motifs (such as feed-forward loops), calculating global statistics (such as the clustering coefficient and eccentricity), and identifying hubs and bottlenecks etc.

Structure and Macromolecular Motions

NameRelease DateDescription
3V2010

The 3V web server extracts and comprehensively analyzes the internal volumes of input RNA and protein structures. It identifies internal volumes by taking the difference between two rolling-probe solvent-excluded surfaces.

HIT2006The Helix Interaction Tool (HIT) is a comprehensive package for analyzing helix-helix packing in proteins. This enables the user to obtain quantitative measures of the helix interaction surface area and helix crossing angle, as well as several methods for visualizing the helical interaction.
Macromolecular Geometry and Packing Tools1994-2009A number of programs for calculating properties of protein and nucleic acid structures have been collected into a single distribution. Included is a library functions for analyzing structures, a convenient interactive command-line interpreter, and software for the calculation of geometrical quantities associated with macromolecular structures and their motions.
Morph Server2000A web server for generating and viewing models of protein conformational change using interpolation with energy minimization. The user may opt to use either single- or multi-chain proteins as input.
STRESS
Github repo
2016STRucturally-identified ESSential residues (STRESS) is a web tool that enables users to submit PDB-formatted protein structures to predict both surface- and interior-allosteric residues. The software behind this tool employs 3D structures to build models of protein conformational change in order to perform allosteric site predictions.
Intensification
Github repo
2016Intensification is a database that contains the results for 12 repeat protein domains, from the amplification of population-genetic signal by constructing a motif-based multiple sequence alignment (motif-MSA). We make use of the modular structure of repeat motifs to amplify signals of selection from population genetics and traditional inter-species conservation.

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