SODa – SuperOxide Dismutase Annotation Tool

SODa

:: DESCRIPTION

The SODa webtool predicts if a target sequence corresponds to an Fe/Mn Superoxide dismutases (SODs) .

::DEVELOPER

Service de Biomodélisation, Bioinformatique et Bioprocédés (3BIO)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2008 Jun 2;9:257. doi: 10.1186/1471-2105-9-257.
SODa: an Mn/Fe superoxide dismutase prediction and design server.
Kwasigroch JM1, Wintjens R, Gilis D, Rooman M.

UROPA 3.1.0 – Universal RObust Peak Annotation

UROPA 3.1.0

:: DESCRIPTION

UROPA is a command line based tool, intended for universal genomic range annotation. Based on a configuration file, different target features can be prioritized with multiple integrated queries. These can be sensitive for feature type, distance, strand specificity, feature attributes (e.g. protein_coding) or anchor position relative to the feature.

::DEVELOPER

the Loosolab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

UROPA

:: MORE INFORMATION

Citation:

Kondili M, Fust A, Preussner J, Kuenne C, Braun T, Looso M.
UROPA: a tool for Universal RObust Peak Annotation.
Scientific Reports. 2017;7:2593. doi:10.1038/s41598-017-02464-y.

diHMM v0.1 beta – multi-scale Chromatin State Annotation from ChIPseq data

diHMM v0.1 beta

:: DESCRIPTION

diHMM (Hierarchical Hidden Markov Model) is a novel computational method for finding chromatin states at multiple scales. The model takes as input a multidimensional set of histone modifications for several cell types and classifies the genome into a preselected number of nucleosome-level and domain-level hidden states.

::DEVELOPER

Guo-CHeng Yuan Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/Windows/MacOsX
  • Matlab

:: DOWNLOAD

diHMM

:: MORE INFORMATION

Citation

Marco E, Meuleman W, Huang J, Glass K, Pinello L, Wang J, Kellis M, Yuan GC.
Multi-scale chromatin state annotation using a hierarchical hidden Markov model.
Nature Communications. 2017 Apr 7;8:15011.

ASAP 1.4.1 – A Systematic Annotation Package for Community Analysis of Genomes

ASAP 1.4.1

:: DESCRIPTION

ASAP is designed to organize the data associated with a genome from the early stages of sequence annotation through genetic and biochemical characterization, providing a vehicle for ongoing updates of the annotation and a repository for genome-scale experimental data.

::DEVELOPER

Genome Evolution Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows/ Linux / Mac OsX
  • PHP
  • MySQL

:: DOWNLOAD

 ASAP

:: MORE INFORMATION

Citation

Nucleic Acids Res. 2003 Jan 1;31(1):147-51.
ASAP, a systematic annotation package for community analysis of genomes.
Glasner JD1, Liss P, Plunkett G 3rd, Darling A, Prasad T, Rusch M, Byrnes A, Gilson M, Biehl B, Blattner FR, Perna NT.

CRISPRdigger 1.007 – Detecting CRISPRs with better direct Repeat Annotations

CRISPRdigger 1.007

:: DESCRIPTION

CRISPRdigger is a de novo CRISPR detection program which could identify more truncated DR and has higher accuracy and more contents in the test genomes compared with the present other tools-CRISPRFinder[1], CRT[2] and PILER-CR[3].

::DEVELOPER

Health Informatics Lab (HILab)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ MacOsX
  • Perl

:: DOWNLOAD

 CRISPRdigger

:: MORE INFORMATION

Citation

Sci Rep. 2016 Sep 6;6:32942. doi: 10.1038/srep32942.
CRISPRdigger: detecting CRISPRs with better direct repeat annotations.
Ge R, Mai G, Wang P, Zhou M, Luo Y, Cai Y, Zhou F

scds 1.2.0 – In-Silico Annotation of Doublets for Single Cell RNA Sequencing Data

scds 1.2.0

:: DESCRIPTION

scds (single cell doublet scoring) is a software of computational doublet prediction for single cell RNA sequencing data

::DEVELOPER

Kostka Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux / MacOsX
  • BioConductor

:: DOWNLOAD

scds

:: MORE INFORMATION

Citation

Bioinformatics. 2019 Sep 10. pii: btz698. doi: 10.1093/bioinformatics/btz698.
scds: Computational Annotation of Doublets in Single-Cell RNA Sequencing Data.
Bais AS, Kostka D.

MOAT v1.0 – Mutations Overburdening Annotations Tool

MOAT v1.0

:: DESCRIPTION

MOAT 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.

::DEVELOPER

Gerstein Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

MOAT 

:: MORE INFORMATION

Citation:

Bioinformatics. 2018 Mar 15;34(6):1031-1033. doi: 10.1093/bioinformatics/btx700.
MOAT: efficient detection of highly mutated regions with the Mutations Overburdening Annotations Tool.
Lochovsky L, Zhang J, Gerstein M.

ALoFT 1.0 – Annotation of Loss-of-Function Transcripts

ALoFT 1.0

:: DESCRIPTION

ALoFT provides extensive annotations to putative loss-of-function variants (LoF) in protein-coding genes including functional, evolutionary and network features. Further, ALoFT can predict the impact of premature stop variants and classify them as dominant disease-causing, recessive disease-causing and benign variants.

::DEVELOPER

Gerstein Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

ALoFT

:: MORE INFORMATION

Citation:

Nat Commun. 2017 Aug 29;8(1):382. doi: 10.1038/s41467-017-00443-5.
Using ALoFT to determine the impact of putative loss-of-function variants in protein-coding genes.
Balasubramanian S, Fu Y, Pawashe M, McGillivray P, Jin M, Liu J, Karczewski KJ, MacArthur DG, Gerstein M

LARVA – Large-scale Analysis of Variants in noncoding Annotations

LARVA

:: DESCRIPTION

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.

::DEVELOPER

Gerstein Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

LARVA

:: MORE INFORMATION

Citation:

LARVA: an integrative framework for large-scale analysis of recurrent variants in noncoding annotations.
Lochovsky L, Zhang J, Fu Y, Khurana E, Gerstein M.
Nucleic Acids Res. 2015 Sep 30;43(17):8123-34. doi: 10.1093/nar/gkv803.

SCALOP – Sequence-based antibody CAnonical LOoP structure annotation

SCALOP

:: DESCRIPTION

SCALOP is a sequence-based canonical form predictor for five of the six complementarity-determining regions (H1, H2, L1, L2 and L3) on an antibody.

::DEVELOPER

the Oxford Protein Informatics Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • MacOs/ Linux

:: DOWNLOAD

SCALOP

:: MORE INFORMATION

Citation

SCALOP: sequence-based antibody canonical loop structure annotation.
Wong WK, Georges G, Ros F, Kelm S, Lewis AP, Taddese B, Leem J, Deane CM.
Bioinformatics. 2019 May 15;35(10):1774-1776. doi: 10.1093/bioinformatics/bty877.