MendeLIMS 3.2 – Laboratory Information Management System for Clinical Genome Sequencing

MendeLIMS 3.2

:: DESCRIPTION

MendeLIMS is a laboratory information management system (LIMS) that is adaptable to continuously evolving experimental protocols and sequencing technologies. Large clinical genomics studies require the ability to select from a large population of patients/samples to identify the samples of interest. Samples must be accurately tracked through various transformations in order to be certain that DNA sequencing results are attributable to the correct originating sample. This web-based LIMS has a flexible configuration, is easily implemented with open source tools and can be tooled for large scale management of next generation DNA

::DEVELOPER

Ji Research Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • MacOsX / Linux
  • Web Server
  • rails 2.3.x and ruby 1.8.7
  • MySQL

:: DOWNLOAD

 MendeLIMS

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2014 Aug 27;15:290. doi: 10.1186/1471-2105-15-290.
MendeLIMS: a web-based laboratory information management system for clinical genome sequencing.
Grimes SM, Ji HP

MISO 0.2.195 – Managing Information for Sequencing Operations

MISO 0.2.195

:: DESCRIPTION

MISO is a new open-source Lab Information Management System (LIMS) under development at TGAC, specifically designed for tracking next-generation sequencing experiments.

::DEVELOPER

the Earlham Institute.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 MISO

:: MORE INFORMATION

PaSS – A PacBio Sequencing Simulator

PaSS

:: DESCRIPTION

PaSS is a fast sequencing simulator for PacBio sequencing with a high fidelity. It will facilitate the evaluation and development of new analysis tools for the PacBio sequencing data.

::DEVELOPER

Dr. Chaochun Wei

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Perl

:: DOWNLOAD

PaSS

:: MORE INFORMATION

Citation:

BMC Bioinformatics. 2019 Jun 21;20(1):352. doi: 10.1186/s12859-019-2901-7.
PaSS: a sequencing simulator for PacBio sequencing.
Zhang W, Jia B, Wei C

LongISLND 0.9.5 – In silico Sequencing of Lengthy and Noisy Datatypes

LongISLND 0.9.5

:: DESCRIPTION

LongISLND is a read simulator which profiles the characteristics of third generation, single-molecule sequencing technologies and simulates accordingly.

::DEVELOPER

Roche Sequencing Solutions

:: SCREENSHOTS

N/a

:: REQUIREMENTS

  • Linux
  • Python
  • Java
  • Maven

:: DOWNLOAD

LongISLND

:: MORE INFORMATION

Citation

LongISLND: in silico sequencing of lengthy and noisy datatypes.
Lau B, Mohiyuddin M, Mu JC, Fang LT, Bani Asadi N, Dallett C, Lam HY.
Bioinformatics. 2016 Dec 15;32(24):3829-3832. Epub 2016 Sep 25.

MethGo – Analyzing Whole-genome Bisulfite Sequencing data

MethGo

:: DESCRIPTION

MethGo is a simple and effective tool designed for the analysis of data from whole genome bisulfite sequencing (WGBS) and reduced representation bisulfite sequencing (RRBS).

::DEVELOPER

Pao-Yang Chen’s Laboratory 

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

 MethGo

:: MORE INFORMATION

Citation

MethGo: a comprehensive tool for analyzing whole-genome bisulfite sequencing data.
Liao WW, Yen MR, Ju E, Hsu FM, Lam L, Chen PY.
BMC Genomics. 2015 Dec 9;16 Suppl 12:S11. doi: 10.1186/1471-2164-16-S12-S11.

secureSeq – Secure Sequencing Analysis Tools

secureSeq

:: DESCRIPTION

secureSeq is a suite of secure sequencing analysis tools

::DEVELOPER

HCBravo Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 secureSeq

:: MORE INFORMATION

Citation

Privacy-Preserving Microbiome Analysis Using Secure Computation.
Wagner J, Paulson JN, Wang X, Bhattacharjee B, Bravo HC.
Bioinformatics. 2016 Feb 11. pii: btw073.

FILTUS 1.0.5 – Analysis of Exome Sequencing data

FILTUS 1.0.5

:: DESCRIPTION

FILTUS is a stand-alone tool for downstream analysis in high-throughput sequencing projects. It is especially well suited for identification of variants causing Mendelian disease.

::DEVELOPER

Magnus Dehli Vigeland, PhD

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / MacOsX/ Windows
  • Python

:: DOWNLOAD

  FILTUS

:: MORE INFORMATION

Citation

FILTUS: a desktop GUI for fast and efficient detection of disease-causing variants, including a novel autozygosity detector.
Vigeland MD, Gjøtterud KS, Selmer KK.
Bioinformatics. 2016 Jan 27. pii: btw046.

GIPS 1.7 – Gene Identification via Phenotype Sequencing

GIPS 1.7

:: DESCRIPTION

GIPS software considers a range of experimental and analysis choices in sequencing-based forward genetics studies within an integrated probabilistic framework, which enables direct gene cloning from the sequencing of several unrelated mutants of the same phenotype without the need to create segregation populations.

::DEVELOPER

GIPS team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  •  Linux / WIndows/ MacOsX
  • Java

:: DOWNLOAD

 GIPS

:: MORE INFORMATION

Citation

GIPS: A Software Guide to Sequencing-based Direct Gene Cloning in Forward Genetics Studies.
Hu H, Wang W, Zhu Z, Zhu J, Tan D, Zhou Z, Mao C, Chen X.
Plant Physiol. 2016 Feb 3. pii: pp.01327.2015.

Resilience – Scan Sequencing or Genotyping Data for Potential unexpected Heroes

Resilience

:: DESCRIPTION

The Resilience Project aims at finding individuals with rare genetic mutations that the medical text books would indicate should have caused catastrophic illness but somehow these individuals are “resilient” – they have been protected via yet to be discovered genetic or environmental factors.

::DEVELOPER

Rong Chen Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows
  • JAVE

:: DOWNLOAD

 Resilience

:: MORE INFORMATION

HPG pore – Framework for Nanopore Sequencing data

HPG pore

:: DESCRIPTION

HPG Pore is a toolkit to explore and analyze nanopore sequencing data that can run both on a single computer and on the Hadoop distributed computing framework.

::DEVELOPER

HPG pore team

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  •  Linux

:: DOWNLOAD

 HPG pore

:: MORE INFORMATION

Citation:

HPG pore: an efficient and scalable framework for nanopore sequencing data.
Tarraga J, Gallego A, Arnau V, Medina I, Dopazo J.
BMC Bioinformatics. 2016 Feb 27;17(1):107. doi: 10.1186/s12859-016-0966-0.