BOL: Related items

Bioinformatics tools to detect horizontal gene transfer (HGT) in genomes

Jit — Fri, 02 Mar 2018 04:56:23 -0600

Horizontal gene transfer (HGT), the “non-sexual movement of genetic material between two organisms” , is relatively common in prokaryotes and single-celled eukaryotes, but a number of factors combine to make it far rarer in multicellular eukaryotes. In order for a eukaryotic species to gain a gene by HGT, foreign DNA must enter the host nucleus, integrate into the genome, and in more complex organisms it must enter the sequestered germline in order to be transmitted to offspring. Once there, it must not experience strong negative selection, despite potential for genetic incompatibility with the host genome and mismatch between the niche of the donor and the host. Over the longer term, foreign DNA may become “domesticated” in the recipient genome and provide novel function.

Following are the popular tool to detect HGT in genomes:

T-REX / 3.22

HGT detection / download & compile

20525630

RANGER-DTL / 2.0

HGT detection / download binary

22689773

PhyloNet / 3.6.1

HGT detection / download binary

18662388

Jane / 4.01

HGT detection / download binary (!license!)

20181081

TREE-PUZZLE / 5.3.rc16

HGT detection / download & compile

11934758

CONSEL / 0.20

HGT detection / download

11751242

DarkHorse / 1.5 rev170

HGT detection / download & install

17274820

HGTector / 0.2.1

HGT detection / git clone

25159222

EGID / 1.0

HGT detection / download

22355228

GeneMarkS / 4.30

HGT detection / download binary (!license!)

9461475

Big genomic data on Google Cloud Platform

Fri, 17 Oct 2014 02:16:00 -0500

As the cost of DNA sequencing has dropped, the volume of data produced has risen into the petabytes. Google is working with the genomics community to define a standard API for working with big genomic data sets in the cloud. Building on Google Cloud Platform, we show how to store, process, explore and share genomic data using technologies like BigQuery, AppEngine MapReduce, R and more.

Ligand Docking Tools and Software !

Poonam Mahapatra — Wed, 25 Apr 2018 05:05:17 -0500

Ligand docking referred to cases where small molecule (“ligand”) is being docked into much larger macromolecule ("target"). The following is partial list of docking software, focusing on free (at least for academic institutes) and/or popular docking tools.

AutoDock

Stochastic (GA)

Flexible ligand and partially flexible target

ArgusLab

Systematic

Flexible ligandX-Score based

DOCK

Systematic (IC)

Flexible ligandDOCK 3.5 (force field)

eHITS

Systematic (RBD of fragments followed by reconstruction)Flexible ligand and partially flexible targetHiTS_Score (empirical)

FlexX

Systematic (IC)Flexible ligandFlexX SF (empirical)Commercial

FLIPDock

Stochastic (GA)Flexible ligand and flexible targetAUTODOCK (empirical)

FRED

Systematic (RBD)Flexible ligandChemScore, PLP, ScreenScore, ChemGauss (empirical/consensus)

GOLD

Stochastic (GA)

Flexible ligand and partially flexible targetGoldScore, ChemScore (empirical), ASP (knowledge based)

ICM

Stochastic (MC)

Flexible ligand and partially flexible targetICM SF (empirical)

ParDOCK

Stochastic (MC)

RigidBAPPL (empirical)

PLANTS

Stochastic (ACO)Flexible ligand and partially flexible target

CHEMPLP, PLP (empirical)

Surflex

Systematic (IC/MA)Flexible ligandHammerhead based (empirical)

Point to note:

Several studies have shown that the performance of most docking tools is highly dependent on the particular characteristics of both the binding site and the ligand to be investigated, and the determination which method would be more suitable in a specific context is difficult. We encouraged you to check several docking methods to determine which one(s) work best for your system.

CLUSTER INNOVATION CENTER @ UNIVERSITY OF DELHI

Wed, 22 Oct 2014 10:39:49 -0500

Applications for Pre-selection of candidates under ‘Institutions Mode’ for DST-ISPIRE Faculty in Computational Biology/ Systems Biology/ Bioinformatics

Applications are invited for pre-selection of candidates for Ministry of Science and Technology, Department of Science and Technology INSPIRE Faculty Scheme: a component of “Assured Opportunity for Research Career (AORC)” under INSPIRE in the area of computational Biology/Systems Biology/Bioinformatics.

Candidates having done their B.Tech/B.E. and or M.Sc./M.Tech in Computer Science or Biotechnology and Ph.D. in Systems/ Computational Biology or Bioinformatics may apply in the following format prescribed by DST to the Director, Cluster Innovation Center, University Stadium, GC Narang Marg, University of Delhi, Delhi -11107. Detials of other qualification, age limits etc., please visit www.inspire-dst.gov.in.

Application on the prescribed format may be submitted by email to director@cic.du.ac.in before October 25, 2014. Selected candidates shall be called for an interview. The date, time and venue of the interview shall be informed by email/telephone. For more information about Cluster Innovation Center, please visit https://ducic.ac.in.

Scallop: reference-based transcriptome assembler for RNA-seq

Rahul Nayak — Tue, 08 May 2018 04:23:27 -0500

Scallop is an accurate reference-based transcript assembler. Scallop features its high accuracy in assembling multi-exon transcripts as well as lowly expressed transcripts. Scallop achieves this improvement through a novel algorithm that can be proved preserving all phasing paths from reads and paired-end reads, while also achieves both transcripts parsimony and coverage deviation minimization.

Scallop paper has been published at Nature Biotechnology. The datasets and scripts used in this paper to compare the performance of Scallop and other assemblers are available at scalloptest.

Please also checkout the podcast about Scallop (thanks Roman Cheplyaka for the interview). It is available at both the bioinformatics chat and iTunes.

https://github.com/Kingsford-Group/scallop

Address of the bookmark: https://github.com/Kingsford-Group/scallop

IPython: Interactive notebooks

Rahul Nayak — Fri, 07 Nov 2014 12:07:02 -0600

The IPython Notebook is a web-based interactive computational environment where you can combine code execution, text, mathematics, plots and rich media into a single document.

These notebooks are normal files that can be shared with colleagues, converted to other formats such as HTML or PDF, etc. You can share any publicly available notebook by using the IPython Notebook Viewer service which will render it as a static web page. This makes it easy to give your colleagues a document they can read immediately without having to install anything.

To learn more about using the IPython Notebook, you can visit our example collection, and you can read the documentation for all the details on how to use and configure the system. The Notebook Gallery showcases many interesting notebooks covering a variety of topics, from basic programming to advanced scientific computing.

More http://www.nature.com/news/interactive-notebooks-sharing-the-code-1.16261

http://ipython.org/ipython-doc/1/interactive/notebook.html

Reference http://ipython.org/notebook.html

gapFinisher: A reliable gap filling pipeline for SSPACE-LongRead scaffolder output

Rahul Nayak — Fri, 24 Jan 2020 06:04:40 -0600

gapFinisher is based on the controlled use of a previously published gap filling tool FGAP and works on all standard Linux/UNIX command lines. They compare the performance of gapFinisher against two other published gap filling tools PBJelly and GMcloser.

gapFinisher can fill gaps in draft genomes quickly and reliably.

Address of the bookmark: https://github.com/kammoji/gapFinisher

Tools for Differential expression analysis

Abhi — Tue, 08 Nov 2022 03:40:33 -0600

apeglm - https://bioconductor.org/packages/release/bioc/html/apeglm.html

ashr - https://github.com/stephens999/ashr, https://cran.r-project.org/web/packages/ashr/index.html

consensusDE - https://bioconductor.org/packages/release/bioc/html/consensusDE.html

DESeq2 - https://bioconductor.org/packages/release/bioc/html/DESeq2.html

edgeR - https://bioconductor.org/packages/release/bioc/html/edgeR.html

limma - https://kasperdanielhansen.github.io/genbioconductor/html/limma.html https://bioconductor.org/packages/release/bioc/html/limma.html

MetaCycle - https://cran.r-project.org/web/packages/MetaCycle/index.html, https://github.com/gangwug/MetaCycle

RUVSeq - https://bioconductor.org/packages/release/bioc/html/RUVSeq.html

SARTools - https://github.com/PF2-pasteur-fr/SARTools

tximport - https://github.com/mikelove/tximport

NIAB Molecular Biology/Bioinformatics Scientist/RA Openings

Thu, 13 Nov 2014 13:37:27 -0600

D. No. 1-121/1, 4th and 5th Floors, Axis Clinicals Building, Miyapur, Hyderabad, Telangana, India- 500 049

Email: admin@niab.org.in Telephones: +91 40 2304 9403 Telefax: +91 40 2304 2740
Advertisement No: 5/2014

About NIAB National Institute of Animal Biotechnology (NIAB), Hyderabad, an autonomous institute under the aegis of Department of Biotechnology, Government of India, is aimed to harness novel and emerging biotechnologies and create knowledge in the cutting edge areas for improving animal health and productivity.

Applications are invited for the following temporary research positions to work in ongoing DBTBBSRC sponsored research project entitled “Transcriptome Analysis in Indian buffalo and the Genetics of Innate Immunity” at the National Institute of Animal Biotechnology, Hyderabad.

(A) Project Scientist – Level B (One Position)

Emoluments: Rs. 15600 + GP Rs. 5400 + 30 % HRA p.m. (Total emoluments will be Rs. 49,770/-p.m. for the duration of the project)

Essential Qualification: Candidates having M.V.Sc. in Veterinary Microbiology / Veterinary Pathology / Veterinary Public Health / Ph.D. degree in Life Sciences, Biotechnology, Molecular Biology or any other related field from the recognized university are eligible to apply.

The candidate should have a good academic record and research experience as evidenced from published in standard referred journals / patents.

Desirable: Candidates having research experience in the area of tissue culture, genomics, Transcriptomics and Advanced Molecular Biology will be given preference.

Age Limit: Not exceeding 30 years as on last date of the submission of the application.

(B) Research Associate in Bioinformatics (One position)

Fellowship: Rs. 22,000 + 30 % HRA

Essential Qualification: Candidates having Ph.D. degree or M.Tech. with three years of
experience in Bioinformatics, Computational Biology, Biotechnology, Life Sciences or any other related field are eligible to apply.

Desirable: Candidate having research experience in the area of next generation sequencing (NGS) data analysis, Genome wide association studies, Genomic selection, advance genomic data analysis etc., will be given preference. The candidate should have a good academic record and research experience as evidenced from published papers in standard journals / patents.

Age Limit: Not exceeding 30 years as on last date of the submission of the application.

Project Duration: The duration of the project is Three years and the positions are co- terminus with the duration of the project. (Initial appointment will be for one year and further extension will be granted based on annual review).

Mode of submission of application: Only online applications are to be submitted through
www.niab.org.in on or before 08 December, 2014. Link for online submission of applications will be available from 10 November 2014.

Advertisement: www.niab.org.in/Notifications/Advt_5_2014/Advt_5_2014.pdf

List of bioinformatics workflow management tools !

Rahul Nayak — Sat, 20 Mar 2021 00:15:25 -0500

Here are list of Workflow Managers

BigDataScript – A cross-system scripting language for working with big data pipelines in computer systems of different sizes and capabilities. [ paper-2014 | web ]
Bpipe – A small language for defining pipeline stages and linking them together to make pipelines. [ web ]
Common Workflow Language – a specification for describing analysis workflows and tools that are portable and scalable across a variety of software and hardware environments, from workstations to cluster, cloud, and high performance computing (HPC) environments. [ web ]
Cromwell – A Workflow Management System geared towards scientific workflows. [ web ]
Galaxy – a popular open-source, web-based platform for data intensive biomedical research. Has several features, from data analysis to workflow management to visualization tools. [ paper-2018 | web ]
Nextflow (recommended) – A fluent DSL modelled around the UNIX pipe concept, that simplifies writing parallel and scalable pipelines in a portable manner. [ paper-2018 | web ]
Ruffus – Computation Pipeline library for python widely used in science and bioinformatics. [ paper-2010 | web ]
SeqWare – Hadoop Oozie-based workflow system focused on genomics data analysis in cloud environments. [ paper-2010 | web ]
Snakemake – A workflow management system in Python that aims to reduce the complexity of creating workflows by providing a fast and comfortable execution environment. [ paper-2018 | web ]
Workflow Descriptor Language – Workflow standard developed by the Broad. [ web ]