BOL: Related items

Cheatsheet for Linux !!

Jit — Wed, 22 Jun 2016 07:55:06 -0500

Linux Commands Cheat Sheet

    File System

    ls — list items in current directory

    ls -l — list items in current directory and show in long format to see perimissions, size, an modification date

    ls -a — list all items in current directory, including hidden files

    ls -F — list all items in current directory and show directories with a slash and executables with a star

    ls dir — list all items in directory dir

    cd dir — change directory to dir

    cd .. — go up one directory

    cd / — go to the root directory

    cd ~ — go to to your home directory

    cd - — go to the last directory you were just in

    pwd — show present working directory

    mkdir dir — make directory dir

    rm file — remove file

    rm -r dir — remove directory dir recursively

    cp file1 file2 — copy file1 to file2

    cp -r dir1 dir2 — copy directory dir1 to dir2 recursively

    mv file1 file2 — move (rename) file1 to file2

    ln -s file link — create symbolic link to file

    touch file — create or update file

    cat file — output the contents of file

    less file — view file with page navigation

    head file — output the first 10 lines of file

    tail file — output the last 10 lines of file

    tail -f file — output the contents of file as it grows, starting with the last 10 lines

    vim file — edit file

    alias name 'command' — create an alias for a command
    System

    shutdown — shut down machine

    reboot — restart machine

    date — show the current date and time

    whoami — who you are logged in as

    finger user — display information about user

    man command — show the manual for command

    df — show disk usage

    du — show directory space usage

    free — show memory and swap usage

    whereis app — show possible locations of app

    which app — show which app will be run by default
    Process Management

    ps — display your currently active processes

    top — display all running processes

    kill pid — kill process id pid

    kill -9 pid — force kill process id pid
    Permissions

    ls -l — list items in current directory and show permissions

    chmod ugo file — change permissions of file to ugo - u is the user's permissions, g is the group's permissions, and o is everyone else's permissions. The values of u, g, and o can be any number between 0 and 7.

    7 — full permissions

    6 — read and write only

    5 — read and execute only

    4 — read only

    3 — write and execute only

    2 — write only

    1 — execute only

    0 — no permissions

    chmod 600 file — you can read and write - good for files

    chmod 700 file — you can read, write, and execute - good for scripts

    chmod 644 file — you can read and write, and everyone else can only read - good for web pages

    chmod 755 file — you can read, write, and execute, and everyone else can read and execute - good for programs that you want to share
    Networking

    wget file — download a file

    curl file — download a file

    scp user@host:file dir — secure copy a file from remote server to the dir directory on your machine

    scp file user@host:dir — secure copy a file from your machine to the dir directory on a remote server

    scp -r user@host:dir dir — secure copy the directory dir from remote server to the directory dir on your machine

    ssh user@host — connect to host as user

    ssh -p port user@host — connect to host on port as user

    ssh-copy-id user@host — add your key to host for user to enable a keyed or passwordless login

    ping host — ping host and output results

    whois domain — get information for domain

    dig domain — get DNS information for domain

    dig -x host — reverse lookup host

    lsof -i tcp:1337 — list all processes running on port 1337
    Searching

    grep pattern files — search for pattern in files

    grep -r pattern dir — search recursively for pattern in dir

    grep -rn pattern dir — search recursively for pattern in dir and show the line number found

    grep -r pattern dir --include='*.ext — search recursively for pattern in dir and only search in files with .ext extension

    command | grep pattern — search for pattern in the output of command

    find file — find all instances of file in real system

    locate file — find all instances of file using indexed database built from the updatedb command. Much faster than find

    sed -i 's/day/night/g' file — find all occurrences of day in a file and replace them with night - s means substitude and g means global - sed also supports regular expressions
    Compression

    tar cf file.tar files — create a tar named file.tar containing files

    tar xf file.tar — extract the files from file.tar

    tar czf file.tar.gz files — create a tar with Gzip compression

    tar xzf file.tar.gz — extract a tar using Gzip

    gzip file — compresses file and renames it to file.gz

    gzip -d file.gz — decompresses file.gz back to file
    Shortcuts

    ctrl+a — move cursor to beginning of line

    ctrl+f — move cursor to end of line

    alt+f — move cursor forward 1 word

    alt+b — move cursor backward 1 word

A5-miseq

Jit — Thu, 18 Aug 2016 04:05:23 -0500

_A5-miseq_ is a pipeline for assembling DNA sequence data generated on the Illumina sequencing platform. This README will take you through the steps necessary for running _A5-miseq_.

Point to note:

There are many situations where A5-miseq is not the right tool for the job. In order to produce accurate results, A5-miseq requires Illumina data with certain characteristics. A5-miseq will likely not work well with Illumina reads shorter than around 80nt, or reads where the base qualities are low in all or most reads before 60nt. A5-miseq assumes it is assembling homozygous haploid genomes. Use a different assembler for metagenomes and heterozygous diploid or polyploid organisms. Use a different assembler if a tool like FastQC reports your data quality is dubious. You have been warned! Datasets consisting solely of unpaired reads are not currently supported.

Address of the bookmark: https://sourceforge.net/projects/ngopt/

Kraken: ultrafast metagenomic sequence classification using exact alignments

Jit — Mon, 27 Jun 2016 11:01:44 -0500

Kraken is an ultrafast and highly accurate program for assigning taxonomic labels to metagenomic DNA sequences. Previous programs designed for this task have been relatively slow and computationally expensive, forcing researchers to use faster abundance estimation programs, which only classify small subsets of metagenomic data. Using exact alignment of k-mers, Kraken achieves classification accuracy comparable to the fastest BLAST program. In its fastest mode, Kraken classifies 100 base pair reads at a rate of over 4.1 million reads per minute, 909 times faster than Megablast and 11 times faster than the abundance estimation program MetaPhlAn. Kraken is available at http://ccb.jhu.edu/software/kraken/.

Krona

https://sourceforge.net/p/krona/home/krona/

Address of the bookmark: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4053813/

Machine Learning !!!

Gudiya Pal — Fri, 01 Jul 2016 12:57:12 -0500

In machine learning, computers apply statistical learning techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions.

Keep scrolling. Using a data set about homes, we will create a machine learning model to distinguish homes in New York from homes in San Francisco.

Address of the bookmark: http://www.r2d3.us/visual-intro-to-machine-learning-part-1/

Scarpa

Poonam Mahapatra — Wed, 13 Jul 2016 07:59:25 -0500

Scarpa is a stand-alone scaffolding tool for NGS data. It can be used together with virtually any genome assembler and any NGS read mapper that supports SAM format. Other features include support for multiple libraries and an option to estimate insert size distributions from data. Scarpa is available free of charge for academic and commercial use under the GNU General Public License (GPL).

See the user manual or the paper for more information about Scarpa. Click here for the supplementary material.

Address of the bookmark: http://compbio.cs.toronto.edu/hapsembler/scarpa.html

Aravind J Shankar gets all India rank 1 in BINC, 2016

Jit — Tue, 19 Jul 2016 05:19:06 -0500

Aravind J Shankar, a bioinformatics graduate of SASTRA University, has secured the all India rank 1 in the Bioinformatics National Certification (BINC) 2016, organised by the Department of Biotechnology, Government of India.

The BINC is a nationwide examination aimed at certifying professionals in bioinformatics and tests their theoretical and practical knowledge across three phases of examination. He is entitled to receive a DBT research fellowship leading to a Ph.D. from any premier research institute in India.

Find predicted CRISPR sites using Ensembl

Jit — Wed, 27 Jul 2016 03:15:59 -0500

Did you know that you can now use Ensembl to help design your CRISPR experiments? Just turn on the brand new track that shows you the CRISPR sites that have been predicted by the WGE group (http://www.sanger.ac.uk/science/tools/wge)

Find out more on our blog:
http://www.ensembl.info/…/find-predicted-crispr-sites-usin…/

Senior Manager (Bioinformatics Operations) at RGCB, India

Wed, 17 Aug 2016 03:19:05 -0500

No. RGCB/ADVT/ADMN&TECH/01/2016

August 17, 2016

RGCB invites applications for the following positions from Indian citizens with prescribed qualifications. Full details including job description, additional desirable qualifications, etc. are described below.

Code No. 1

Senior Manager (Bioinformatics Operations)

(To download application format, click here )

Scale of Pay

PB-3 Rs.15600-39100 + Grade Pay Rs.6600/-

Number of Positions

1 (General)

Minimum Qualifications

PhD in Bioinformatics, Biotechnology, Life Sciences or Computer Science applied to biological questions.
A minimum of 5 years documented experience in national or state government R&D centers or state and central universities.
Track record of research funding and peer reviewed publications.
Proficiency using statistical analysis software or libraries such as R or Matlab.
Experience with a general scripting language such as Python, Ruby, or Pearl
Experience working with Next Generation Sequencing data
Proficiency with data visualization tools (Spotfire, Tableau, R, Python, etc.)
Experience with an object-oriented language such as Java, C++ or C# and familiarity with standard software development best practices: source code control, unit testing, in-code documentation and automated build environments.
Excellent listening, time management, organizational and interpersonal skills
Excellent communication skills, including the ability to illustrate problems and generate solutions
Management skills – demonstrated through the successful management of a team or large projects.
Broad and deep knowledge of computational methods for high-throughput sequence analysis and interpretation.
Extensive experience in delivering bioinformatics as a service and conducting training programs.
Experience of working with a production, customer-focused environment and business development projects.
Experience with management of funding and financial sustainability.
Demonstrated ability to work in a team environment and ability to lead and motivate an effective team, and also work as a good team player.
Good problem solver, able to logically identify solutions to technical problems.
Able to see the bigger picture and contribute towards strategic direction of Platforms and Pipelines teams.
Responsibilities

This position will involve cross-functional teamwork to build and develop bioinformatics tools and provide analysis for ongoing clinical trials.
Collaborate with biomarker scientists, clinical investigators and pipeline teams to build analytical tools.
Implement and evaluate new algorithms for R&D.
Support Research and Development teams by analyzing NGS data to identify predictive response markers
Lead training programs in Computational Biology and Bioinformatics.

More at http://rgcb.res.in/positions.php

Genome STRiP

Neel — Tue, 06 Sep 2016 03:58:19 -0500

Genome STRiP (Genome STRucture In Populations) is a suite of tools for discovering and genotyping structural variations using sequencing data. The methods are designed to detect shared variation using data from multiple individuals.

Genome STRiP looks both across and within a set of sequenced genomes to detect variation. The methods are adaptive and support heterogeneous data sets, including variations in sequencing depth, read lengths and mixtures of paired and single-end reads. A minimum of 20 to 30 genomes are required to get acceptable results, but the method gains power across genomes and processing more genomes provide better results.

To run discovery or genotyping on a single sequenced genome or a small set of genomes, you need to call your data against a background population, such as a set of genomes from the 1000 Genomes Project. The background population does not need to be matched to the target individuals.

Address of the bookmark: http://software.broadinstitute.org/software/genomestrip/

CrossMap

Abhimanyu Singh — Mon, 05 Sep 2016 04:07:38 -0500

CrossMap is a program for convenient conversion of genome coordinates (or annotation files) between different assemblies (such as Human hg18 (NCBI36) <> hg19 (GRCh37), Mouse mm9 (MGSCv37) <> mm10 (GRCm38)).
It supports most commonly used file formats including SAM/BAM, Wiggle/BigWig, BED, GFF/GTF, VCF.
CrossMap is designed to liftover genome coordinates between assemblies. It’s not a program for aligning sequences to reference genome.
We do not recommend using CrossMap to convert genome coordinates between species.

Address of the bookmark: http://crossmap.sourceforge.net/