BOL: Related items

Quick next generation sequencing (NGS) terms definition

Neel — Fri, 09 Jun 2017 04:52:26 -0500

fragment size: the Illumina WGS protocol generates paired-end reads from both ends of longer fragments. The lengths of these fragments are assumed to be sampled from a normal distribution. Therefore, in the absence of structural variants, mapping locations of the paired ends span within an interval [δmin,δmax]. Most (>90%) of paired-end reads are sampled from no-SV regions, therefore the fragment size distribution can be learned empirically for each WGS data set separately.

concordant reads: a read pair is called concordant if they can be mapped to the reference genome as “expected”: (a) mapped to opposing strands where the upstream read is mapped to the forward strand and the downstream read is mapped to the reverse strand2, (b) the distance between ends is between the minimum and maximum expected fragment size.

discordant reads: briefly, any non-concordant read pair is considered discordant. Note that, by definition, the discordant read pairs signal potential SVs. The sequence signature produced by these type of reads is known as read-pair signature.

split reads: a read that can only be mapped to the reference genome by breaking into two sub-reads is called a split-read. These types of reads also indicate a potential SV or a short insertion or deletion (indel).

read depth: number of reads that map within a region of the genome. Overall genome-wide read depth is also referred to as depth of coverage. It is expected that the number of reads that “cover” each base-pair to follow a Poisson distribution. Therefore, if the read depth over a certain region deviates significantly from this distribution, it signals for a potential copy number variation (CNV).

MIX: Combining multiple assemblies from NGS data

Rahul Nayak — Tue, 08 May 2018 04:58:05 -0500

Mix is a tool that combines two or more draft assemblies, without relying on a reference genome and has the goal to reduce contig fragmentation and thus speed-up genome finishing. The proposed algorithm builds an extension graph where vertices represent extremities of contigs and edges represent existing alignments between these extremities. These alignment edges are used for contig extension. The resulting output assembly corresponds to a path in the extension graph that maximizes the cumulative contig length.

The Mix algorithm, approach and results were published in BMC bioinformatics : http://www.biomedcentral.com/1471-2105/14/S15/S16.

Address of the bookmark: https://github.com/cbib/MIX

Search Shell Command History

Rahul Nayak — Thu, 12 Jun 2014 17:43:34 -0500

We use couple of hundreads of command in daily basis. Most of them are actually repeated several time. The question remain open how do I search old command history under bash shell and modify or reuse it?

Now a days almost all modern shell allows you to search command history if enabled by user. Use history command to display the history list with line numbers. Lines listed with with a * have been modified by user.

Shell history search command

Type history at a shell prompt:
$ history

It will display the list of all used commandline history with an serial number.

To search particular command, enter:
$ history | grep command-name
$ history | egrep -i 'scp|ssh|ftp'
Emacs Line-Edit Mode Command History Searching

To get previous command containing string, hit [CTRL]+[r] followed by search string:

(reverse-i-search):

To get previous command, hit [CTRL]+[p]. You can also use up arrow key.

CTRL-p

To get next command, hit [CTRL]+[n]. You can also use down arrow key.

CTRL-n

fc command

Apart from hostory command there are fc command to extract the command from history. The fc stands for either "find command" or "fix command.

For example list last 10 command, enter:
$ fc -l 10
To list commands 130 through 150, enter:
$ fc -l 130 150
To list all commands since the last command beginning with ssh, enter:
$ fc -l ssh
You can edit commands 1 through 5 using vi text editor, enter:
$ fc -e vi 1 5

Delete command history

The -c option causes the history list to be cleared by deleting all of the entries:
$ history -c

Installing Salmon for Trinity !

Rahul Nayak — Tue, 03 Jul 2018 09:02:29 -0500

➜ trinityrnaseq-Trinity-v2.6.6 git:(master) ✗ conda install salmon
Solving environment: done

## Package Plan ##

environment location: /home/urbe/anaconda3

added / updated specs:
- salmon

The following packages will be downloaded:

package | build
---------------------------|-----------------
boost-1.64.0 | py36_4 331 KB conda-forge
jemalloc-5.1.0 | hfc679d8_0 8.2 MB conda-forge
boost-cpp-1.64.0 | 1 17.8 MB conda-forge
salmon-0.10.2 | 1 3.7 MB bioconda
conda-4.5.5 | py36_0 624 KB conda-forge
tbb-2018_20171205 | 0 1.2 MB conda-forge
------------------------------------------------------------
Total: 31.8 MB

The following NEW packages will be INSTALLED:

boost: 1.64.0-py36_4 conda-forge
boost-cpp: 1.64.0-1 conda-forge
jemalloc: 5.1.0-hfc679d8_0 conda-forge
salmon: 0.10.2-1 bioconda
tbb: 2018_20171205-0 conda-forge

The following packages will be UPDATED:

conda: 4.5.4-py36_0 conda-forge --> 4.5.5-py36_0 conda-forge

Proceed ([y]/n)? y

Downloading and Extracting Packages
boost-1.64.0 | 331 KB | ####################################################################################################################################### | 100%
jemalloc-5.1.0 | 8.2 MB | ####################################################################################################################################### | 100%
boost-cpp-1.64.0 | 17.8 MB | ####################################################################################################################################### | 100%
salmon-0.10.2 | 3.7 MB | ####################################################################################################################################### | 100%
conda-4.5.5 | 624 KB | ####################################################################################################################################### | 100%
tbb-2018_20171205 | 1.2 MB | ####################################################################################################################################### | 100%
Preparing transaction: done
Verifying transaction: done
Executing transaction: done

Bioinformatician’s Pocket Reference !!

RAJESH DETROJA — Sun, 08 Jun 2014 09:56:58 -0500

It is amusing how brain of bioinformaticians work! Learning a new programming language for days feels so much of fun that making 5 minute discussion with neighbours (unless under special circumstances!) in our own mother-tongue. Today every bioinformatician keeps more than few languages and core IT toolkits on their plate. It has become mandatory to be able to mould different code snippets to build our own custom workflows, and thus keeping syntax at our fingertips has become essential.Although Google is best way to get syntax problem solved, it is not a bad idea to keep reference sheets is our smartphones or stick out some printed sheets on the back of your door, in the old fashion way!!

Address of the bookmark: http://infoplatter.wordpress.com/2014/04/06/bioinformaticians-pocket-reference/

List of non-commercial NGS genotype-calling software

Jit — Thu, 09 Aug 2018 04:21:32 -0500

Meaningful analysis of next-generation sequencing (NGS) data, which are produced extensively by genetics and genomics studies, relies crucially on the accurate calling of SNPs and genotypes. Recently developed statistical methods both improve and quantify the considerable uncertainty associated with genotype calling, and will especially benefit the growing number of studies using low- to medium-coverage data.

A list of programs for genotype and SNP calling :

SOAP2 http://soap.genomics.org.cn/index.html

Single-sample High-quality variant database (for example, dbSNP) Package for NGS data analysis, which includes a single individual genotype caller (SOAPsnp)

realSFS http://128.32.118.212/thorfinn/realSFS/

Single-sample Aligned reads Software for SNP and genotype calling using single individuals and allele frequencies. Site frequency spectrum (SFS) estimation

Samtools http://samtools.sourceforge.net/

Multi-sample Aligned reads Package for manipulation of NGS alignments, which includes a computation of genotype likelihoods (samtools) and SNP and genotype calling (bcftools)

GATK http://www.broadinstitute.org/gsa/wiki/index.php/The_Genome_Analysis_Toolkit Multi-sample Aligned reads Package for aligned NGS data analysis, which includes a SNP and genotype caller (Unifed Genotyper), SNP filtering (Variant Filtration) and SNP quality recalibration (Variant Recalibrator)

Beagle http://faculty.washington.edu/browning/beagle/beagle.html

Multi-sample LD Candidate SNPs, genotype likelihoods Software for imputation, phasing and association that includes a mode for genotype calling

IMPUTE2 http://mathgen.stats.ox.ac.uk/impute/impute_v2.html

Multi-sample LD Candidate SNPs, genotype likelihoods Software for imputation and phasing, including a mode for genotype calling. Requires fine-scale linkage map

QCall ftp://ftp.sanger.ac.uk/pub/rd/QCALL

Multi-sample LD ‘Feasible’ genealogies at a dense set of loci, genotype likelihoods Software for SNP and genotype calling, including a method for generating candidate SNPs without LD information (NLDA) and a method for incorporating LD information (LDA). The ‘feasible’ genealogies can be generated using Margarita (http://www.sanger.ac.uk/resources/software/margarita)

MaCH http://genome.sph.umich.edu/wiki/Thunder

Multi-sample LD Genotype likelihoods Software for SNP and genotype calling, including a method (GPT_Freq) for generating candidate SNPs without LD information and a method (thunder_glf_freq) for incorporating LD information

Assistant Professor in Medical Bioinformatics

Tue, 24 Jun 2014 01:46:36 -0500

Advt. No : ME-I/A-IV/03/14
No.of Posts:01 (SC)
Pay Scale:
Pay Band of Rs.15600-39100 + Rs.6000/- GP +NPA @ 25% of Basic Pay +Learning Resource Allowance @ Rs.20,000/-P.A.+ Conveyance Allowance @ Rs. 1650/-P.M.+ Academic Allowance @ Rs.2500/- P.M. and other admissible allowances.
Qualifications:
Area of Specialization:-
Bioinformatics/Computational/Biology/Genomics/ Proteomics/ Structural Biology
1. Postgraduate qualification, e.g. Master’s Degree in Biotechnology/Bioinformatics/ Biophysics.
2. A Doctorate Degree of recognized University/Institute in a basic or allied Medical Science subject e.g. Medical Biotechnology/Biophysics. Bioinformatics/X-ray Crystallography/
Immunology/Structural Biology etc
Experience:
1.Minimum three years teaching and/or research experience in a recognized medical/research Institution in an allied medical subject after obtaining doctorate degree and preferably in Medical
Molecular Biology/ Biophysics/Structural Biology/Genomics and Clinical Proteomics/Computational Biology.
2. Minimum two publication with atleast one in international journal and atleast one as first author
Desirable:-
Consistently excellent scholastic/academic record, demonstrated ability to write grant proposal/(s) successfully, Post Doctoral training in a frontier area of medical Bioinformatics Research and of direct relevance to clinical diagnosis or patient care (preferably from a recognized top-ranking medical institution abroad)
Send your applications to O/O, Deputy Registrar, Recruitment & Establishment Cell, University of Health Sciences, Rohtak by 08.7.2014
For more details,please visit website: http://pgimsrohtak.nic.in/2014%20AP%20Advt.pdf
Last Apply Date: 08 Jul 2014

AMStat: display statistics of large sequence files from next generation sequencing projects

Neel — Fri, 09 Nov 2018 13:34:56 -0600

SAMStat is an efficient C program to quickly display statistics of large sequence files from next generation sequencing projects. When applied to SAM/BAM files all statistics are reported for unmapped, poorly and accurately mapped reads separately. This allows for identification of a variety of problems, such as remaining linker and adaptor sequences, causing poor mapping. Apart from this SAMStat can be used to verify individual processing steps in large analysis pipelines.

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

Postdoc position at Centre Méditerranéen de Médecine Moléculaire

Sun, 06 Jul 2014 11:23:06 -0500

The research group of Dr. Michele Trabucchi at the Centre Méditerranéen de Médecine Moléculaire (C3M) at INSERM U1065 (University of Nice Sophia-Antipolis, France) is seeking candidates for a Postdoctoral fellow position to start on October 2014 for 3 years funded by FRM (Fondation pour la Recherche Médicale).
The broad interest of the lab is in understanding the expression control and function of small RNAs in activated myeloid cells (visit our webpage to check research interests and publications of the group : http://www.unice.fr/c3m/EN/Equipe10.html ).

The work will focus on the functional studies of small RNAs by using next-generation sequencing approaches.

Candidates should hold a Ph.D. degree and have strong background in bioinformatics.
The University of Nice Sophia-Antipolis provides a wide range of facilities and training essential for biomedical research.
Interested applicants should send a PDF with a cover letter stating research interests and qualifications, an updated CV, a summary of previous research experience and contact information for two references to Michele Trabucchi ( mtrabucchi@unice.fr )

Scientist-B (Bioinformatics) at AIIMS, Delhi

Sun, 20 Dec 2020 04:34:55 -0600

Name of the Project: “Artificial intelligence in Oncology, Harnessing big data and advanced computing to provide personalized diagnosis and treatment for Cancer patients”

Age Limit: 35

How to Apply for the AIIMS Life Science Job:

Interested applicants are asked to send out a detailed CV to Dr Ashok Sharma (aioncoaiims@gmail.com). Laboratory of Chromatin and also Cancer Epigenetics, Department of Biochemistry with the subject line “Application for Scientist-B position for MeitY project” latest by January 01st, 2021.
Complete Information of the year of passing, experience, marks, etc. ought to be mentioned in the CV Incomplete. applications will certainly be rejected Just shortlisted applicants will be called for interview. Chosen candidates will certainly be intimated by email/phone.
No TA/DA will certainly be paid for appearing in the interview.
Note, The institute reserved the right to fill up or not to fill up the post advertised.

Emoluments: Rs. 56,000/- plus 24 percent HRA

Eligibility:
2nd class Master’s Degree with a PhD in a pertinent subject (Bioinformatics) from.a recognized University
1st class Master’s degree in Life Sciences (Bioinformatics) from a recognized university OR.
Bachelor’s Degree in Engineering or-Technology with minimal 60% marks from a recognized University or equivalent.

Desirable Qualifications:
Experience in Bioinformatics/NGS data. Analysis/System Biology/Computer Science/ statistics with experience in Machine learning/Al project.
Experience of Deep learning applications in biological data ( image/text).
Proficient in Rf Python machine learning libraries.
Prior experience in the cancer-related project (ML-based) will be advantageous.
Experience with PyTorch/TensorFlow will certainly be very desirable.
Applicant should have strong scientific writing as well as. verbal abilities.
Papers in sci-indexed journals demonstrating ML skill sets.
Database handling will certainly be plus yet not required.

More detail at https://www.aiims.edu/images/pdf/recruitment/advertisement/biochem-16-12-20.pdf