BOL: Related items

bedtools

Jit — Fri, 24 Feb 2017 04:50:44 -0600

Collectively, the bedtools utilities are a swiss-army knife of tools for a wide-range of genomics analysis tasks. The most widely-used tools enable genome arithmetic: that is, set theory on the genome. For example, bedtools allows one tointersect, merge, count, complement, and shuffle genomic intervals from multiple files in widely-used genomic file formats such as BAM, BED, GFF/GTF, VCF. While each individual tool is designed to do a relatively simple task (e.g., intersect two interval files), quite sophisticated analyses can be conducted by combining multiple bedtools operations on the UNIX command line.

bedtools is developed in the Quinlan laboratory at the University of Utah and benefits from fantastic contributions made by scientists worldwide.

Address of the bookmark: http://bedtools.readthedocs.io/en/latest/index.html

FinisherSC: a repeat-aware and scalable tool for upgrading de novo assembly using long reads

Jit — Mon, 27 Feb 2017 09:49:45 -0600

FinisherSC, a repeat-aware and scalable tool for upgrading de novo assembly using long reads. Experiments with real data suggest that FinisherSC can provide longer and higher quality contigs than existing tools while maintaining high concordance.

Address of the bookmark: http://kakitone.github.io/finishingTool/

MetaBAT: An Efficient Tool for Accurately Reconstructing Single Genomes from Complex Microbial Communities

Jit — Mon, 06 Mar 2017 03:44:34 -0600

MetaBAT, An Efficient Tool for Accurately Reconstructing Single Genomes from Complex Microbial Communities

Grouping large genomic fragments assembled from shotgun metagenomic sequences to deconvolute complex microbial communities, or metagenome binning, enables the study of individual organisms and their interactions. Here we developed an automated metagenome binning software, called MetaBAT, which integrates empirical probabilistic distances of genome abundance and tetranucleotide frequency. Tested on both synthetic and real metagenome datasets, MetaBAT outperforms alternative methods in both accuracy and computational efficiency. Applying MetaBAT to an assembly from 1,704 human gut samples formed 1,634 genome bins (>200kb) in 3 hours, where 621 genome bins are >50% complete with <5% contamination from other species. Further analysis shows that the quality of these genome bins approaches manually curated genomes.

Address of the bookmark: https://bitbucket.org/berkeleylab/metabat

COCACOLA (binning metagenomic contigs using sequence COmposition, read CoverAge, CO-alignment, and paired-end read LinkAge)

Jit — Tue, 07 Mar 2017 08:50:57 -0600

COCACOLA is a general framework that combines different types of information: sequence COmposition, CoverAge across multiple samples, CO-alignment to reference genomes and paired-end reads LinkAge to automatically bin contigs into OTUs. Furthermore, COCACOLA seamlessly embraces customized prior knowledge to facilitate binning accuracy.

News: Python version of COCACOLA is available now!

Address of the bookmark: https://github.com/younglululu/COCACOLA

sequenceserver

Jit — Fri, 10 Mar 2017 08:51:55 -0600

SequenceServer lets you rapidly set up a BLAST+ server with an intuitive user interface for use locally or over the web.

More at http://sequenceserver.com.

Address of the bookmark: https://github.com/wurmlab/sequenceserver

Software and Tools to detect structure variation with long reads !!

Archana Malhotra — Wed, 15 Mar 2017 14:31:09 -0500

Uncovering the connection between genetics and heritable diseases requires an approach that looks at all the variant bases and types in a genome. While a PacBio de novo assembly resolves the most novel SV variants. 8-10X PacBio coverage of single genomes or trios reveals triple the SVs detectable by short-read data.

With Single Molecule, Real-Time (SMRT) Sequencing, you can access structural variations having a broad range of sizes, types, and GC content with the ability to:

Uncover missing heritability linked to structural variation
Unambiguously identify genomic context and variant breakpoints at the sequence level to unravel the genetic etiology of disease
Resolve structural variation across the complete size spectrum with basepair resolution

Following are the SV tools, which can assist you to achieve your goal.

Sniffles: Structural variation caller using third generation sequencing

Sniffles is a structural variation caller using third generation sequencing (PacBio or Oxford Nanopore). It detects all types of SVs using evidence from split-read alignments, high-mismatch regions, and coverage analysis. Please note the current version of Sniffles requires sorted output from BWA-MEM (use -M and -x parameter) or NGM-LR with the optional SAM attributes enabled!

More at https://github.com/fritzsedlazeck/Sniffles

MultiBreak-SV: It identifies structural variants from next-generation paired end data, third-generation long read data, or data from a combination of sequencing platforms.

There are two pieces of software in this release: (1) a pre-processor that takes machineformat (.m5) BLASR files, and (2) MultiBreak-SV. For installation and usage instructions, see doc/MultiBreakSV-Manual.txt.

More at https://github.com/raphael-group/multibreak-sv

Parliament: A Structural Variation Tool. Why ask a single sv-detection approach to find every variant when you can have a parliament of tools deciding?

Publication about the algorithm and “…the first long-read characterization of structural variation in a diploid human personal genome…” (HS1011) - “Assessing structural variation in a personal genome—towards a human reference diploid genome”

More at https://sourceforge.net/projects/parliamentsv/

https://www.dnanexus.com/papers/Parliament_Info_Sheet.pdf

PBHoney: the structural variation discovery tool

PBHoney is an implementation of two variant-identification approaches designed to exploit the high mappability of long reads (i.e., greater than 10,000 bp). PBHoney considers both intra-read discordance and soft-clipped tails of long reads to identify structural variants.

Read The Paper http://www.biomedcentral.com/1471-2105/15/180/abstract

More at https://sourceforge.net/projects/pb-jelly/

SMRT-SV: Structural variant and indel caller for PacBio reads

Structural variant (SV) and indel caller for PacBio reads based on methods from Chaisson et al. 2014.

SMRT-SV provides an official software package for tools described in Chaisson et al. 2014 and adds several key features including the following.

Unified variant calling user interface with built-in cluster compute support
Small indel calling (2-49 bp)
Improved inversion calling (screenInversions)
Quality metric for SV calls based on number of local assemblies supporting each call
Higher sensitivity for SV calls using tiled local assemblies across the entire genome instead of "signature" regions
Genotyping of SVs with Illumina paired-end reads from WGS samples

More at https://github.com/EichlerLab/pacbio_variant_caller

Fools guide

Poonam Mahapatra — Sun, 02 Apr 2017 14:31:18 -0500

This website and accompaning documents are intended as a tool to help researchers dealing with non-model organisms acquire and process transcriptomic high-throughput sequencing data without having to learn extensive bioinformatics skills. It covers all steps from tissue collection, sample preparation and computer setup, through addressing biological questions with gene expression and SNP data.

http://sfg.stanford.edu/denovo.html

http://sfg.stanford.edu/sequencing.html

http://sfg.stanford.edu/BLAST.html

http://sfg.stanford.edu/denovo.html

Address of the bookmark: http://sfg.stanford.edu/guide.html

Biotechnology Eligibility Test (BET) Question Paper !

Abhimanyu Singh — Wed, 17 Apr 2019 04:56:33 -0500

DBT-BET JRF 2019 Exam was held successfully on 14th April 2019. Official Question Paper & Answer key of DBT-BET 2019 Exam has been released.

The best part about the DBT-BET Exam is both the question paper & answer key is released immediately after the exam so you get the upper hand here to check how well you did in the DBT-BET exam, how much you are going to score and if you can pass the Exam with good score. This helps you in planning your career ahead.

DBT Exam is held once in a year by Department of Biotechnology – Govt of India. Candidates willing to get DBT-Junior Research Fellowship – DBT JRF fellowship should take up the DBT-BET Exam, DBT – Biotechnology Eligibility Test (BET) 2020 to be held on somewhere in the month of April. Official Notification for DBT-BET 2020 will be released in Feb 2020.

Answer at https://bioinformaticsonline.com/file/view/39262/biotechnology-eligibility-test-bet-answer-set

LoRDEC: a hybrid error correction program for long, PacBio reads

Jit — Mon, 10 Apr 2017 04:16:09 -0500

LoRDEC is a program to correct sequencing errors in long reads from 3rd generation sequencing with high error rate, and is especially intended for PacBio reads. It uses a hybrid strategy, meaning that it uses two sets of reads: the reference read set, whose error rate is assumed to be small, and the PacBio read set, which is then corrected using the reference set. Typically, the reference set contains Illumina reads.

Usually, errors in PacBio reads include many insertions and deletions, and comparatively less substitutions. LoRDEC can correct errors of all these types.
After correction, a larger portion of the sequence of PacBio reads is usable for detection of region of similarity with other sequences, for aligning them to the contigs of an assembly, etc.

Why is LoRDEC different?

It is efficient and can process large read data sets, included from eukaryotic or vertebrate species, on a usual computing server, and even works on desktop/laptop computers.
It adopts a novel graph based approach: it builds a succinct De Bruijn Graph (DBG) representing the short reads, and seeks a corrective sequence for each erroneous region of a long read by traversing chosen paths in the graph.

Address of the bookmark: http://www.atgc-montpellier.fr/lordec/

Selecting between Python 2 and Python 3?

Rahul Agarwal — Wed, 10 Jul 2013 16:30:58 -0500

Which version is best for bioinformatician to work on?