BOL: Related items

IVA: accurate de novo assembly of RNA virus genomes

Neel — Wed, 23 Jun 2021 07:51:59 -0500

IVA (Iterative Virus Assembler) designed specifically for read pairs sequenced at highly variable depth from RNA virus samples. We tested IVA on datasets from 140 sequenced samples from human immunodeficiency virus-1 or influenza-virus-infected people and demonstrated that IVA outperforms all other virus de novo assemblers.

Availability and implementation: The software runs under Linux, has the GPLv3 licence and is freely available from http://sanger-pathogens.github.io/iva

https://pubmed.ncbi.nlm.nih.gov/25725497/

Address of the bookmark: https://github.com/sanger-pathogens/iva

Bioistats Online course

Abhimanyu Singh — Thu, 10 Nov 2016 04:22:51 -0600

One of our primary focuses will be to develop an understanding of the various ways in which we can assign a probability to some chance event. We'll also learn the fundamental properties of probability, investigate how probability behaves, and learn how to calculate the probability of a new chance event.

This book is handy understanding basic concepts.

Address of the bookmark: https://onlinecourses.science.psu.edu/stat414/node/287

Short-read assembly using Spades !

Abhimanyu Singh — Mon, 31 Jan 2022 07:18:16 -0600

If we only had Illumina reads, we could also assemble these using the tool Spades.

You can try this here, or try it later on your own data.

Get data

We will use the same Illumina data as we used above:

illumina_R1.fastq.gz: the Illumina forward reads
illumina_R2.fastq.gz: the Illumina reverse reads

Assemble

Run Spades:

spades.py -1 illumina_R1.fastq.gz -2 illumina_R2.fastq.gz --careful --cov-cutoff auto -o spades_assembly_all_illumina

-1 is input file of forward reads
-2 is input file of reverse reads
--careful minimizes mismatches and short indels
--cov-cutoff auto computes the coverage threshold (rather than the default setting, “off”)
-o is the output directory

Results

Move into the output directory and look at the contigs:

infoseq contigs.fasta

Research Officer at National Tea Research Foundation

Fri, 18 Nov 2016 04:19:24 -0600

National Tea Research Foundation (NTRF) a registered body, requires qualified and experienced agricultural research scientist for contractual appointment as per details below :

Post Research Officer, NTRF, Kolkata

Essential Post Graduate degree in Life Science having special paper in Bioinformatics. Post Graduate degree in Bioinformatics.

Desirable Ph. D. in the area of computational biology or bioinformatics.

Job Experience Work experience on database development, capable to work independently and efficient in bioinformatics related project.

Job Responsibility

To develop database on various aspects of tea research.

Screening of the In-house projects of NTRF at the preliminary level.

Review and evaluation of In-house projects of NTRF. Technical monitoring of the In-house projects of NTRF.

Reviewing the final technical report of the In-house projects of NTRF.

Putting-up of same proposals for taking approval and sanction of the competent authority.

Physical and technical verification of the In-house projects of NTRF.

To assist in organizing seminars / workshops / meetings etc.

Interested candidate may appear for walk-in Interview on 17 th November, 2016

More Info :

http://www.teaboard.gov.in/pdf/Recruitment_for_the_post_of_Research_Officer_pdf7538.pdf

auN: a new metric to measure assembly contiguity

Jit — Tue, 02 Aug 2022 01:18:47 -0500

Given a de novo assembly, we often measure the “average” contig length by N50. N50 is neither the real average nor median. It is the length of the contig such that this and longer contigs cover at least 50% of the assembly. A longer N50 indicates better contiguity. We can similarly define Nx such that contigs no shorter than Nx covers x% of the assembly. The Nx curve plots Nx as a function of x, where x is ranged from 0 to 100.

Address of the bookmark: https://lh3.github.io/2020/04/08/a-new-metric-on-assembly-contiguity

Spines

Jit — Mon, 28 Nov 2016 05:33:26 -0600

Spines is a collection of software tools, developed and used by the Vertebrate Genome Biology Group at the Broad Institute. It provides basic data structures for efficient data manipulation (mostly genomic sequences, alignments, variation etc.), as well as specialized tool sets for various analyses. It also features three sequence alignment packages: Satsuma, a highly parallelized program for high-sensitivity, genome-wide synteny; Papaya, an all-purpose alignment tool for less diverged sequences; and SLAP, a context-sensitive local aligner for diverged sequences with large gaps.

Access Spines here.

Address of the bookmark: https://www.broadinstitute.org/genome-sequencing-and-analysis/spines

Mitochondrial genome assembly tools !

Abhi — Wed, 06 Sep 2023 00:37:18 -0500

Mitochondrial genome assembly tools are specialized software and algorithms designed to accurately reconstruct the mitochondrial genome (mitogenome) from sequencing data, typically obtained through techniques like next-generation sequencing (NGS). The mitochondrial genome is relatively small compared to the nuclear genome, making it an ideal target for assembly. Here are some commonly used mitochondrial genome assembly tools:

MitoFinder: Mitofinder is a pipeline to assemble mitochondrial genomes and annotate mitochondrial genes from trimmed read sequencing data.

MitoHiFi: a python pipeline for mitochondrial genome assembly from PacBio high fidelity reads

MITObim: MITObim is a tool specifically developed for the iterative assembly of mitochondrial genomes. It starts with a reference mitogenome and iteratively refines the assembly using the read data.

MITOS: MITOS is a web-based platform that provides a pipeline for annotating mitochondrial genomes. It integrates multiple software tools for assembly, annotation, and visualization of mitogenomes.

MIRA: MIRA (Mimicking Intelligent Read Assembly) is a versatile genome assembly tool that can be used for mitochondrial genome assembly. It supports various sequencing technologies and allows for reference-based or de novo assembly.

NOVOPlasty: NOVOPlasty is a user-friendly tool designed for de novo assembly of organelle genomes, including mitochondria. It utilizes a seed-and-extend algorithm and is suitable for both short-read and long-read data.

MITOS2: MITOS2 is an updated version of the MITOS pipeline, which automates the annotation of mitochondrial genomes. It provides improved accuracy and additional features for mitochondrial genome analysis.

GetOrganelle: While primarily designed for chloroplast genome assembly, GetOrganelle can also be used for mitochondrial genome assembly. It is particularly useful for dealing with high-throughput sequencing data.

SPAdes: SPAdes (St. Petersburg genome assembler) is a versatile genome assembly tool that can be employed for mitochondrial genome assembly, especially when dealing with complex datasets that may contain nuclear mitochondrial DNA sequences (numts).

IDBA-UD: IDBA-UD (Iterative De Bruijn Graph De Novo Assembler) is another de novo assembly tool that can be used for mitochondrial genome assembly, especially in cases with relatively low coverage.

Velvet: Velvet is a de novo assembly tool that can be applied to mitochondrial genome assembly, especially when working with short-read data.

When selecting a mitochondrial genome assembly tool, it's important to consider the specific characteristics of your sequencing data, such as read length and coverage, as well as the complexity of the mitochondrial genome. Additionally, some tools are better suited for specific organisms or research objectives, so choosing the right tool will depend on your particular project requirements.

bipype

Jit — Thu, 01 Dec 2016 08:47:38 -0600

Bipype is a very useful program, which prepare a lot of types of bioinformatics analyses. There are three input options: amplicons, WGS (whole genome sequences) and metatranscriptomic data. If amplicons are input data, then bipype does reconstruction and pairs merging. After that biodiversity is searching. There are two types of searching depending on the amplicons types (ITS or 16S). If WGS are chosen, then bipype finds the SA coordinates of the input reads and generates alignments in the SAM format given single-end reads, aligns reads to reference sequence(s). All of these analyses will be shown with Krona program, which allows to show hierarchical data with pie charts.

Address of the bookmark: https://readthedocs.org/projects/bipype/

fqtools

Jit — Thu, 08 Dec 2016 09:31:12 -0600

fqtools is a software suite for fast processing of FASTQ files. Various file manipulations are supported. See below for a full list of the subcommands available and a brief description of their purpose. Most of the individual subcommands will take either a single file or a pair of files as input. If no input file is specified, fqtools will attempt to read data from stdin. In this case, it is advisabe to specify the format of the data provided. For subcommands that generate FASTQ data, either a single file or a pair of files will be generated. If no -o argument is provided, single files will be writted to stdout.

Address of the bookmark: https://github.com/alastair-droop/fqtools

BIMA V3: an aligner customized for mate pair library sequencing

Abhimanyu Singh — Wed, 14 Dec 2016 15:20:00 -0600

Summary: Mate pair library sequencing is an effective and economical method for detecting genomic structural variants and chromosomal abnormalities. Unfortunately, the mapping and alignment of mate pair read pairs to a reference genome is a challenging and
time consuming process for most NGS alignment programs. Large insert sizes, introduction of library preparation protocol artifacts (biotin junction reads, paired-end read contamination, chimeras, etc.), and presence of structural variant breakpoints within reads increases mapping and alignment complexity. We describe an algorithm that is up to 20 times faster and 25% more accurate than popular NGS alignment programs when processing mate pair sequencing.
Availability: http://bioinformaticstools.mayo.edu/research/bima/
Contact: vasmatzis.george@mayo.edu

Address of the bookmark: http://bioinformatics.oxfordjournals.org/content/early/2014/02/12/bioinformatics.btu078.full.pdf