BOL: Related items

Hifiasm: a haplotype-resolved assembler for accurate Hifi reads

Jit — Thu, 24 Dec 2020 10:03:36 -0600

Hifiasm is a fast haplotype-resolved de novo assembler for PacBio Hifi reads. It can assemble a human genome in several hours and works with the California redwood genome, one of the most complex genomes sequenced so far. Hifiasm can produce primary/alternate assemblies of quality competitive with the best assemblers. It also introduces a new graph binning algorithm and achieves the best haplotype-resolved assembly given trio data.

Address of the bookmark: https://github.com/chhylp123/hifiasm

Bioinformatics tools for telomere to telomere assembly !

BioStar — Tue, 17 Aug 2021 13:17:09 -0500

● Merfin – k-mer-based assembly and variant calling evaluation for improved consensus accuracy (Arang Rhie)
● PanGenie – algorithm that leverages a pangenome reference built from haplotype-resolved genome assemblies in conjunction with k-mer count information from raw, short-read sequencing data to genotype a wide spectrum of genetic variation (Tobias Marschall)
● SQANTI3 – an automated pipeline for the classification of long-read transcripts that can assess the quality of data and the preprocessing pipeline (Rocío Amorín de Hegedüs @rocioadh)
● tama (Transcriptome Annotation by Modular Algorithms) – software designed for processing Iso-Seq data and other long-read transcriptome data (Richard Kuo @GenomeRIK)
● pbaa (PacBio Amplicon Analysis) – separates complex mixtures of amplicon targets from genomic samples to cluster and generate high-quality consensus sequences from HiFi reads (Zev Kronenberg @zevkronenberg)
● bellerophon – analyzes MHC typing and other low-complexity gene amplicon data; performs allele calling while detecting polymorphic sites within the sequences and removing potential chimeric sequence variants (Yuanyuan Cheng @Yuanyuan929)
● svpack – tools for filtering, comparing, and annotating structural variant (SV) calls in VCF format (Aaron Wenger)
● JumboDB – tool for de Bruijn graph construction (Anton Bankevich @AntonBankevich)
● uLTRA – tool for splice alignment of long transcriptomic reads to a genome, guided by a database of exon annotations. (Kristoffer Sahlin @krsahlin)
● LeafGo – workflow to rapidly produce high-quality de novo plant genomes (Luca Ermini @ermini_luca)

Reference:

https://www.pacb.com/blog/young-investigators-share-stellar-science-career-advice-and-bioinformatics-tools-at-smrt-leiden-2021/

Internship Program for Bioinformatics / Biotechnology / MBA / MCA (No. Of Vacancy: 5)

Mon, 15 Dec 2014 08:11:02 -0600

ArrayGen is offering an Internship Program for Post graduate Bioinformatics / Biotechnology / MBA / MCA students and professionals. ArrayGen Technologies provide an excellent opportunity to gain research experience and explore if a scientific career is right for you. Currently we offer positions to outstanding students interested in Next Generation Sequencing (NGS) data analysis or marketing or software development. Applications are accepted throughout the year. Accepted students will be notified through email.

Steps to find palindrome in genomes !

BioStar — Thu, 09 Mar 2023 02:56:54 -0600

Palindromes are sequences of nucleotides that read the same backward as forward. They can be present in genomes and have various biological functions. Here are some methods for discovering palindromes in genomes:

Direct sequence search: One of the simplest ways to discover palindromes is to search the genome sequence directly for palindromic sequences using pattern matching tools, such as regular expressions or string algorithms. This approach can be useful for discovering simple palindromes, but may miss more complex palindromic structures.
Dot plot analysis: Dot plot analysis is a graphical method that can be used to identify palindromic regions in a genome. It involves plotting the genome sequence against itself and examining the diagonal patterns that emerge. Palindromic regions will appear as symmetrical patterns along the diagonal.
Restriction enzyme analysis: Some restriction enzymes, such as EcoRI and HindIII, recognize palindromic sequences and cleave DNA at these sites. By digesting the genome with these enzymes and examining the resulting fragments, palindromic regions can be identified.
Next-generation sequencing: High-throughput sequencing technologies, such as PacBio and Oxford Nanopore, can generate long reads that can span entire palindromic regions. By mapping these reads to the genome, palindromic regions can be identified and characterized.
Comparative genomics: Comparing the genomes of related species can also reveal palindromic regions that are conserved across evolutionarily divergent lineages. This approach can help identify functional palindromes that are under selective pressure.

Overall, the discovery of palindromic sequences in genomes can be accomplished using a variety of methods, each with their own advantages and limitations. A combination of these methods can provide a comprehensive understanding of the palindromic landscape of a genome.

irishgrid: Irish Grid Mapping System

Jit — Fri, 26 Dec 2014 07:53:24 -0600

Perl module for creating geographic 10km-square maps using either SVG or PNG (with GD library) output format.

Originally design to map the location of objects in a 10 km map IrishGrid includes:

native support of the Irish Grid System (see http://www.osi.ie/)
optimize for speed (there's as less as possible data to conversion)
customized color functions

https://code.google.com/p/irishgrid/downloads/detail?name=irishgrid.pl

Address of the bookmark: https://code.google.com/p/irishgrid/

QuorUM: An Error Corrector for Illumina Reads

Jit — Wed, 08 Nov 2017 11:40:41 -0600

Illumina Sequencing data can provide high coverage of a genome by relatively short (most often 100 bp to 150 bp) reads at a low cost. Even with low (advertised 1%) error rate, 100 × coverage Illumina data on average has an error in some read at every base in the genome. These errors make handling the data more complicated because they result in a large number of low-count erroneous k-mers in the reads. However, there is enough information in the reads to correct most of the sequencing errors, thus making subsequent use of the data (e.g. for mapping or assembly) easier. Here we use the term “error correction” to denote the reduction in errors due to both changes in individual bases and trimming of unusable sequence. We developed an error correction software called QuorUM. QuorUM is mainly aimed at error correcting Illumina reads for subsequent assembly. It is designed around the novel idea of minimizing the number of distinct erroneous k-mers in the output reads and preserving the most true k-mers, and we introduce a composite statistic π that measures how successful we are at achieving this dual goal. We evaluate the performance of QuorUM by correcting actual Illumina reads from genomes for which a reference assembly is available.

QuorUM is distributed as an independent software package and as a module of the MaSuRCA assembly software. Both are available under the GPL open source license at http://www.genome.umd.edu.

Address of the bookmark: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130821

Teaching Assistant at SVIMS

Fri, 31 Jul 2015 10:15:16 -0500

Eligible candidates are invited for a walk-in-interview for recruitment of Teaching Assistant in the Department of Bioinformatics on 8.08.2015 at 10 A.M. in the Committee Hall, SVIMS, Tirupati. The candidates have to attend with all original certificates of qualification, experience on the date of interview. The engagement will be made purely on adhoc basis for a period of 6 months and it can be terminated at any time without notice or without assigning any reason thereof. This is purely an adhoc appointment and the candidate will not have any right to claim permanent benefits of any kind.

1. Remuneration : Rs. 12000/- per month (consolidated)

2. Qualification : M.Sc./M.Tech. Bioinformatics (preference will be given to the candidates with BINC / NET / GATE / Bioinformatics DBT-Traineeship / Studentship and teaching experience)

3. Place of work : Department of Bioinformatics, SVIMS, Tirupati

4. No. of Position : One

Terms and conditions:

1. Candidates are required to submit the Biodata, attested copies of relevant certificates in support of their age, educational qualification, experience etc., before the interview committee, SVIMS University, Tirupati.
2. No TA / DA will be paid for attending the interview.
3. Interim enquiries will not be entertained.
4. The maximum age limit for Teaching Assistant is 34 years as on 8th August, 2015.
5. The tenure of will be further extended subject to performance of the incumbent.

Advertisement: http://svimsbic.org/Teaching_Assistant_B.I._2015.pdf

NxRepair: error correction in de novo assemblies using Nextera Mate Pair Reads

BioStar — Thu, 24 Jan 2019 10:35:12 -0600

NxRepair is a python module that automatically detects large structural errors in de novo assemblies using Nextera mate pair reads. The decector will break a contig at the site of an identified misassembly and will generate a new fasta file containing both the corrected contigs and the correct, unaffected contigs.

https://nxrepair.readthedocs.io/en/latest/tutorial.html

nxrepair aligned_matepairs.bam assemblyfasta.fasta error_locations.csv new_fasta.fasta

Address of the bookmark: https://github.com/rebeccaroisin/nxrepair

Interview with a bioinformatician series ...

Jitendra Narayan — Sat, 27 Dec 2014 13:30:15 -0600

The aim of this series to interviews some notable bioinformaticians to get their views on various aspects of bioinformatics research. Hopefully these answers will prove useful to others in the field, especially to those who are just starting their bioinformatics careers.

This series will be available at BOL every fortnight.

BEAR: Better Emulation for Artificial Reads

BioStar — Sat, 06 Jul 2024 04:27:53 -0500

Created by Stephen Johnson, Brett Trost, Dr. Jeffrey R. Long, Dr. Anthony Kusalik University of Saskatchewan, Department of Computer Science

BEAR is intended to be an easy-to-use collection of scripts for generating simulated WGS metagenomic reads with read lengths, quality scores, error profiles, and species abundances derived from real user-supplied WGS data.

Address of the bookmark: https://github.com/sej917/BEAR