BOL: Related items

MashMap: a fast and approximate software for mapping long reads (PacBio/ONT) or assembly to reference genome(s)

Jit — Tue, 12 Dec 2017 17:23:31 -0600

MashMap is a fast and approximate software for mapping long reads (PacBio/ONT) or assembly to reference genome(s). It maps a query sequence against a reference region if and only if its estimated alignment identity is above a specified threshold. It does not compute the alignments explicitly, but rather estimates a k-mer based Jaccard similarity using a combination of Winnowing and MinHash. This is then converted to an estimate of sequence identity using the Mash distance. An appropriate k-mer sampling rate is automatically determined given minimum local alignment length and identity thresholds. The efficiency of the algorithm improves as both of these thresholds are increased.

Address of the bookmark: https://github.com/marbl/MashMap

TEannot

Jit — Thu, 18 Aug 2016 10:02:03 -0500

We advise to run first the TEdenovo pipeline but it is not compulsory. We suppose you begin by running the TEannot pipeline on the example provided in the directory "db/" rather than directly on your own genomic sequences. Thus, from now on, the project name is "DmelChr4".

Address of the bookmark: https://urgi.versailles.inra.fr/Tools/REPET/TEannot-tuto

RGFA: powerful and convenient handling of assembly graphs

Rahul Nayak — Thu, 25 Jan 2018 05:47:53 -0600

RGFA, an implementation of the proposed GFA specification in Ruby. It allows the user to conveniently parse, edit and write GFA files. Complex operations such as the separation of the implicit instances of repeats and the merging of linear paths can be performed. A typical application of RGFA is the editing of a graph, to finish the assembly of a sequence, using information not available to the assembler. We illustrate a use case, in which the assembly of a repetitive metagenomic fosmid insert was completed using a script based on RGFA.

https://github.com/ggonnella/rgfa

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5103826/

GeneMANIA

Jit — Mon, 22 Aug 2016 09:55:16 -0500

Faster, more accurate algorithms function prediction "GeneMANIA (Multiple Association Network Integration Algorithm)" have however been developed in recent years and are publicly available on the web, indicating the future direction of function prediction.

Address of the bookmark: http://genemania.org/

MECAT: fast mapping, error correction, and de novo assembly for single-molecule sequencing reads

Rahul Nayak — Fri, 11 May 2018 05:07:45 -0500

MECAT is an ultra-fast Mapping, Error Correction and de novo Assembly Tools for single molecula sequencing (SMRT) reads. MECAT employs novel alignment and error correction algorithms that are much more efficient than the state of art of aligners and error correction tools. MECAT can be used for effectively de novo assemblying large genomes. For example, on a 32-thread computer with 2.0 GHz CPU , MECAT takes 9.5 days to assemble a human genome based on 54x SMRT data, which is 40 times faster than the current PBcR-Mhap pipeline. MECAT performance were compared with PBcR-Mhap pipeline, FALCON and Canu(v1.3) in five real datasets. The quality of assembled contigs produced by MECAT is the same or better than that of the PBcR-Mhap pipeline and FALCON.

https://www.nature.com/articles/nmeth.4432

Address of the bookmark: https://github.com/xiaochuanle/MECAT

GeneValidator - Identify problems with predicted genes

Poonam Mahapatra — Fri, 26 Aug 2016 06:00:03 -0500

GeneValidator helps in identifing problems with gene predictions and provide useful information extracted from analysing orthologs in BLAST databases. The results produced can be used by biocurators and researchers who need accurate gene predictions.

If you would like to use GeneValidator on a few sequences, see our online GeneValidator Web App -http://genevalidator.sbcs.qmul.ac.uk.

If you use GeneValidator in your work, please cite us as follows:

Dragan M‡, Moghul MI‡, Priyam A, Bustos C & Wurm Y. 2016. GeneValidator: identify problems with protein-coding gene predictions. Bioinformatics, doi: 10.1093/bioinformatics/btw015.

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

Cerulean: A hybrid assembly using high throughput short and long reads

Rahul Nayak — Tue, 05 Jun 2018 10:10:15 -0500

Cerulean extends contigs assembled using short read datasets like Illumina paired-end reads using long reads like PacBio RS long reads. Cerulean v0.1 has been implemented with bacterial genomes in mind. The method is fully described in Deshpande, V., Fung, E. D., Pham, S., & Bafna, V. (2013). Cerulean: A hybrid assembly using high throughput short and long reads. arXiv preprint arXiv:1307.7933. http://arxiv.org/abs/1307.7933

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

Scientist at Advanced Centre for Treatment, Research and Education in Cancer - Navi Mumbai, Maharashtra

Tue, 30 Aug 2016 04:16:15 -0500

Scientist
Advanced Centre for Treatment, Research and Education in Cancer - Navi Mumbai, Maharashtra
Scientist (One position)
Project: Bioinformatics centre DBT- Sub-DIC at ACTREC
Funding agency: DBT Grant No.232

Duration of the Project: Six Months from the date of appointment can be extended further for six months
Essential Qualification and Experience: 1st Class Masters Degree in Bioinformatics or Life Sciences equivalent degree from a recognized University with 4 years R&D experience in Bioinformatics or relevant subjects from recognized institutes.
OR
Ph.D. degree in Bioinformatics or Life Sciences from recognized University.
M.Sc. degree obtained after a one year course will not be considered.
Experience: Research/teaching experience in Bioinformatics or relevant subjects form recognized Institute(s).

More at http://www.actrec.gov.in/data%20files/Vacancies/2016/AV-scin-stud-trainee-6-Sept-16.docx

ChopStitch: exon annotation and splice graph construction using transcriptome assembly and whole genome sequencing data

Rahul Nayak — Tue, 03 Jul 2018 04:14:52 -0500

ChopStitch is a new method for finding putative exons and constructing splice graphs using an assembled transcriptome and whole genome shotgun sequencing (WGSS) data. ChopStitch identifies exon-exon boundaries in de novo assembled RNA-seq data with the help of a Bloom filter that represents the k-mer spectrum of WGSS reads. The algorithm also detects base substitutions in transcript sequences corresponding to sequencing or assembly errors, haplotype variations, or putative RNA editing events. The primary output of our tool is a FASTA file containing putative exons. Further, exon edges are interrogated for alternative exon-exon boundaries to detect transcript isoforms, which are reported as splice graphs in dot output format.

Address of the bookmark: https://github.com/bcgsc/ChopStitch

R-chie

Jit — Thu, 01 Sep 2016 11:47:24 -0500

R-chie allows you to make arc diagrams of RNA secondary structures, allowing for easy comparison and overlap of two structures, rank and display basepairs in colour and to also visualize corresponding multiple sequence alignments and co-variation information.
R4RNA is the R package powering R-chie, available for download and local use for more customized figures and scripting.

http://www.e-rna.org/r-chie/plot.cgi?eg=single

Address of the bookmark: http://www.e-rna.org/r-chie/plot.cgi?eg=single