BOL: Related items

GenomeMapper: Simultaneous alignment of short reads against multiple genomes

Jit — Fri, 25 May 2018 09:29:44 -0500

GenomeMapper is a short read mapping tool designed for accurate read alignments. It quickly aligns millions of reads either with ungapped or gapped alignments. It can be used to align against multiple genomes simulanteously or against a single reference. If you are unsure which one is the appropriate GenomeMapper, you might want to use the latter https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2768987/

Address of the bookmark: http://1001genomes.org/software/genomemapper.html

Prokka: tool for the rapid annotation of prokaryotic genomes

Jit — Mon, 06 Mar 2017 03:49:57 -0600

Prokka is a software tool for the rapid annotation of prokaryotic genomes. A typical 4 Mbp genome can be fully annotated in less than 10 minutes on a quad-core computer, and scales well to 32 core SMP systems. It produces GFF3, GBK and SQN files that are ready for editing in Sequin and ultimately submitted to Genbank/DDJB/ENA.

Address of the bookmark: http://www.vicbioinformatics.com/software.prokka.shtml

AlignQC: A tool for assessing an alignment, and generating reports that are easy to share

Jit — Tue, 07 Aug 2018 04:41:07 -0500

Long read alignment analysis. Generate a reports on sequence alignments for mappability vs read sizes, error patterns, annotations and rarefraction curve analysis. The most basic analysis only requires a BAM file, and outputs a web browser compatible xhtml to visualize/share/store/extract analysis results.

https://f1000research.com/articles/6-100/

https://github.com/jason-weirather/AlignQC

Address of the bookmark: https://www.healthcare.uiowa.edu/labs/au/AlignQC/

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

rHAT: a seed-and-extension-based noisy long read alignment tool

Abhimanyu Singh — Sun, 23 Sep 2018 05:12:22 -0500

rHAT is a seed-and-extension-based noisy long read alignment tool. It is suitable for aligning 3rd generation sequencing reads which are in large read length with relatively high error rate, especially Pacbio's Single Molecule Read-time (SMRT) sequencing reads.

Address of the bookmark: https://github.com/dfguan/rHAT

Shouji: a fast and efficient pre-alignment filter for sequence alignment

Jit — Mon, 04 Nov 2019 07:09:45 -0600

The ability to generate massive amounts of sequencing data continues to overwhelm the processing capacity of existing algorithms and compute infrastructures. In this work, we explore the use of hardware/software co-design and hardware acceleration to significantly reduce the execution time of short sequence alignment, a crucial step in analyzing sequenced genomes.

We introduce Shouji, a highly parallel and accurate pre-alignment filter that remarkably reduces the need for computationally-costly dynamic programming algorithms. The first key idea of our proposed pre-alignment filter is to provide high filtering accuracy by correctly detecting all common subsequences shared between two given sequences. The second key idea is to design a hardware accelerator design that adopts modern FPGA (field-programmable gate array) architectures to further boost the performance of our algorithm.

More at https://github.com/CMU-SAFARI/Shouji

Address of the bookmark: https://github.com/CMU-SAFARI/Shouji

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

Mulan: MUltiple sequence Local AligNment and conservation visualization tool

Rahul Nayak — Thu, 20 Jul 2017 08:02:32 -0500

Mulan performs multiple (2 or more) sequence alignments with an efficient and rapid "full local" alignment strategy that ensures a recapitulation of evolutionary sequence rearrangements (such as inversions and reshuffling) in any of the species. It combines refine and tba tools to align either "draft" or "finished" quality sequences. Mulan provides a dynamic graphical interface to align and visualize conservation profiles for evolutionarily distant and closely related species.

Input formats, automated data upload from the UCSC Genome Browser, gene annotation, annotation of repetitive elements, and progress report were previously described in the zPicture instructions and we refer the users to these materials for more details. This introduction is mainly focused on some novel features unique to the Mulan.

Address of the bookmark: https://mulan.dcode.org/mulanInstructions.php

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/

Genomic Impact

Jitendra Narayan — Wed, 10 Jul 2013 01:33:50 -0500

The ongoing genomic research in USA contributed $31 billion to the U.S. gross national product and helped support 152,000 jobs.

Reference: http://www.unitedformedicalresearch.com/wp-content/uploads/2013/06/The-Impact-of-Genomics-on-the-US-Economy.pdf