BOL: Related items

Magic-BLAST: a tool for mapping large next-generation RNA or DNA sequencing runs against a whole genome or transcriptome.

Jit — Tue, 26 Dec 2017 22:23:39 -0600

Magic-BLAST is a tool for mapping large next-generation RNA or DNA sequencing runs against a whole genome or transcriptome. Each alignment optimizes a composite score, taking into account simultaneously the two reads of a pair, and in case of RNA-seq, locating the candidate introns and adding up the score of all exons. This is very different from other versions of BLAST, where each exon is scored as a separate hit and read-pairing is ignored.

Magic-BLAST incorporates within the NCBI BLAST code framework ideas developed in the NCBI Magic pipeline, in particular hit extensions by local walk and jump (http://www.ncbi.nlm.nih.gov/pubmed/26109056), and recursive clipping of mismatches near the edges of the reads, which avoids accumulating artefactual mismatches near splice sites and is needed to distinguish short indels from substitutions near the edges.

Address of the bookmark: https://ncbi.github.io/magicblast/

List of visualization tools for genome alignments

Rahul Nayak — Fri, 02 Feb 2018 13:25:33 -0600

Genome browsers are useful not only for showing final results but also for improving analysis protocols, testing data quality, and generating result drafts. Its integration in analysis pipelines allows the optimization of parameters, which leads to better results. But sometime, we need publication ready figure of genomes. Following are the list of genome alignment visualization tools, which could be useful for analysis and interpretation of results:

ABySS Explorer

Interactive Java application that uses a novel graph-based representation to display a sequence assembly and associated metadata

http://www.bcgsc.ca/platform/bioinfo/software/abyss-explorer

BamView

Genome browser and annotation tool that allows visualization of sequence features, next-generation sequencing (NGS) data and the results of analyses within the context of the sequence, and also its six-frame translation

http://www.sanger.ac.uk/resources/software/artemis/

DNannotator

Annotation web toolkit for regional genomic sequences

http://bioapp.psych.uic.edu/DNannotator.htm

JVM

Java Visual Mapping tool for NGS reads

http://www.springer.com/cda/content/document/cda_downloaddocument/9789401792448-c2.pdf?SGWID=0-0-45-1487072-p176815501

LookSeq

Web-based visualization of sequences derived from multiple sequencing technologies. Low- or high-depth read pileups and easy visualization of putative single nucleotide and structural variation

http://lookseq.sourceforge.net

MagicViewer

Visualization of short read alignment, identification of genetic variation and association with annotation information of a reference genome

http://bioinformatics.zj.cn/magicviewer/

MapView

Alignments of huge-scale single-end and pair-end short reads

http://omictools.com/mapview-s1367.html

MultiPipMaker

Computes alignments of similar regions in two DNA sequences. The resulting alignments are summarized with a ‘percent identity plot’ (pip)

http://pipmaker.bx.psu.edu/pipmaker/

PileLineGUI

Handling genome position files in NGS studies

http://sing.ei.uvigo.es/pileline/pilelinegui.html

SAMtools tview

Simple and fast text alignment viewer; NGS compatible

http://www.htslib.org/

SEWAL

Uses a locality-sensitive hashing algorithm to enumerate all unique sequences in an entire Illumina sequencing run

http://www.sourceforge.net/projects/sewal

STAR

A web-based integrated solution to management and visualization of sequencing data

http://wanglab.ucsd.edu/star/browser

SVA

Software for annotating and visualizing sequenced human genomes

http://www.svaproject.org

Viewer (IGV)

Visualization of large heterogeneous datasets, providing a smooth and intuitive user experience at all levels of genome resolution

https://www.broadinstitute.org/igv/

ZOOM Lite

NGS data mapping and visualization software

http://bioinfor.com/zoom/lite/

ARCS: scaffolding genome drafts with linked reads

Rahul Nayak — Tue, 06 Mar 2018 16:35:26 -0600

ARCS, an application that utilizes the barcoding information contained in linked reads to further organize draft genomes into highly contiguous assemblies. We show how the contiguity of an ABySS H.sapiensgenome assembly can be increased over six-fold, using moderate coverage (25-fold) Chromium data. We expect ARCS to have broad utility in harnessing the barcoding information contained in linked read data for connecting high-quality sequences in genome assembly drafts.

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

CrossMap: a program for convenient conversion of genome coordinates

Jit — Thu, 31 May 2018 06:00:47 -0500

CrossMap is a program for convenient conversion of genome coordinates (or annotation files) between different assemblies (such as Human hg18 (NCBI36) <> hg19 (GRCh37), Mouse mm9 (MGSCv37) <> mm10 (GRCm38)). It supports most commonly used file formats including SAM/BAM, Wiggle/BigWig, BED, GFF/GTF, VCF. CrossMap is designed to liftover genome coordinates between assemblies. It’s not a program for aligning sequences to reference genome. We do not recommend using CrossMap to convert genome coordinates between species.

Address of the bookmark: http://crossmap.sourceforge.net

swgis v2.0 : a seqword genomic island sniffer

Abhimanyu Singh — Thu, 01 Nov 2018 12:35:52 -0500

swgis v2.0 is the modified version of the seqword genomic island sniffer. this version is specifically optimized for predicting genomic islands in eukaryotic genomes. swgis v2.0 was tested on several eukaryotic species of different lineages. all identified genomic islands were deposited in the eugi database.

download swgis v2.0

Address of the bookmark: http://eugi.bi.up.ac.za/eugi_download_swgis.php

NovoGraph: building whole genome graphs from long-read-based de novo assemblies

Jit — Thu, 15 Nov 2018 12:48:30 -0600

NovoGraph: building whole genome graphs from long-read-based de novo assemblies

An algorithmically novel approach to construct a genome graph representation of long-read-based de novo sequence assemblies. We then provide a proof of principle by creating a genome graph of seven ethnically-diverse human genomes.

https://f1000research.com/articles/7-1391/v1

Address of the bookmark: https://github.com/NCBI-Hackathons/NovoGraph

ARCS: scaffolding genome drafts with linked reads

Jit — Mon, 17 Dec 2018 17:40:28 -0600

ARCS requires two input files:

Draft assembly fasta file
Interleaved linked reads file (Barcode sequence expected in the BX tag of the read header or in the form "@readname_barcode" ; Run Long Ranger basic on raw chromium reads to produce this interleaved file)

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

LTR_retriever: accurately identifies and annotates LTR retrotransposons and use LAI to evaluates the continuity of genome assemblies.

Neel — Sun, 13 Jan 2019 07:14:31 -0600

LTR_retriever is a command line program (in Perl) for accurate identification of LTR retrotransposons (LTR-RTs) from outputs of LTRharvest, LTR_FINDER, and/or MGEScan-LTR and generating non-redundant LTR-RT library for genome annotations.

By default, the program will generate whole-genome LTR-RT annotation and the LTR Assembly Index (LAI) for evaluations of the assembly continuity of the input genome. Users can also run LAI separately (see Usage).

Address of the bookmark: https://github.com/oushujun/LTR_retriever

SeqMule: Automated human exome/genome variants detection

BioStar — Tue, 18 Feb 2020 03:22:54 -0600

SeqMule takes single-end or paird-end FASTQ or BAM files, generates a script consisting of more than 10 popular alignment, analysis tools and runs the script line by line. Users can change the pipeline or fine-tune the parameters by modifying its configuration file.

Address of the bookmark: https://doc-openbio.readthedocs.io/projects/seqmule/en/latest/

KAD: Assessing genome assemblies using K-mer copies in assemblies and K-mer abundance in Illumina reads

Jit — Fri, 19 Jun 2020 07:34:12 -0500

KAD is designed for evaluating the accuracy of nucleotide base quality of genome assemblies. Briefly, abundance of k-mers are quantified for both sequencing reads and assembly sequences. Comparison of the two values results in a single value per k-mer, K-mer Abundance Difference (KAD), which indicates how well the assembly matches read data for each k-mer.

where, c is the count of a k-mer from reads, m is the mode of counts of read k-mers, and n is the copy of the k-mer in the assembly.

Address of the bookmark: https://github.com/liu3zhenlab/KAD