BOL: Related items

Ribbon !!

Jit — Fri, 21 Oct 2016 04:54:30 -0500

Visualization has played an extremely important role in the current genomic revolution to inspect and understand variants, expression patterns, evolutionary changes, and a number of other relationships. However, most of the information in read-to-reference or genome-genome alignments is lost for structural variations in the one-dimensional views of most genome browsers showing only reference coordinates. Instead, structural variations captured by long reads or assembled contigs often need more context to understand, including alignments and other genomic information from multiple chromosomes. We have addressed this problem by creating Ribbon (genomeribbon.com) an interactive online visualization tool that displays alignments along both reference and query sequences, along with any associated variant calls in the sample. This way Ribbon shows patterns in alignments of many reads across multiple chromosomes, while allowing detailed inspection of individual reads (Supplementary Note 1). For example, here we show a gene fusion in the SK-BR-3 breast cancer cell line linking the genes CYTH1 and EIF3H. While it has been found in the transcriptome previously, genome sequencing did not identify a direct chromosomal fusion between these two genes. After SMRT sequencing, Ribbon shows that there are indeed long reads that span from one gene to the other, going through not one but two variants, for the first time showing the genomic link between these two genes (Figure 1a). More gene fusions of this cancer cell line are investigated in Supplementary Note 2. Figure 1b shows another complex event in this sample made simple in Ribbon: the translocation of a 4.4 kb sequence deleted from chr19 and inserted into chr16 (Figure 1b). Thus, Ribbon enables understanding of complex variants, and it may also help in the detection of sequencing and sample preparation issues, testing of aligners and variant-callers, and rapid curation of structural variant candidates (Supplementary Note 3). In addition to SAM and BAM files with long, short, or paired-end reads, Ribbon can also load coordinate files from whole genome aligners such as MUMmer. Therefore, Ribbon can be used to test assembly algorithms or inspect the similarity between species. Supplementary Note 4 shows a comparison of gorilla and human genomes using Ribbon, highlighting major structural differences. In conclusion, Ribbon is a powerful interactive web tool for viewing complex genomic alignments.

Script at https://github.com/MariaNattestad/ribbon

Address of the bookmark: http://genomeribbon.com/

eFORGE.v1.2

Jit — Fri, 28 Oct 2016 09:06:59 -0500

The eFORGE tool provides a method to view the tissue specific regulatory component of a set of EWAS DMPs. eFORGE analysis takes a set of DMPs, such as those hits above genome-wide significance threshold in an EWAS study, and analyses whether there is enrichment for overlap of putative functional elements compared to matched background DMPs. It assesses enrichment on a per cell type basis, since functional elements are differentially active in different cell types, and hence can expose tissue-specific signals of enrichment for the given test DMP set. This can reveal the sites of action underlying the EWAS signal, and provide confirmation of the validity of the EWAS where a tissue-specific mechanism is known or expected for the phenotype. Conversely unknown tissue involvements can also be revealed.

Address of the bookmark: http://eforge.cs.ucl.ac.uk/eFORGE.v1.2/?documentation

E-MEM: Efficient computation of Maximal Exact Matches

Jit — Thu, 15 Dec 2016 09:30:43 -0600

E-MEM is a C++/OpenMP program designed to efficiently compute MEMs between large genomes. See the README file for instructions on how to use E-MEM.

E-MEM source code

The source code can be downloaded here.

If you use E-MEM, please cite:

N. Khiste, L. Ilie, E-MEM: Efficient computation of Maximal Exact Matches for very large genomes, Bioinformatics 31(4) (2015) 509 -- 514.

For any questions, please contact Lucian Ilie: ilie@uwo.ca

Address of the bookmark: http://www.csd.uwo.ca/~ilie/E-MEM/

Progressive Cactus

Jit — Tue, 17 Jan 2017 03:40:06 -0600

v0.0 by Glenn Hickey (hickey@soe.ucsc.edu)

Progressive Cactus is a whole-genome alignment package.

Requirements

git
gcc 4.2 or newer
python 2.7
wget
64bit processor and build environment
150GB+ of memory on at least one machine when aligning mammal-sized genomes; less memory is needed for smaller genomes.
Parasol or SGE for cluster support.
750M disk space

Instructions

IMPORTANT NOTE: Progressive Cactus does not presently support installation into paths that contain spaces. Until this is resolved, you can use a softlink as a workaround: ln -s "path with spaces" "installation path without spaces"

In the parent directory of where you want Progressive Cactus installed:

git clone git://github.com/glennhickey/progressiveCactus.git
cd progressiveCactus
git pull
git submodule update --init
make

It is also convenient to add the location of progressiveCactus/bin to your PATH environment variable. In order to run the included tools (ex hal2maf) in the submodules/ directory structure, first source progressiveCactus/environment to load the installed environment.

If any errors occur during the build process, you are unlikely to be able to use the tool. Please submit a GitHub issue so we can help out: not only will you help yourself, but others who wish to use the tool as well.

Note that all dependencies are also built and included in the submodules/ directory. This increases the size and build time but greatly simplifies installation and version management. The installation does not create or modify any files outside the progressiveCactus/ directory.

Address of the bookmark: https://github.com/glennhickey/progressiveCactus

Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome

BioStar — Wed, 22 Jul 2020 10:11:13 -0500

We have developed the Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome. We envisage its use during annotation jamborees, genome comparison and for use by developers for rapid feedback during annotation software development and testing. SOBA also provides annotation consistency feedback to ensure correct use of terminology within annotations, and guides users to add new terms to the Sequence Ontology when required. SOBA is available at http://www.sequenceontology.org/cgi-bin/soba.cgi.

More at https://pubmed.ncbi.nlm.nih.gov/20494974/

Address of the bookmark: http://www.sequenceontology.org/cgi-bin/soba.cgi

HASLR: a hybrid assembler which uses both second and third generation sequencing reads

BioStar — Mon, 04 May 2020 02:04:03 -0500

HASLR, a hybrid assembler which uses both second and third generation sequencing reads to efficiently generate accurate genome assemblies. Our experiments show that HASLR is not only the fastest assembler but also the one with the lowest number of misassemblies on all the samples compared to other tested assemblers. Furthermore, the generated assemblies in terms of contiguity and accuracy are on par with the other tools on most of the samples. Availability. HASLR is an open source tool available at https://github.com/vpc-ccg/haslr.

Address of the bookmark: https://github.com/vpc-ccg/haslr

HapSolo: An optimization approach for removing secondary haplotigs during diploid genome assembly and scaffolding.

Jit — Mon, 26 Oct 2020 21:23:36 -0500

Despite marked recent improvements in long-read sequencing technology, the assembly of diploid genomes remains a difficult task. A major obstacle is distinguishing between alternative contigs that represent highly heterozygous regions. If primary and secondary contigs are not properly identified, the primary assembly will overrepresent both the size and complexity of the genome, which complicates downstream analysis such as scaffolding.

More at https://github.com/esolares/HapSolo

Address of the bookmark: https://github.com/esolares/HapSolo

HapSolo: An optimization approach for removing secondary haplotigs during diploid genome assembly and scaffolding

Jit — Sat, 08 May 2021 21:25:00 -0500

HapSolo, that identifies secondary contigs and defines a primary assembly based on multiple pairwise contig alignment metrics. HapSolo evaluates candidate primary assemblies using BUSCO scores and then distinguishes among candidate assemblies using a cost function. The cost function can be defined by the user but by default considers the number of missing, duplicated and single BUSCO genes within the assembly. HapSolo performs hill climbing to minimize cost over thousands of candidate assemblies.

Address of the bookmark: https://github.com/esolares/HapSolo

Illumina based assembly pipeline steps !

Surabhi Chaudhary — Fri, 10 Dec 2021 06:22:54 -0600

Illumina

Merge re-sequenced FastQ files (cat)
Read QC (FastQC)
Adapter trimming (fastp)
Removal of host reads (Kraken 2; optional)
Variant calling
1. Read alignment (Bowtie 2)
2. Sort and index alignments (SAMtools)
3. Primer sequence removal (iVar; amplicon data only)
4. Duplicate read marking (picard; optional)
5. Alignment-level QC (picard, SAMtools)
6. Genome-wide and amplicon coverage QC plots (mosdepth)
7. Choice of multiple variant calling and consensus sequence generation routes (iVar variants and consensus; default for amplicon data || BCFTools, BEDTools; default for metagenomics data)
  - Variant annotation (SnpEff, SnpSift)
  - Consensus assessment report (QUAST)
  - Lineage analysis (Pangolin)
  - Clade assignment, mutation calling and sequence quality checks (Nextclade)
  - Individual variant screenshots with annotation tracks (ASCIIGenome)
8. Intersect variants across callers (BCFTools)
De novo assembly
1. Primer trimming (Cutadapt; amplicon data only)
2. Choice of multiple assembly tools (SPAdes || Unicycler || minia)
  - Blast to reference genome (blastn)
  - Contiguate assembly (ABACAS)
  - Assembly report (PlasmidID)
  - Assembly assessment report (QUAST)
Present QC and visualisation for raw read, alignment, assembly and variant calling results (MultiQC)

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

Abhi — Tue, 05 Sep 2023 07:31:35 -0500

MitoHiFi v3.2 is a python pipeline distributed under MIT License !

MitoHiFi was first developed to assemble the mitogenomes for a wide range of species in the Darwin Tree of Life Project (DToL)

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-023-05385-y

Address of the bookmark: https://github.com/marcelauliano/MitoHiFi