BOL: All site bookmarks

GRIDSS: the Genomic Rearrangement IDentification Software Suite

Rahul Nayak — Sun, 17 May 2020 10:27:44 -0500

GRIDSS is a module software suite containing tools useful for the detection of genomic rearrangements. GRIDSS includes a genome-wide break-end assembler, as well as a structural variation caller for Illumina sequencing data. GRIDSS calls variants based on alignment-guided positional de Bruijn graph genome-wide break-end assembly, split read, and read pair evidence.

Address of the bookmark: https://github.com/PapenfussLab/gridss

gapFinisher: A reliable gap filling pipeline for SSPACE-LongRead scaffolder output

Rahul Nayak — Thu, 14 May 2020 15:13:30 -0500

gapFinisher to process SSPACE-LongRead output to fill gaps after the scaffolding. gapFinisher is based on the controlled use of a previously published gap filling tool FGAP and works on all standard Linux/UNIX command lines.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6733440/

Address of the bookmark: https://github.com/kammoji/gapFinisher

LR_Gapcloser: a tiling path-based gap closer that uses long reads to complete genome assembly

Rahul Nayak — Thu, 14 May 2020 15:09:52 -0500

LR_Gapcloser is a gap closing tool using long reads from studied species. The long reads could be downloaed from public read archive database (for instance, NCBI SRA database ) or be your own data. Then they are fragmented and aligned to scaffolds using BWA mem algorithm in BWA package. In the package, we provided a compiled bwa, so the user needn't to install bwa. LR_Gapcloser uses the alignments to find the bridging that cross the gap, and then fills the long read original sequence into the genomic gaps.

Address of the bookmark: https://github.com/CAFS-bioinformatics/LR_Gapcloser

Filtlong: quality filtering tool for long reads

Radha Agarkar — Wed, 13 May 2020 10:23:55 -0500

Filtlong is a tool for filtering long reads by quality. It can take a set of long reads and produce a smaller, better subset. It uses both read length (longer is better) and read identity (higher is better) when choosing which reads pass the filter.

Filtlong builds into a stand-alone executable:

git clone https://github.com/rrwick/Filtlong.git
cd Filtlong
make -j
bin/filtlong -h

Address of the bookmark: https://github.com/rrwick/Filtlong

Synteny and Rearrangement Identifier (SyRI)

Jit — Tue, 05 May 2020 10:37:10 -0500

SyRI is a comprehensive tool for predicting genomic differences between related genomes using whole-genome assemblies (WGA). The assemblies are aligned using whole-genome alignment tools, and these alignments are then used as input to SyRI. SyRI identifies syntenic path (longest set of co-linear regions), structural rearrangements (inversions, translocations, and duplications), local variations (SNPs, indels, CNVs etc) within syntenic and structural rearrangements, and un-aligned regions.

Address of the bookmark: https://schneebergerlab.github.io/syri/

NucDiff: In-depth characterization and annotation of differences between two sets of DNA sequences

Jit — Tue, 05 May 2020 10:35:48 -0500

NucDiff locates and categorizes differences between two closely related nucleotide sequences. It is able to deal with very fragmented genomes, structural rearrangements and various local differences. These features make NucDiff to be perfectly suitable to compare assemblies with each other or with available reference genomes.

NucDiff provides information about the types of differences and their locations. It is possible to upload the results into genome browser for visualization and further inspection. It was written in Python and uses the NUCmer package from MUMmer[1] for sequence comparison.

Address of the bookmark: https://github.com/uio-cels/NucDiff

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

RefKA: A fast and efficient long-read genome assembly approach for large and complex genomes

Rahul Nayak — Fri, 01 May 2020 03:00:40 -0500

RefKA, a reference-based approach for long read genome assembly. This approach relies on breaking up a closely related reference genome into bins, aligning k-mers unique to each bin with PacBio reads, and then assembling each bin in parallel followed by a final bin-stitching step.

Address of the bookmark: https://github.com/AppliedBioinformatics/RefKA

flexidot: Highly customizable, ambiguity-aware dotplots for visual sequence analyses

Jit — Fri, 24 Apr 2020 08:39:28 -0500

FlexiDot is a cross-platform dotplot suite generating high quality self, pairwise and all-against-all visualizations. To improve dotplot suitability for comparison of consensus and error-prone sequences, FlexiDot harbors routines for strict and relaxed handling of mismatches and ambiguous residues. The custom shading modules facilitate dotplot interpretation and motif identification by adding information on sequence annotations and sequence similarities to the images. Combined with collage-like outputs, FlexiDot supports simultaneous visual screening of a large sequence sets, allowing dotplot use for routine screening.

Address of the bookmark: https://github.com/molbio-dresden/flexidot

WEGO : simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results

BioStar — Sun, 12 Apr 2020 10:02:22 -0500

WEGO (Web Gene Ontology Annotation Plot) is a simple but useful tool for visualizing, comparing and plotting GO (Gene Ontology) annotation results. As the GO vocabulary became more and more popular, WEGO was widely adopted and used in many researches. Therefore we have updated WEGO 2.0 in 2018. Here are some changes we’ve made:
1. The limit of input file numbers was cancelled. Now the users could upload as many files as they want with one operation.
2. We have added the reference data of 9 species for users selection.
3. Besides the traditional WEGO histogram, WEGO 2.0 outputs an additional type of bar graph showing GO terms with significant gene number differences.

Address of the bookmark: http://wego.genomics.org.cn/