BOL: Related items

Bioinformatics tools for telomere to telomere assembly !

BioStar — Tue, 17 Aug 2021 13:17:09 -0500

● Merfin – k-mer-based assembly and variant calling evaluation for improved consensus accuracy (Arang Rhie)
● PanGenie – algorithm that leverages a pangenome reference built from haplotype-resolved genome assemblies in conjunction with k-mer count information from raw, short-read sequencing data to genotype a wide spectrum of genetic variation (Tobias Marschall)
● SQANTI3 – an automated pipeline for the classification of long-read transcripts that can assess the quality of data and the preprocessing pipeline (Rocío Amorín de Hegedüs @rocioadh)
● tama (Transcriptome Annotation by Modular Algorithms) – software designed for processing Iso-Seq data and other long-read transcriptome data (Richard Kuo @GenomeRIK)
● pbaa (PacBio Amplicon Analysis) – separates complex mixtures of amplicon targets from genomic samples to cluster and generate high-quality consensus sequences from HiFi reads (Zev Kronenberg @zevkronenberg)
● bellerophon – analyzes MHC typing and other low-complexity gene amplicon data; performs allele calling while detecting polymorphic sites within the sequences and removing potential chimeric sequence variants (Yuanyuan Cheng @Yuanyuan929)
● svpack – tools for filtering, comparing, and annotating structural variant (SV) calls in VCF format (Aaron Wenger)
● JumboDB – tool for de Bruijn graph construction (Anton Bankevich @AntonBankevich)
● uLTRA – tool for splice alignment of long transcriptomic reads to a genome, guided by a database of exon annotations. (Kristoffer Sahlin @krsahlin)
● LeafGo – workflow to rapidly produce high-quality de novo plant genomes (Luca Ermini @ermini_luca)

Reference:

https://www.pacb.com/blog/young-investigators-share-stellar-science-career-advice-and-bioinformatics-tools-at-smrt-leiden-2021/

Comparative genomics visualisation tools !

Neel — Thu, 17 Feb 2022 05:37:55 -0600

Comparative genomics visualisation tools !

Address of the bookmark: https://cmdcolin.github.io/awesome-genome-visualization/?latest=true&selected=%23BRIG&tag=Comparative

Bioinformatic tools for pathogens informatics at CVR

Abhi — Sat, 08 Jun 2024 15:59:46 -0500

Novel sequencing and analytical approaches focused on studying viruses and virus-host interactions. Below you will find summaries and links to a number of bioinformatic tools that have been developed @ CVR.

DIGS

The database-integrated genome-screening (DIGS) tool provides a framework for implementing automated in silico screening of sequence databases using BLAST in combination with a relational database (MySQL).

DisCVR

DisCVR is a Diagnostic tool for detecting known human viruses in clinical samples from Next-Generation Sequencing (NGS) data. The tool uses a simple and straightforward Graphical User Interface and is optimized on Windows OS without compromising speed and accuracy.

DiversiTools

DiversiTools is a computational tool that is specifically tailored towards viral HTS data sets and the analysis of the underlying viral populations that they represent. It was initially developed in collaboration with a number of virologists interested in characterising the intra-host diversity of viral populations and studying their evolution across transmission chains at the micro-evolutionary scale.

GLUE

GLUE is a flexible data-centric bioinformatics environment for virus sequence data, with a focus on virus evolution and genomic variation. GLUE has been applied to a range of viruses. A GLUE-based resource focused on Hepatitis C virus is HCV-GLUE.

Tanoti

Tanoti is a BLAST guided reference based short read aligner. It is developed for maximising alignment in highly variable next generation sequence data sets (Illumina).

ViCTree

ViCTree is a bioinformatic framework that automatically selects new candidate virus sequences from GenBank, generates multiple sequence alignments, calculates a maximum likelihood phylogeny and integrates the sequences into the existing phylogenetic trees. For more information click here.

Viral Host Predictor

Viral Host Predictor provides a fast and simple way to predict the hosts and vectors of RNA viruses from viral sequences.

GRACy

GRACy is a bioinformatic tool designed for the analysis of Illumina data originated from Human cytomegalovirus samples. GRACy can be used to perform read quality filtering, genotyping, de novo assembly, variant detection, annotation and data submission to public database.

LoReTTA

LoReTTA (Long Read Template Targeted Assembler) is a reference assisted de novo assembler specifically designed to deal with PacBio reads generated from viral genomes.

BingleSeq

BingleSeq is a R-package enables the user-friendly analysis of count tables obtained by both Bulk RNA-Seq and single-cell RNA-Seq protocols. The development of BingleSeq focused on providing a flexible and intuitive user experience.

GPOPSIM: a simulation tool for whole-genome genetic data

Jit — Wed, 17 Jan 2018 03:47:46 -0600

GPOPSIM is a simulation tool for pedigree, phenotypes, and genomic data, with a variety of population and genome structures and trait genetic architectures. It provides flexible parameter settings for a wide discipline of users, especially can simulate multiple genetically correlated traits with desired genetic parameters and underlying genetic architectures.

Address of the bookmark: https://github.com/SCAU-AnimalGenetics/GPOPSIM

ALLHiC: Phasing and scaffolding polyploid genomes based on Hi-C data

BioStar — Thu, 20 Dec 2018 12:03:32 -0600

The major problem of scaffolding polyploid genome is that Hi-C signals are frequently detected between allelic haplotypes and any existing stat of art Hi-C scaffolding program links the allelic haplotypes together. To solve the problem, we developed a new Hi-C scaffolding pipeline, called ALLHIC, specifically tailored to the polyploid genomes. ALLHIC pipeline contains a total of 5 steps: prune, partition, rescue, optimize and build.

Address of the bookmark: https://github.com/tangerzhang/ALLHiC/wiki

kallisto: a program for quantifying abundances of transcripts from bulk and single-cell RNA-Seq data

Jit — Mon, 07 Jan 2019 10:35:14 -0600

kallisto is a program for quantifying abundances of transcripts from bulk and single-cell RNA-Seq data, or more generally of target sequences using high-throughput sequencing reads. It is based on the novel idea of pseudoalignment for rapidly determining the compatibility of reads with targets, without the need for alignment. On benchmarks with standard RNA-Seq data, kallisto can quantify 30 million human reads in less than 3 minutes on a Mac desktop computer using only the read sequences and a transcriptome index that itself takes less than 10 minutes to build. Pseudoalignment of reads preserves the key information needed for quantification, and kallisto is therefore not only fast, but also as accurate as existing quantification tools. In fact, because the pseudoalignment procedure is robust to errors in the reads, in many benchmarks kallisto significantly outperforms existing tools. kallisto is described in detail in:

Nicolas L Bray, Harold Pimentel, Páll Melsted and Lior Pachter, Near-optimal probabilistic RNA-seq quantification, Nature Biotechnology 34, 525–527 (2016), doi:10.1038/nbt.3519

Address of the bookmark: https://pachterlab.github.io/kallisto/about

heatmaply: popular graphical method for visualizing high-dimensional data

Neel — Sat, 11 Jan 2020 07:34:14 -0600

This work is based on ggplot2 and plotly.js engine. It produces similar heatmaps as d3heatmap, with the advantage of speed (plotly.js is able to handle larger size matrix), and the ability to zoom from the dendrogram.

heatmaply also provides an interface based around the plotly R package. This interface can be used by choosing plot_method = "plotly" instead of the default plot_method = "ggplot". This interface can provide smaller objects and faster rendering to disk in many cases and provides otherwise almost identical features.

Documentation for this package is also available as a pkgdown site: http://talgalili.github.io/heatmaply/

Address of the bookmark: http://talgalili.github.io/heatmaply/articles/heatmaply.html

Juicebox: Visualization and analysis software for Hi-C data

Jit — Fri, 21 Feb 2020 00:33:38 -0600

Juicebox is visualization software for Hi-C data. This distribution includes the source code for Juicebox, Juicer Tools, and Assembly Tools. Download Juicebox here, or use Juicebox on the web. Detailed documentation is available on the wiki. Instructions below pertain primarily to usage of command line tools and the Juicebox jar files.

Juicebox can now be used to visualize and interactively (re)assemble genomes. Check out the Juicebox Assembly Tools Module website https://aidenlab.org/assembly for more details on how to use Juicebox for assembly.

GUI at https://aidenlab.org/juicebox/

Address of the bookmark: https://github.com/aidenlab/Juicebox

Useful links to therapy, disease, drug and drug-target network data:

Jit — Mon, 01 Jun 2020 11:47:51 -0500

Useful links to therapy, disease, drug and drug-target network data:

DrugBank:

a bioinformatics- cheminformatics resource combining detailed drug data with comprehensive drug target information with >4900 drug (~3500 experimental) and >1500 non-redundant protein entries http://www.drugbank.ca/

Drug-Target Network:

network data of 890 drugs and 394 target human proteins http://www.nature.com/nbt/journal/v25/ n10/suppinfo/nbt1338_S1.html

Drug-Therapy Network:

three layers of drug-therapy networks according to the ATC classification http://www.biomedcentral.com/1471-2210/8/5/additional/

FDA Orange Book:

approved drug products with therapeutic equivalence evaluations http://www.fda.gov/cder/ob/HIDdb: Thomson Investigational drugs database including information on 107000 patents, 25000 investigational drugs and 80000 chemical structures http://scientific.thomson.com/products/iddb/HOMIM: a knowledgebase of human genes and genetic disorders http://www.ncbi.nlm.nih.gov/ sites/entrez?db=omim

PDTD:

3D drug target structure database with a target identification option http://www.dddc.ac.cn/pdtd/

Predicted drug targets:

a set of 1383 predicted drug targets http://www.biomedcentral.com/1471-2105/8/353/additional/ [25] Protein ligand network: a network of 4208 ligands and ~15000 binding sites http://pbil.kaist.ac.kr/~parkkw/Lnet/

TDR Targets Database:

identification and ranking targets against neglected tropical diseases http://tdrtargets.org/

Therapeutic Target Database:

lists >1500 therapeutic targets, disease conditions and corresponding drugs http://xin.cz3.nus.edu.sg/group/cjttd/ttd.asp

MAGIC: A tool for predicting transcription factors and cofactors driving gene sets using ENCODE data

BioStar — Thu, 26 Nov 2020 11:05:04 -0600

The algorithm presented herein, Mining Algorithm for GenetIc Controllers (MAGIC), uses ENCODE ChIP-seq data to look for statistical enrichment of TFs and cofactors in gene bodies and flanking regions in gene lists without an a priori binary classification of genes as targets or non-targets. When compared to other TF mining resources, MAGIC displayed favourable performance in predicting TFs and cofactors that drive gene changes in 4 settings:

1) A cell line expressing or lacking single TF,

2) Breast tumors divided along PAM50 designations

3) Whole brain samples from WT mice or mice lacking a single TF in a particular neuronal subtype

4) Single cell RNAseq analysis of neurons divided by Immediate Early Gene expression levels.

In summary, MAGIC is a standalone application that produces meaningful predictions of TFs and cofactors in transcriptomic experiments.

More at https://uwmadison.app.box.com/s/8j90e5h2rjrsz3bacaxnq8kor2o64vyg

Address of the bookmark: https://github.com/asroopra/MAGIC