BOL: Related items

dna2bit: an ultra-fast and accurate genomic distance estimation software

LEGE — Sun, 31 Aug 2025 06:24:58 -0500

dna2bit is a software tool developed in C++11, leveraging the capabilities of OpenMP for parallel computing and the popcount technique for efficient bit manipulation. It has been thoroughly tested using the g++ and clang compilers on both Linux and MacOS platforms.

Address of the bookmark: https://github.com/lijuzeng/dna2bit

MIX: Combining multiple assemblies from NGS data

Rahul Nayak — Tue, 08 May 2018 04:58:05 -0500

Mix is a tool that combines two or more draft assemblies, without relying on a reference genome and has the goal to reduce contig fragmentation and thus speed-up genome finishing. The proposed algorithm builds an extension graph where vertices represent extremities of contigs and edges represent existing alignments between these extremities. These alignment edges are used for contig extension. The resulting output assembly corresponds to a path in the extension graph that maximizes the cumulative contig length.

The Mix algorithm, approach and results were published in BMC bioinformatics : http://www.biomedcentral.com/1471-2105/14/S15/S16.

Address of the bookmark: https://github.com/cbib/MIX

MSAProbs - Parallel and accurate multiple sequence alignment

Neel — Tue, 09 Jul 2019 23:58:44 -0500

MSAProbs is a well-established state-of-the-art multiple sequence alignment algorithm for protein sequences. The design of MSAProbs is based on a combination of pair hidden Markov models and partition functions to calculate posterior probabilities. Assessed using the popular benchmarks: BAliBASE, PREFAB, SABmark and OXBENCH, MSAProbs achieves statistically significant accuracy improvements over the existing top performing aligners, including ClustalW, MAFFT, MUSCLE, ProbCons and Probalign. In addition, MSAProbs is optimized for shared-memory CPUs by employing a multi-threaded design, and further parallelized for distributed-memory systems using MPI to overcome high memory overhead barrier and achieve good parallel and data-size scalability.

Address of the bookmark: http://msaprobs.sourceforge.net/homepage.htm#latest

Caretta – A multiple protein structure alignment and feature extraction suite

Rahul Nayak — Fri, 18 Dec 2020 02:09:44 -0600

Caretta – a multiple protein structure alignment and feature extraction suite

Caretta, a multiple structure alignment suite meant for homologous but sequentially divergent protein families which consistently returns accurate alignments with a higher coverage than current state-of-the-art tools. Caretta is available as a GUI and command-line application and additionally outputs an aligned structure feature matrix for a given set of input structures, which can readily be used in downstream steps for supervised or unsupervised machine learning.

Address of the bookmark: http://www.bioinformatics.nl/caretta/

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

AVID: A Global Alignment Program

Archana Malhotra — Wed, 24 May 2017 05:19:28 -0500

A new global alignment method called AVID. The method is designed to be fast, memory efficient, and practical for sequence alignments of large genomic regions up to megabases long. We present numerous applications of the method, ranging from the comparison of assemblies to alignment of large syntenic genomic regions and whole genome human/mouse alignments. We have also performed a quantitative comparison of AVID with other popular alignment tools. To this end, we have established a format for the representation of alignments and methods for their comparison. These formats and methods should be useful for future studies. The tools we have developed for the alignment comparisons, as well as the AVID program, are publicly available. See Web Site References section for AVID Web address and Web addresses for other programs discussed in this paper.

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC430967/

MOPGA 2024 Visiting Fellowship Program for Early Career Researchers

Fri, 10 Nov 2023 02:30:22 -0600

France, as a major player in the fight against climate change and guarantor of the spirit of the Paris Agreement, is launching a new MOPGA visiting fellowship program geared towards strengthening scientific contributions to climate change issues raised by the COPs.

This seventh Make Our Planet Great Again (MOPGA) call for applications is intended to welcome at least 40 early career researchers wishing to carry out their research in France. The program is funded by the French Ministry for Europe and Foreign Affairs, in collaboration with the French Ministry for Higher Education and Research, and implemented by Campus France.

The MOPGA 2024 Visiting Fellowship Program for Early Career Researchers will support researchers working on topics listed in the "Research Themes" section.

More at https://www.campusfrance.org/en/mopga-2024

PATRISTIC: a program for calculating patristic distances and graphically comparing the components of genetic change

Jit — Mon, 07 Aug 2017 18:40:38 -0500

PATRISTICv1.0 is a java program that calculates patristic distances from large trees in a range of file formats and allows graphical and statistical interpretation of distance matrices calculated by other programs.

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1352388/

Rebaler: program for conducting reference-based assemblies using long reads.

Jit — Tue, 18 Sep 2018 07:52:41 -0500

Rebaler is a program for conducting reference-based assemblies using long reads. It relies mainly on minimap2 for alignment and Racon for making consensus sequences.

I made Rebaler for bacterial genomes (specifically for the task of testing basecallers). It should in principle work for non-bacterial genomes as well, but I haven't tested it.

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

CroCo: A program to detect potential cross contaminations in HTS assembled transcriptomes using expression level quantification

Jit — Mon, 07 Jan 2019 18:17:44 -0600

CroCo is a program to detect cross contamination events in assembled transcriptomes using sequencing reads to determine the true origin of every transcripts.
Such cross contaminations can be expected if several RNA-Seq experiments were prepared during the same period at the same lab, or by the same people, or if they were processed or sequenced by the same sequencing service facility.
Our approach first determines a subset of transcripts that are suspiciously similar across samples using a pairwise BLAST procedure. CroCo then combine all transcriptomes into a metatranscriptome and quantifies the "expression level" of all transcripts successively using every sample read data (e.g. several species sequenced by the same lab for a particular study) while allowing read multi-mappings.
Several mapping tools implemented in CroCo can be used to estimate expression level (default is RapMap).
This information is then used to categorize each transcript in the following 5 categories :

clean: the transcript origin is from the focal sample.

cross contamination: the transcript origin is from an alien sample of the same experiment.

dubious: expression levels are too close between focal and alien samples to determine the true origin of the transcript.

low coverage: expression levels are too low in all samples, thus hampering our procedure (which relies on differential expression) to confidently assign it to any category.

over expressed: expression levels are very high in at least 3 samples and CroCo will not try to categorize it. Indeed, such a pattern does not correspond to expectations for cross contaminations, but often reflect highly conserved genes such as ribosomal gene, or external contamination shared by several samples (e.g. Escherichia coli contaminations).

Address of the bookmark: https://gitlab.mbb.univ-montp2.fr/mbb/CroCo