BOL: Related items

Dahak: benchmarking and containerization of tools for analysis of complex non-clinical metagenomes.

BioStar — Thu, 09 Apr 2020 04:56:09 -0500

Dahak is a software suite that integrates state-of-the-art open source tools for metagenomic analyses. Tools in the dahak software suite will perform various steps in metagenomic analysis workflows including data pre-processing, metagenome assembly, taxonomic and functional classification, genome binning, and gene assignment. We aim to deliver the analytical framework as a robust and reliable containerized workflow system, which will be free from dependency, installation, and execution problems typically associated with other open-source bioinformatics solutions. This will maximize the transparency, data provenance (i.e., the process of tracing the origins of data and its movement through the workflow), and reproducibility.

More at https://dahak-metagenomics.github.io/dahak/

Address of the bookmark: https://github.com/dahak-metagenomics/dahak

postdoctoral fellow for a large-scale microbial comparative genomics !

Thu, 29 Apr 2021 08:44:53 -0500

Asaf Levy hiring a postdoctoral fellow for a large-scale microbial comparative genomics project at the Hebrew University of Jerusalem (Israel).
The project is a continuation of Levy Asaf et al. Nature Genetics 2018 paper.
Requirements:
1.Experience with programming in at least one programming language, preferably Python.
2.A PhD in bioinformatics/computational biology
3.At least one first authorship publication in a good journal, preferably more.
4.Good communication skills in English
5.Ability to enter and study in Israel (not applicable for Pakistani people, for example).
6.Ability to work in a team.
Please send CV to alevy@mail.huji.ac.il

Understanding Fastqc Output

Jit — Fri, 15 Apr 2016 05:47:40 -0500

Understanding Following table and graphs

Duplication level
kmer profile
per base GC content
per base N content
per base quality
per base sequence content
per sequence GC content
per sequence quality
sequence length distribution

More at http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/3%20Analysis%20Modules/

Address of the bookmark: http://www.bioinformatics.babraham.ac.uk/projects/fastqc/Help/3%20Analysis%20Modules/

AfterQC: Automatic Filtering, Trimming, Error Removing and Quality Control for fastq data

Jit — Fri, 29 Jun 2018 03:26:03 -0500

Automatic Filtering, Trimming, Error Removing and Quality Control for fastq data AfterQC can simply go through all fastq files in a folder and then output three folders: good, bad and QC folders, which contains good reads, bad reads and the QC results of each fastq file/pair. Currently it supports processing data from HiSeq 2000/2500/3000/4000, Nextseq 500/550, MiniSeq...and other Illumina 1.8 or newer formats The author has reimplemented this tool in C++ with multithreading support to make it much faster. The new tool is called fastp and can be found at: https://github.com/OpenGene/fastp . If you prefer a C++ based tool, please use fastp instead. https://github.com/OpenGene/AfterQC

Address of the bookmark: https://github.com/OpenGene/AfterQC

eQuant : energy-based quality assessment of protein

Shruti Paniwala — Sat, 24 Jun 2017 19:24:24 -0500

Protein structures are of varying quality. Especially, in-silico modeled structures are prone to contain serious errors, which limit the usefulness and reliability of these particular protein structures.

eQuant is a service for structure quality assessment of single proteins, which utilizes a coarse-grained energy model. The overall quality is calculated as well as the reliability of individual residues. You can submit single PDB files or archives containing a set of proteins.

https://biosciences.hs-mittweida.de/equant/

Address of the bookmark: https://biosciences.hs-mittweida.de/equant/

Referee: Genome assembly quality scores

Jit — Sun, 04 Nov 2018 16:44:30 -0600

Modern genome sequencing technologies provide a succint measure of quality at each position in every read, however all of this information is lost in the assembly process. Referee summarizes the quality information from the reads that map to a site in an assembled genome to calculate a quality score for each position in the genome assembly.

We accomplish this by first calculating genotype likelihoods for every site. For a given site in a diploid genome, there are 10 possible genotypes (AA, AC, AG, AT, CC, CG, CT, GG, GT, TT). Referee takes as input the genotype likelihoods calculated for all 10 genotypes given the called reference base at each position.

Referee is a program to calculate a quality score for every position in a genome assembly. This allows for easy filtering of low quality sites for any downstream analysis.

https://github.com/gwct/referee

Address of the bookmark: https://gwct.github.io/referee/#

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

Single Cell RNAseq data analysis tutorial !!

Robert M Willioms — Mon, 27 Nov 2017 16:24:29 -0600

A major breakthrough (replaced microarrays) in the late 00’s and has been widely used since
Measures the average expression level for each gene across a large population of input cells
Useful for comparative transcriptomics, e.g. samples of the same tissue from different species
Useful for quantifying expression signatures from ensembles, e.g. in disease studies
Insufficient for studying heterogeneous systems, e.g. early development studies, complex tissues (brain)
Does not provide insights into the stochastic nature of gene expression

Following are the useful links:

Single Cell RNAseq data analysis Tutorial

A step-by-step workflow for low-level analysis of single-cell RNA-seq data

A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor

SCell: single-cell RNA-seq analysis software

https://github.com/diazlab/SCell

Beta-Poisson model for single-cell RNA-seq data analyses

https://github.com/nghiavtr/BPSC

Sincera: A Computational Pipeline for Single Cell RNA-Seq Profiling Analysis

https://research.cchmc.org/pbge/sincera.html

SC3 – consensus clustering of single-cell RNA-Seq data

http://biorxiv.org/content/early/2016/09/02/036558

Citrus: A toolkit for single cell sequencing analysis

http://biorxiv.org/content/early/2016/09/14/045070

Single-Cell Resolution of Temporal Gene Expression during Heart Development

http://www.cell.com/developmental-cell/fulltext/S1534-5807(16)30682-7

Scalable latent-factor models applied to single-cell RNA-seq data separate biological drivers from confounding effects

http://biorxiv.org/content/early/2016/11/15/087775

Single cell transcriptomes identify human islet cell signatures and reveal cell-type-specific expression changes in type 2 diabetes

http://genome.cshlp.org/content/early/2016/11/18/gr.212720.116.abstract

SCODE: An efficient regulatory network inference algorithm from single-cell RNA-Seq during differentiation

http://biorxiv.org/content/early/2016/11/21/088856

SCOUP is a probabilistic model to analyze single-cell expression data during differentiation

https://github.com/hmatsu1226/SCOUP

scLVM is a modelling framework for single-cell RNA-seq data

https://github.com/PMBio/scLVM

Selective Locally linear Inference of Cellular Expression Relationships (SLICER) algorithm for inferring cell trajectories

https://github.com/jw156605/SLICER

SinQC: A Method and Tool to Control Single-cell RNA-seq Data Quality

http://www.morgridge.net/SinQC.html

TSCAN: Pseudo-time reconstruction and evaluation in single-cell RNA-seq analysis

https://github.com/zji90/TSCAN

Visualization and cellular hierarchy inference of single-cell data using SPADE

http://www.nature.com/nprot/journal/v11/n7/full/nprot.2016.066.html

OEFinder: Identify ordering effect genes in single cell RNA-seq data

https://github.com/lengning/OEFinder

Flye: Fast and accurate de novo assembler for single molecule sequencing reads

BioJoker — Tue, 02 Apr 2019 21:54:55 -0500

Flye is a de novo assembler for single molecule sequencing reads, such as those produced by PacBio and Oxford Nanopore Technologies. It is designed for a wide range of datasets, from small bacterial projects to large mammalian-scale assemblies. The package represents a complete pipeline: it takes raw PB / ONT reads as input and outputs polished contigs. Flye also includes a special mode for metagenome assembly.

Address of the bookmark: https://github.com/fenderglass/Flye

VCFtools: perform common tasks with VCF files such as file validation, file merging, intersecting, complements

Rahul Nayak — Tue, 07 Aug 2018 10:01:46 -0500

VCFtools contains a Perl API (Vcf.pm) and a number of Perl scripts that can be used to perform common tasks with VCF files such as file validation, file merging, intersecting, complements, etc. The Perl tools support all versions of the VCF specification (3.2, 3.3, 4.0, 4.1 and 4.2), nevertheless, the users are encouraged to use the latest versions VCFv4.1 or VCFv4.2. The VCFtools in general have been used mainly with diploid data, but the Perl tools aim to support polyploid data as well. Run any of the Perl scripts with the --help switch to obtain more help.

Many of the Perl scripts require that the VCF files are compressed by bgzip and indexed by tabix (both tools are part of the tabix package, available for download here). The VCF files can be compressed and indexed using the following commands

bgzip my_file.vcf
tabix -p vcf my_file.vcf.gz

http://vcftools.sourceforge.net/perl_module.html

Address of the bookmark: http://vcftools.sourceforge.net/perl_module.html