BOL: Related items

SeqMonk:A tool to visualise and analyse high throughput mapped sequence data

Jit — Tue, 11 Sep 2018 04:39:38 -0500

SeqMonk is a program to enable the visualisation and analysis of mapped sequence data. It was written for use with mapped next generation sequence data but can in theory be used for any dataset which can be expressed as a series of genomic positions. It's main features are:

Import of mapped data from mapped data (BAM/SAM/bowtie etc)
Creation of data groups for visualisation and analysis
Visualisation of mapped regions against an annotated genome.
Flexible quantitation of the mapped data to allow comparisons between data sets
Statistical analysis of data to find regions of interest
Creation of reports containing data and genome annotation

Address of the bookmark: http://www.bioinformatics.babraham.ac.uk/projects/seqmonk/

NanoPack: visualizing and processing long-read sequencing data

Jit — Tue, 25 Dec 2018 21:20:50 -0600

The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools.

Address of the bookmark: https://github.com/wdecoster/nanopack

Katuali is a flexible consensus pipeline implemented in Snakemake to basecall, assemble, and polish Oxford Nanopore Technologies' sequencing data

Jit — Tue, 22 Jan 2019 06:26:55 -0600

Run a pipeline processing fast5s to a consensus in a single command.
Recommended fixed "standard" and "fast" pipelines.
Interchange basecaller, assembler, and consensus components of the pipelines simply by changing the target filepath.
Seemless distribution of tasks over local or distributed compute.
Highly configurable.
Open source (Mozilla Public License 2.0).

Documentation can be found at https://nanoporetech.github.io/katuali/.

Address of the bookmark: https://github.com/nanoporetech/katuali

ClinCNV: Detection of copy number changes in Germline/Trio/Somatic contexts in NGS data

Neel — Thu, 16 Jan 2020 23:16:02 -0600

ClinCNV detects CNVs in germline and somatic context in NGS data (targeted and whole-genome). We work in cohorts, so it makes sense to try ClinCNV if you have more than 10 samples (recommended amount - 40 since we estimate variances from the data). By "cohort" we mean samples sequenced with the same enrichment kit with approximately the same depth (ie 1x WGS and 30x WGS better be analysed in separate runs of ClinCNV). Of course it is better if your samples were sequenced within the same sequencing facility.

Address of the bookmark: https://github.com/imgag/ClinCNV

LoFreq*: A sequence-quality aware, ultra-sensitive variant caller for NGS data

BioStar — Tue, 18 Feb 2020 03:24:22 -0600

LoFreq* (i.e. LoFreq version 2) is a fast and sensitive variant-caller for inferring SNVs and indels from next-generation sequencing data. It makes full use of base-call qualities and other sources of errors inherent in sequencing (e.g. mapping or base/indel alignment uncertainty), which are usually ignored by other methods or only used for filtering.

https://github.com/CSB5/lofreq

http://csb5.github.io/lofreq/installation/

https://github.com/CSB5/lofreq/tree/master/dist

Address of the bookmark: http://csb5.github.io/lofreq/

Parliament2: Runs a combination of tools to generate structural variant calls on whole-genome sequencing data

Jit — Thu, 28 May 2020 21:57:03 -0500

Parliament2 identifies structural variants in a given sample relative to a reference genome. These structural variants cover large deletion events that are called as Deletions of a region, Insertions of a sequence into a region, Duplications of a region, Inversions of a region, or Translocations between two regions in the genome.

Parliament2 runs a combination of tools to generate structural variant calls on whole-genome sequencing data. It can run the following callers: Breakdancer, Breakseq2, CNVnator, Delly2, Manta, and Lumpy. Because of synergies in how the programs use computational resources, these are all run in parallel. Parliament2 will produce the outputs of each of the tools for subsequent investigation.

Address of the bookmark: https://github.com/dnanexus/parliament2

DADA2: Fast and accurate sample inference from amplicon data with single-nucleotide resolution

Jit — Tue, 10 Nov 2020 20:26:00 -0600

The DADA2 tutorial goes through a typical workflow for paired end Illumina Miseq data: raw amplicon sequencing data is processed into the table of exact amplicon sequence variants (ASVs) present in each sample.

The DADA2 Workflow on Big Data goes through workflow optimized to run on large datasets (10s of millions to billions of reads).

An ITS-specific version of the DADA2 workflow identifies and verifiably removes primers on both ends of each ITS read, a key step due to the variable length of the ITS region.

Short demonstrations of assigning taxonomy and assigning species to sequences.

Address of the bookmark: https://benjjneb.github.io/dada2/index.html

Ktrim: an extra-fast and accurate adapter- and quality-trimmer for sequencing data

Jit — Thu, 11 Feb 2021 21:39:05 -0600

Ktrim is written in C++ for GNU Linux/Unix platforms. After uncompressing the source package, you can find an executable file ktrim under bin/ directory compiled using g++ v4.8.5 and linked with libz v1.2.7 for Linux x86_64 system. If you could not run it (which is usually caused by low version of libc++ or libz library) or you want to build a version optimized for your system, you can re-compile the programs:

user@linux$ make clean && make

Address of the bookmark: https://github.com/hellosunking/Ktrim

gget

BioStar — Sat, 01 Apr 2023 09:42:07 -0500

gget is a free, open-source command-line tool and Python package that enables efficient querying of genomic databases. gget consists of a collection of separate but interoperable modules, each designed to facilitate one type of database querying in a single line of code.

Address of the bookmark: https://github.com/pachterlab/gget

BioKit: a set of tools dedicated to bioinformatics, data visualisation

Neel — Tue, 18 Jun 2024 02:04:39 -0500

BioKit is a set of tools dedicated to bioinformatics, data visualisation (biokit.viz), access to online biological data (e.g. UniProt, NCBI thanks to bioservices). It also contains more advanced tools related to data analysis (e.g., biokit.stats). Since R is quite common in bioinformatics, we also provide a convenient module to run R inside your Python scripts or shell (:mod:biokit.rtools module).

Address of the bookmark: https://biokit.readthedocs.io/en/latest/index.html