BOL: Related items

DeepVariant : an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.

Jit — Sat, 25 Jan 2020 13:28:09 -0600

DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.

DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data. DeepVariant relies on Nucleus, a library of Python and C++ code for reading and writing data in common genomics file formats (like SAM and VCF) designed for painless integration with the TensorFlow machine learning framework.

https://ai.googleblog.com/2017/12/deepvariant-highly-accurate-genomes.html

https://www.biorxiv.org/content/10.1101/092890v6

Address of the bookmark: https://github.com/google/deepvariant

McClintock: Meta-pipeline to identify transposable element insertions using next generation sequencing data

BioStar — Tue, 27 Oct 2020 00:21:18 -0500

an integrated bioinformatics pipeline for the detection of TE insertions in whole-genome shotgun data, called McClintock (https://github.com/bergmanlab/mcclintock), which automatically runs and standardizes output for multiple TE detection methods. We demonstrate the utility of McClintock by evaluating six TE detection methods using simulated and real genome data from the model microbial eukaryote, Saccharomyces cerevisiae.

Address of the bookmark: https://github.com/bergmanlab/mcclintock

Libraries or management tools for high throughput sequencing data

LEGE — Fri, 04 Oct 2024 02:45:06 -0500

GATB Library. The Genome Analysis Toolbox with de-Bruijn graph. A large part of tools developed by the GenScale team are based on this library.
These methods enable the analysis of data sets of any size on multi-core desktop computers, including very huge amount of reads data coming from any kind of organisms such as bacteria, plants, animals and even complex samples (e.g. metagenomes). Among them are (the full is available here: https://gatb.inria.fr/software/):
LRez: C++ Library and toolkit for the barcode-based management and indexation of linked-read datasets.

Variant calling and/or genotyping

DiscoSNP++ and discoSnpRAD: Reference-free small variant discovery (SNPs and indels)
MindTheGap: Detection and assembly of large insertion variants
TakeABreak: reference-free inversion discovery tool
SVJedi: Structural Variant genotyper with long read data
SVJedi-graph: Structural Variant genotyper with long read data using a variation graph

Sequence assembly

MinYS: reference-guided genome assembly in metagenomics data
MTG-link: local assembly tool for linked-read data
Minia: De novo short read assembler
de-novo pipeline: de-novo assembly pipeline (error correction / contigs / scaffolding) for genomes and meta-genomes
Mapsembler2: Targeted assembly (not maintained)

Managing k-mers & indexation

findere: simple strategy for speeding up queries and for reducing false positive calls from any Approximate Membership Query data structure.
- fimpera extends findere adding the abundance information.
kmtricks: modular tool suite for counting kmers, and constructing Bloom filters or kmer matrices, for large collections of sequencing data.
kmindex is a tool for indexing and querying sequencing samples. It is built on top of kmtricks.
back to sequences: Find sequences (reads, unitigs, genes) related to a set of kmers in large datasets, in a matter of seconds.
Backpack Quotient Filter: k-mer indexing data structure with abundance
short read connector: Detect similar reads from potentially large read set
DSK: Count K-mer in sequences

Pangenome graph manipulation

Pancat: Pangenome Comparison and Analysis Toolkit
GFAGraphs: a Python library to handle pangenome graph files in GFA format.

Comparative metagenomics with k-mers

Simka and SimkaMin: Comparative metagenomics for large-scale datasets
Comparead & Commet: comparison of metagenomic datasets

Species and bacterial strains identification

ORI: software using long nanopore reads to identify bacteria present in a sample at the strain level
StrainFLAIR: STRAIN-level proFiLing using vArIation gRaph

General-purpose sequencing data manipulation

GASSST: long read mapper
Leon: short read compressor (now included in GATB-core)
Bloocoo: short read corrector
BCALM: Construct compacted de Bruijn graphs (unitigs)

Protein Structure

A_Purva: Contact Map Overlap solver
MD-Jeep: Distance Geometry solver
CSA: Comparative Structural Alignment

Workflow

SLICEE: parallel execution of bioinformatics workflows

Comparative Genomics

CASSIS: detection of rearrangement breakpoints
PLAST: intensive bank-to-bank sequence comparison
DRJBreakpointFinder: detection and precise localization of excision sites in proviral segments

medaka: Sequence correction provided by ONT Research

BioStar — Mon, 18 May 2020 16:28:00 -0500

medaka is a tool to create a consensus sequence from nanopore sequencing data. This task is performed using neural networks applied from a pileup of individual sequencing reads against a draft assembly. It outperforms graph-based methods operating on basecalled data, and can be competitive with state-of-the-art signal-based methods, whilst being much faster.

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

You can't install David Brownlee ;-)

Jit — Wed, 01 May 2019 21:47:36 -0500

By mistake I ask cpan to install abs, and it return this message.

jitendra@jitendra-Aspire-S3-391[parallelLastz] sudo cpan install abs [ 4:43AM]
Going to read '/home/jitendra/.cpan/Metadata'
Database was generated on Thu, 02 May 2019 00:08:06 GMT
Don't be silly, you can't install David Brownlee ;-)

rHAT: a seed-and-extension-based noisy long read alignment tool

Abhimanyu Singh — Sun, 23 Sep 2018 05:12:22 -0500

rHAT is a seed-and-extension-based noisy long read alignment tool. It is suitable for aligning 3rd generation sequencing reads which are in large read length with relatively high error rate, especially Pacbio's Single Molecule Read-time (SMRT) sequencing reads.

Address of the bookmark: https://github.com/dfguan/rHAT

Shasta long read assembler

Jit — Tue, 14 Jan 2020 06:47:07 -0600

The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using as input DNA reads generated by Oxford Nanopore flow cells.

Computational methods used by the Shasta assembler include:

Using a run-length representation of the read sequence. This makes the assembly process more resilient to errors in homopolymer repeat counts, which are the most common type of errors in Oxford Nanopore reads.
Using in some phases of the computation a representation of the read sequence based on markers, a fixed subset of short k-mers (k ≈ 10).

More at https://chanzuckerberg.github.io/shasta/index.html

Address of the bookmark: https://github.com/chanzuckerberg/shasta

PBSuite: Software for Long-Read Sequencing Data from PacBio

Jit — Mon, 27 Feb 2017 09:54:47 -0600

PBJelly - the genome upgrading tool.
PBHoney - the structural variation discovery tool

Both are contained within the PBSuite code found in downloads.

----- PBJelly -----
Read The Paper
http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0047768

PBJelly is a highly automated pipeline that aligns long sequencing reads (such as PacBio RS reads or long 454 reads in fasta format) to high-confidence draft assembles. PBJelly fills or reduces as many captured gaps as possible to produce upgraded draft genomes.

----- PBHoney -----
Read The Paper
http://www.biomedcentral.com/1471-2105/15/180/abstract

PBHoney is an implementation of two variant-identification approaches designed to exploit the high mappability of long reads (i.e., greater than 10,000 bp). PBHoney considers both intra-read discordance and soft-clipped tails of long reads to identify structural variants.

Address of the bookmark: https://sourceforge.net/projects/pb-jelly/

TULIP - The Uncorrected Long read Itegration Pipeline

Jit — Thu, 23 Nov 2017 09:30:01 -0600

#Running TULIP (The Uncorrected Long-read Integration Process), version 0.4 late 2016 (European eel)

TULIP currently consists of to Perl scripts, tulipseed.perl and tulipbulb.perl. These are very much intended as prototypes, and additional components and/or implementations are likely to follow.
Tulipseed takes as input alignments files of long reads to sparse short seeds, and outputs a graph and scaffold structures. Tulipbulb adds long read sequencing data to these.

https://github.com/Generade-nl/TULIP

Address of the bookmark: https://github.com/Generade-nl/TULIP

LSC: Improving PacBio Long Read Accuracy by Short Read Alignment

Abhimanyu Singh — Thu, 06 Sep 2018 16:27:35 -0500

Added Command line argument support.
Multi-stage execution modes.
Support for parallelization. Now execution proceeds in batches of long reads the size of which can be set by --long_read_batch_size N.
Better compressed intermediate files.
Added utilities folder.
Added support for multiple short read files.
Removed use of configuration file.

Address of the bookmark: https://www.healthcare.uiowa.edu/labs/au/LSC/