BOL: Related items

DIAL

Abhimanyu Singh — Wed, 01 Mar 2017 08:42:28 -0600

A computational pipeline for identifying single-base substitutions between two closely related genomes without the help of a reference genome. DIAL works even when the depth of coverage is insufficient for de novo assembly, and it can be extended to determine small insertions/deletions. Our main motivation is to use this tool to survey the genetic diversity of endangered species as the identified sequence differences can be used to design genotyping arrays to assist in the species' management.

http://www.bx.psu.edu/~ratan/

Address of the bookmark: http://www.bx.psu.edu/miller_lab/

TULIP - The Uncorrected Long read Integration Pipeline

Jit — Tue, 15 May 2018 09:06:37 -0500

TULIP currently consists of two 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.

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

Integrative Meta-Assembly Pipeline (IMAP): Chromosome-level genome assembler combining multiple de novo assemblies

Jit — Sat, 31 Aug 2019 11:30:41 -0500

Chromosome-level genome assembler combining multiple de novo assemblies

https://github.com/jkimlab/IMAP

Address of the bookmark: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0221858

YAMP: Yet Another Metagenomic Pipeline

BioStar — Sat, 06 Jul 2024 04:26:00 -0500

YAMP is constructed on Nextflow, a framework based on the dataflow programming model, which allows writing workflows that are highly parallel, easily portable (including on distributed systems), and very flexible and customisable, characteristics which have been inherited by YAMP. New modules can be added easily and the existing ones can be customised -- even though we have already provided default parameters deriving from our own experience.

Address of the bookmark: https://github.com/alesssia/YAMP

Omega2: metagenome assembly pipeline

Jit — Mon, 10 Jul 2017 05:56:07 -0500

Omega found overlaps between reads using a prefix/suffix hash table. The overlap graph of reads was simplified by removing transitive edges and trimming short branches. Unitigs were generated based on minimum cost flow analysis of the overlap graph and then merged to contigs and scaffolds using mate-pair information. In comparison with three de Bruijn graph assemblers (SOAPdenovo, IDBA-UD and MetaVelvet), Omega provided comparable overall performance on a HiSeq 100-bp dataset and superior performance on a MiSeq 300-bp dataset. In comparison with Celera on the MiSeq dataset, Omega provided more continuous assemblies overall using a fraction of the computing time of existing overlap-layout-consensus assemblers. This indicates Omega can more efficiently assemble longer Illumina reads, and at deeper coverage, for metagenomic datasets.

Address of the bookmark: http://omega.omicsbio.org/

HiC-Pro: an optimized and flexible pipeline for Hi-C data processing

Jit — Wed, 06 Dec 2017 01:05:21 -0600

HiC-Pro was designed to process Hi-C data, from raw fastq files (paired-end Illumina data) to the normalized contact maps. Since version 2.7.0, HiC-Pro supports the main Hi-C protocols, including digestion protocols as well as protocols that do not require restriction enzyme such as DNase Hi-C. In practice, HiC-Pro can be used to process dilution Hi-C, in situ Hi-C, DNase Hi-C, Micro-C, capture-C, capture Hi-C or HiChip data.

http://nservant.github.io/HiC-Pro/

Address of the bookmark: http://nservant.github.io/HiC-Pro/

MetaPlotR: a Perl/R pipeline for plotting metagenes of nucleotide modifications and other transcriptomic sites

Neel — Mon, 05 Nov 2018 08:12:45 -0600

An increasing number of studies are mapping protein binding and nucleotide modifications sites throughout the transcriptome. Often, these sites cluster in certain regions of the transcript, giving clues to their function. Hence, it is informative to summarize where in the transcript these sites occur. A metagene is a simple and effective tool for visualizing the distribution of sites along a simplified transcript model. In this work, we introduce MetaPlotR, a Perl/R pipeline for creating metagene plots.

Address of the bookmark: https://github.com/olarerin/metaPlotR

dnaPipeTE: a pipeline designed to find, annotate and quantify Transposable Elements

Jit — Mon, 12 Aug 2019 21:56:08 -0500

dnaPipeTE (for de-novo assembly & annotation Pipeline for Transposable Elements), is a pipeline designed to find, annotate and quantify Transposable Elements in small samples of NGS datasets. It is very useful to quantify the proportion of TEs in newly sequenced genomes since it does not require genome assembly and works on small datasets (< 1X).

https://github.com/clemgoub/dnaPipeTE/wiki/dnaPipeTE-WIKI-home

Address of the bookmark: https://github.com/clemgoub/dnaPipeTE

3D de novo assembly (3D DNA) pipeline

Jit — Sun, 02 Feb 2020 13:41:55 -0600

For a detailed description of the pipeline and how it integrates with other tools designed by the Aiden Lab see Genome Assembly Cookbook on http://aidenlab.org/assembly.

For the original version of the pipeline and to reproduce the Hs2-HiC and the AaegL4 genomes reported in (Dudchenko et al., Science, 2017) see the original commit.

For the detailed description of the merge section see https://github.com/theaidenlab/AGWG-merge.

Address of the bookmark: https://github.com/theaidenlab/3d-dna

PyParanoid: a pipeline for rapid identification of homologous gene families in a set of genomes

BioStar — Thu, 13 Aug 2020 10:06:19 -0500

PyParanoid is a pipeline for rapid identification of homologous gene families in a set of genomes - a central task of any comparative genomics analysis. The "gold standard" for identifying homologs is to use reciprocal best hits (RBHs) which depends on performing a all-vs-all sequence comparison, usually using BLAST, to determine homology. However, these methods are computationally expensive, requiring O(n2) resources to identify RBHs. This is problematic, as the modern deluge of sequencing data means that comparative genomics analyses could be performed on datasets of thousands of strains.

Address of the bookmark: https://github.com/ryanmelnyk/PyParanoid