BOL: Related items

SeqMule: Automated human exome/genome variants detection

BioStar — Tue, 18 Feb 2020 03:22:54 -0600

SeqMule takes single-end or paird-end FASTQ or BAM files, generates a script consisting of more than 10 popular alignment, analysis tools and runs the script line by line. Users can change the pipeline or fine-tune the parameters by modifying its configuration file.

Address of the bookmark: https://doc-openbio.readthedocs.io/projects/seqmule/en/latest/

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

Rahul Nayak — Mon, 13 Nov 2017 05:10:23 -0600

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

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

MinION_GC: An R script to do some QC on MinION data

Radha Agarkar — Sun, 03 Dec 2017 15:19:18 -0600

Other tools focus on getting data out of the fastq or fast5 files, which is slow and computationally intensive. The benefit of this approach is that it works on a single, small, .txt summary file. So it's a lot quicker than most other things out there: it takes about a minute to analyse a 4GB flowcell on my laptop.

https://github.com/roblanf/minion_qc

Address of the bookmark: https://github.com/roblanf/minion_qc

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

BamView: a free interactive display of read alignments in BAM data files

Neel — Fri, 09 Nov 2018 13:43:22 -0600

To run the application on UNIX from the downloaded jar file run the UNIX:

java -mx512m -jar BamView.jar

and extra command line options are given when '-h' is used:

java -jar BamView.jar -h

BAM files can be specified on the command line with the '-a' option:

java -mx512m -jar BamView.jar -a pathToFile/sorted.bam

If a BAM filename is not given on the command line BamView will prompt for a file to be entered. The BAM index file should have the same name as the BAM file but with a '.bai' suffix. Multiple BAM files can be loaded and overlaid in the viewer. To make this easier BamView will read in files that contain a list of filenames.

Address of the bookmark: http://bamview.sourceforge.net/

kallisto: a program for quantifying abundances of transcripts from bulk and single-cell RNA-Seq data

Jit — Mon, 07 Jan 2019 10:35:14 -0600

kallisto is a program for quantifying abundances of transcripts from bulk and single-cell RNA-Seq data, or more generally of target sequences using high-throughput sequencing reads. It is based on the novel idea of pseudoalignment for rapidly determining the compatibility of reads with targets, without the need for alignment. On benchmarks with standard RNA-Seq data, kallisto can quantify 30 million human reads in less than 3 minutes on a Mac desktop computer using only the read sequences and a transcriptome index that itself takes less than 10 minutes to build. Pseudoalignment of reads preserves the key information needed for quantification, and kallisto is therefore not only fast, but also as accurate as existing quantification tools. In fact, because the pseudoalignment procedure is robust to errors in the reads, in many benchmarks kallisto significantly outperforms existing tools. kallisto is described in detail in:

Nicolas L Bray, Harold Pimentel, Páll Melsted and Lior Pachter, Near-optimal probabilistic RNA-seq quantification, Nature Biotechnology 34, 525–527 (2016), doi:10.1038/nbt.3519

Address of the bookmark: https://pachterlab.github.io/kallisto/about

heatmaply: popular graphical method for visualizing high-dimensional data

Neel — Sat, 11 Jan 2020 07:34:14 -0600

This work is based on ggplot2 and plotly.js engine. It produces similar heatmaps as d3heatmap, with the advantage of speed (plotly.js is able to handle larger size matrix), and the ability to zoom from the dendrogram.

heatmaply also provides an interface based around the plotly R package. This interface can be used by choosing plot_method = "plotly" instead of the default plot_method = "ggplot". This interface can provide smaller objects and faster rendering to disk in many cases and provides otherwise almost identical features.

Documentation for this package is also available as a pkgdown site: http://talgalili.github.io/heatmaply/

Address of the bookmark: http://talgalili.github.io/heatmaply/articles/heatmaply.html

Free Genomics data !

BioStar — Fri, 07 Feb 2020 14:08:31 -0600

The specimens were collected by the Oxford Wytham Woods and Edinburgh Lohse lab teams. DNA extraction and sequencing was carried out by the Sanger Institute Scientific Operations teams. Assemblies were carried out by the Tree of Life team (Shane McCarthy) and colleagues in Pacific Biosciences (Jonas Korlach).

https://www.darwintreeoflife.org/an-initial-set-of-raw-genome-assemblies-from-the-darwin-tree-of-life-project/

Address of the bookmark: https://www.darwintreeoflife.org/an-initial-set-of-raw-genome-assemblies-from-the-darwin-tree-of-life-project/

Phytozome v12.1: plant science community hub for accessing palnts genomic data

Surabhi Chaudhary — Tue, 17 Mar 2020 07:30:17 -0500

Phytozome, the Plant Comparative Genomics portal of the Department of Energy's Joint Genome Institute, provides JGI users and the broader plant science community a hub for accessing, visualizing and analyzing JGI-sequenced plant genomes, as well as selected genomes and datasets that have been sequenced elsewhere. As of release v12.1.6, Phytozome hosts 93 assembled and annotated genomes, from 82 Viridiplantae species. More than half of these genomes have been sequenced, assembled and/or annotated with JGI Plant Science program resources. By integrating this large collection of plant genomes into a single resource and performing comprehensive and uniform annotation and analyses, Phytozome facilitates accurate and insightful comparative genomics studies.

Address of the bookmark: https://phytozome.jgi.doe.gov/pz/portal.html

proActiv: Estimation of Promoter Activity from RNA-Seq data

BioStar — Thu, 13 Aug 2020 10:21:44 -0500

proActiv is an R package that estimates promoter activity from RNA-Seq data. proActiv uses aligned reads and genome annotations as input, and provides absolute and relative promoter activity as output. The package can be used to identify active promoters and alternative promoters, the details of the method are described in Demircioglu et al.

Additional data on differential promoters in tissues and cancers from TCGA, ICGC, GTEx, and PCAWG can be downloaded here: https://jglab.org/data-and-software/

Address of the bookmark: https://github.com/GoekeLab/proActiv