BOL: Related items

DISCOVAR

Abhimanyu Singh — Mon, 18 Apr 2016 11:59:16 -0500

DISCOVAR is a new variant caller and DISCOVAR de novo a new genome assembler, both designed for state-of-the-art data. Their inputs are chosen to optimize quality while keeping costs low. Currently it takes as input Illumina reads of length 250 or longer — produced on MiSeq or HiSeq 2500 — and from a single PCR-free library. These data enable a level of completeness and continuity that was not previously possible.

DISCOVAR can call variants on a region by region basis, potentially tiling an entire large genome. DISCOVAR variant calling is under active development and transitioning to VCF.

DISCOVAR de novo can generate de novo assemblies for both large and small genomes. It currently does not call variants.

More at https://www.broadinstitute.org/software/discovar/blog/?page_id=14

Address of the bookmark: https://www.broadinstitute.org/software/discovar/blog/

BUSCO: Assessing genome assembly and annotation completeness with Benchmarking Universal Single-Copy Orthologs

Anjana — Tue, 10 May 2016 07:46:24 -0500

High-throughput genomics has revolutionized biological research, however, while the number of sequenced genomes grows by the day, quality assessment of the resulting assembled sequences remains complicated and mostly limited to technical measures like N50.
BUSCO provides measures for quantitative assessment of genome assembly, gene set, and transcriptome completeness based on evolutionarily informed expectations of gene content from near-universal single-copy orthologs selected from OrthoDB.
BUSCO assessments are implemented in open-source software, with comprehensive lineage-specific sets of Benchmarking Universal Single-Copy Orthologs for arthropods, vertebrates, metazoans, fungi, eukaryotes, and bacteria.
These conserved orthologs are ideal candidates for large-scale phylogenomics studies, and the annotated BUSCO gene models built during genome assessments provide a comprehensive gene predictor training set for use as part of genome annotation pipelines.
BUSCO assessments offer intuitive metrics, based on evolutionarily informed expectations of gene content from hundreds of species, to gauge completeness of rapidly accumulating genomic data and satisfy an Iberian's quest for quality - "Busco calidad/qualidade".

Address of the bookmark: http://busco.ezlab.org/

mrFAST: Micro Read Fast Alignment Search Tool

Neel — Tue, 26 Apr 2016 03:50:06 -0500

mrFAST is a read mapper that is designed to map short reads to reference genome with a special emphasis on the discovery of structural variation and segmental duplications. mrFAST maps short reads with respect to user defined error threshold, including indels up to 4+4 bp. This manual, describes how to choose the parameters and tune mrFAST with respect to the library settings. mrFAST is designed to find 'all' mappings for a given set of reads, however it can return one "best" map location if the relevant parameter is invoked.

More at http://mrfast.sourceforge.net/manual.html

Address of the bookmark: http://mrfast.sourceforge.net/manual.html

Andi

Jit — Fri, 13 May 2016 05:16:35 -0500

This is the andi program for estimating the evolutionary distance between closely related genomes. These distances can be used to rapidly infer phylogenies for big sets of genomes. Because andi does not compute full alignments, it is so efficient that it scales even up to thousands of bacterial genomes.

This readme covers all necessary instructions for the impatient to get andi up and running. For extensive instructions please consult the manual.

More at https://github.com/evolbioinf/andi/

Address of the bookmark: http://bioinformatics.oxfordjournals.org/content/early/2015/01/13/bioinformatics.btu815.full

BBMap/BBTools package: Multipurpose tool designed for converting reads or other nucleotide data between different formats.

Jit — Mon, 13 Jun 2016 05:47:21 -0500

Reformatis a member of the BBMap/BBTools package. It is a multipurpose tool designed for converting reads or other nucleotide data between different formats. It supports, and can inter-convert:

fastq
fasta
fasta+qual
sam
scarf (an old Illumina format)
bam (if samtools is installed)
gzip
zip
ascii-33 (sanger)
ascii-64 (old Illumina)
paired files
interleaved files

It is multithreaded and can process data at over 500 megabytes per second, and can accept streams from standard in and write to standard out, allowing it to be easily dropped into the middle of a pipeline for format conversion. Reformat autodetects formats based on file extensions and content, making it very easy to use; and the autodetection can be overridden, allowing flexibility for people who don't like to follow naming conventions, or out-of-spec fastq files with qualities values like -17 or 120.

The program has been gradually expanded, and can now perform various other functions. None of these will break pairing, if the input is paired.

Quality trimming (either or both ends)
Quality filtering
Fixed-length trimming
Generation of histograms (base composition, quality, etc)
Subsampling (to a fraction of input reads, or an exact number of reads or bases)
Changing fasta line-wrapping length
Reverse-complementing (all reads or only read 2)
Adding /1 and /2 suffix to read names
GC-content filtering
Length-filtering
Testing for corrupted interleaved files

Reformat is compatible with any platform that supports Java 1.7 or higher. It also has a bash shellscript for simpler invocation. Typical usage examples:

Reformat fastq into fasta:
reformat.sh in=x.fq out=y.fa

Interleave paired reads:
reformat.sh in1=x1.fq in2=x2.fq out=y.fq

Note - you can actually use a shortcut if paired read files have the same name with a 1 and a 2. This is equivalent to the above command:
reformat.sh in=x#.fq out=y.fq

De-interleave reads:
reformat.sh in=x.fq out1=y1.fq out2=y2.fq

Verify that interleaving appears correct, assuming Illumina namimg conventions:
reformat.sh in=x.fq vint

Convert ASCII-33 to ASCII-64:
reformat.sh in=x.fq out=y.fq qin=33 qout=64

Quality-trim paired reads to Q10 on the left and right ends and discard reads shorter than 50bp after trimming:
reformat.sh in1=x1.fq in2=x2.fq out1=y1.fq out2=y2.fq outsingle=singletons.fq qtrim=rl trimq=10 minlength=50

Subsample 10% of the first 20000 pairs in an interleaved file:
reformat.sh in=x.fq out=y.fq reads=20000 samplerate=0.1 int=t
(in this case "int=t" overrides interleaving autodetection, to ensure reads are treated as pairs)

Pipe in a gzipped sam file and pipe out fasta:
reformat.sh in=stdin.sam.gz out=stdout.fa

Reverse-complement reads:
reformat.sh in=x.fq out=y.fq rcomp

For reformatting a file with very long sequences, Reformat will need more memory; just add the additional flag "-Xmx2g". For example, to change the line-wrapping length on the human genome (which has individual sequences over 200Mbp long) to 70 characters:
reformat.sh -Xmx2g in=HG19.fa.gz out=HG19_wrapped.fa.gz fastawrap=70

For additional functions, please run the shellscript with no arguments, or just read it with a text editor. If you have any questions, please post them in this thread.

For people using a non-bash terminal, you may need to type "bash reformat.sh" instead of just "reformat.sh".
For users of Windows or other platforms that do not support bash shellscripts, replace "reformat.sh" with "java -ea -Xmx200m /path/to/bbmap/current/ jgi.ReformatReads"
for example,
java -ea -Xmx200m C:\bbmap\current\ jgi.ReformatReads in=x.fq out=y.fa

Reformat can be downloaded with BBTools here:
https://sourceforge.net/projects/bbmap/

CNIDARIA: fast, reference-free phylogenomic clustering

Shruti Paniwala — Thu, 16 Jun 2016 17:55:17 -0500

Motivation: Identification of biological specimens is a major requirement for a range of applications. Reference-free methods analyse unprocessed sequencing data without relying on prior knowledge, but these do not scale to arbitrarily large genomes and arbitrarily large phylogenetic distances.

Results: We present Cnidaria, a practical tool for clustering genomic and transcriptomic data with no limitation on ge-nome size or phylogenetic distances. We successfully simultaneously clustered 169 genomic and transcriptomic datasets from 4 kingdoms, achieving 100% accuracy at supra-species level and 78% accuracy for species level.

Availability and Implementation: Cnidaria is written in C++ and Python and is available at http://www.ab.wur.nl/cnidaria.

Contact: Saulo Aflitos - sauloal@gmail.com

Supplementary information: Supplementary data are available at Bioinformatics online.

Address of the bookmark: https://github.com/sauloal/cnidaria/wiki

SAM flags

Poonam Mahapatra — Wed, 29 Jun 2016 15:38:15 -0500

Decoding SAM flags

This utility makes it easy to identify what are the properties of a read based on its SAM flag value, or conversely, to find what the SAM Flag value would be for a given combination of properties.

To decode a given SAM flag value, just enter the number in the field below. The encoded properties will be listed under Summary below, to the right.

Address of the bookmark: https://broadinstitute.github.io/picard/explain-flags.html

Arvados

Martin Jones — Sat, 20 Sep 2014 16:54:21 -0500

Arvados is a free and open source bioinformatics platform for genomic and biomedical data. User can Store | Organize | Compute | Share the data for free.

Address of the bookmark: https://arvados.org/

Strudel

Anjana — Fri, 30 Sep 2016 09:47:02 -0500

Strudel is our graphical tool for visualizing genetic and physical maps of genomes for comparative purposes. The application aims to let the user examine their data at a variety of different levels of resolution, from entire maps to individual markers, and explore syntenic relationships between genomes. All browsing and interaction with Strudel happens in real-time – there is no need to wait while the maps are generated. It is built using Java 1.6 and ships with its own JRE, so there is no need for users to install or update Java.

Address of the bookmark: https://ics.hutton.ac.uk/strudel/

ART: Set of Simulation Tools

Jit — Thu, 03 Nov 2016 08:28:25 -0500

ART is a set of simulation tools to generate synthetic next-generation sequencing reads. ART simulates sequencing reads by mimicking real sequencing process with empirical error models or quality profiles summarized from large recalibrated sequencing data. ART can also simulate reads using user own read error model or quality profiles. ART supports simulation of single-end, paired-end/mate-pair reads of three major commercial next-generation sequencing platforms: Illumina's Solexa, Roche's 454 and Applied Biosystems' SOLiD. ART can be used to test or benchmark a variety of method or tools for next-generation sequencing data analysis, including read alignment, de novo assembly, SNP and structure variation discovery. ART was used as a primary tool for the simulation study of the 1000 Genomes Project . ART is implemented in C++ with optimized algorithms and is highly efficient in read simulation. ART outputs reads in the FASTQ format, and alignments in the ALN format. ART can also generate alignments in the SAM alignment or UCSC BED file format. ART can be used together with genome variants simulators (e.g. VarSim) for evaluating variant calling tools or methods.

Address of the bookmark: http://www.niehs.nih.gov/research/resources/software/biostatistics/art/