BOL: Related items

TGNet

Shruti Paniwala — Wed, 24 Aug 2016 05:36:36 -0500

Recent technological progress has greatly facilitated de novo genome sequencing. However, de novo assemblies consist in many pieces of contiguous sequence (contigs) arranged in thousands of scaffolds instead of small numbers of chromosomes. Confirming and improving the quality of such assemblies is critical for subsequent analysis.

Visualization and quality assessment of de novo genome assemblies

Citation

This software is fully described in the paper:
Riba-Grognuz, Keller, Falquet, Xenarios & Wurm (2011) Visualization and quality assessment of de novo genome assemblies.

In brief, our scripts create Cytoscape files to visualize transcript evidence that suggests adjacency between scaffolds and contigs.

Software requirements

BLAT (tested with Standalone BLAT v. 32×1). Source Binaries .
Cytoscape (tested with versions 2.7.0, 2.8.2)
a UNIX machine (tested on Mac OS X 10.6 and CentOS 4.6)

Address of the bookmark: https://github.com/ksanao/TGNet

EAGLER: a scaffolding tool for long reads.

Jit — Mon, 04 Jun 2018 05:26:03 -0500

EAGLER is a scaffolding tool for long reads. The scaffolder takes as input a draft genome created by any NGS assembler and a set of long reads. The long reads are used to extend the contigs present in the NGS draft and possibly join overlapping contigs. EAGLER supports both PacBio and Oxford Nanopore reads.

The tool should be compatible with most UNIX flavors and has been successfully tested on the following operating systems:

Mac OS X 10.11.1
Mac OS X 10.10.3
Ubuntu 14.04 LTS

https://bib.irb.hr/datoteka/844447.Diplomski_2015_Luka_terbi.pdf

Address of the bookmark: https://github.com/mculinovic/EAGLER

Gene Finding and Predictions

Poonam Mahapatra — Fri, 26 Aug 2016 07:26:27 -0500

In this exercise, a previously annotated gene will be used to measure the accuracy of different gene finding approaches. GRAIL, GENSCAN, geneid, FGENESH, GenomeScan, GrailEXP and GENEWISE will be used to annotate the sequence. Both search by signal, content and homology (protein and cDNA sequences) methods will be employed in order to improve the ab initio results. Weak conservation of Start codons will lead to wrong prediction of initial exons in most cases.

http://genome.crg.es/courses/Bioinformatics2003_genefinding/

Address of the bookmark: http://genome.crg.es/courses/Bioinformatics2003_genefinding/

Sushi: An R/Bioconductor package for visualizing genomic data

Jit — Wed, 31 Aug 2016 08:29:12 -0500

Sushi: An R/Bioconductor package for visualizing genomic data

Address of the bookmark: https://www.bioconductor.org/packages/devel/bioc/vignettes/Sushi/inst/doc/Sushi.pdf

Converting a VCF into a FASTA given some reference !

Jit — Fri, 20 Jul 2018 10:03:53 -0500

Samtools/BCFtools (Heng Li) provides a Perl script vcfutils.pl which does this, the function vcf2fq (lines 469-528)

This script has been modified by others to convert InDels as well, e.g. this by David Eccles

./vcf2fq.pl -f <input.fasta> <all-site.vcf> > <output.fastq>

https://github.com/gringer/bioinfscripts/blob/master/vcf2fq.pl

https://github.com/lh3/samtools/blob/master/bcftools/vcfutils.pl

CIRCOS Visualize !!

Jit — Fri, 02 Sep 2016 08:29:26 -0500

Before uploading a data file, check the samples gallery to make sure that your data format is compatible.

Your file must be plain text.
Your data values must be non-negative integers.
Data must be space-separated (one or more tab or space, which will be collapsed).
No two rows or columns may have the same name.
Column and row names must begin with a letter (e.g. 'A', 'A0', 'A-0') and can only contain letters, numbers and _. No punctuation!
Maximum row + column total is 150 — if exceeded, rows and columns are limited to 75.
If you are using order, size and color rows/columns in combination they must appear in that order.

Need help? Post questions to the Circos Google Group.

http://mkweb.bcgsc.ca/tableviewer/visualize/

Address of the bookmark: http://mkweb.bcgsc.ca/tableviewer/visualize/

Structural variants PPT

Jit — Wed, 07 Sep 2016 03:16:09 -0500

1000 Genomes data tutorial at ASHG

Structural variants presentation by

Jan Korbel

European Molecular Biology Laboratory (EMBL) Heidelberg Genome Biology Research Unit

Reference:

https://www.genome.gov/pages/research/der/1000genomesprojecttutorials/structuralvariants-jankorbel.pdf

Nemo – A stochastic, individual-base, genetically explicit simulation platform

Jit — Sat, 01 Oct 2016 14:45:02 -0500

A recombination map has been added for all multi-locus traits. The map positions (chromosomal) for neutral markers (e.g. SNPs) and loci under selection (QTLs, deleterious mutations, DMIs) can now be specified explicitly, or set at random. The map can hold an unlimited number of loci of different types jointly, at any recombination scale (cM or lower). The effects of linkage can thus be finely explored.
A new trait coding for (Bateson-)Dobzhansky-Muller incompatibility loci. Multiple haploid or diploid pairs of incompatible loci can be spread throughout the genome and affect individual fitness.
Multi-type selection: Individual fitness can be jointly determined by different types of loci under selectinon, such as QTLs coding for quantitative traits under spatially variable selection, universally deleterious mutations, and Dobzhansky-Muller incompatibility loci.
An unlimited number of quantitative traits under different forms of selection can be modelled, based on universally pleiotropic loci with several bi- or multi-allelic models.
Spatial and temporal variation of selection on quantitative traits is possible, modelling shifts of environmental conditions over time.
The dispersal matrix describing the movement of individuals among sub-populations can be replaced by a connectivity matrix and a reduced dispersal matrix describing migration only among the connected sub-populations. This offers a substantial gain in computing time and system memory when simulating very large grids.
Input parameters' arguments may be specified in separate files. This is particularly convenient when specifying large matrices.
Many adjustments have been made for refined control of the input of parameters and data output. See updates in the manual.

Address of the bookmark: http://nemo2.sourceforge.net/index.html

wtdbg2: A fuzzy Bruijn graph approach to long noisy reads assembly

BioStar — Mon, 04 Feb 2019 04:53:47 -0600

Wtdbg2 is a de novo sequence assembler for long noisy reads produced by PacBio or Oxford Nanopore Technologies (ONT). It assembles raw reads without error correction and then builds the consensus from intermediate assembly output.

./wtdbg2 -x rs -g 4.6m -t 16 -i reads.fa.gz -fo prefix
./wtpoa-cns -t 16 -i prefix.ctg.lay.gz -fo prefix.ctg.fa

Address of the bookmark: https://github.com/ruanjue/wtdbg2

BBMap help

Shruti Paniwala — Mon, 10 Oct 2016 06:29:03 -0500

BBMAP • a solution for everything

That content has been reformatted and it is being expanded to include more information.

There are common options for most BBMap suite programs and depending on the file extension the input/output format is automatically chosen/set.

Using BBMap

Mapping Nanopore reads

BBMap.sh has a length cap of 6kbp. Reads longer than this will be broken into 6kbp pieces and mapped independently.

More at https://www.biostarhandbook.com/tools/bbmap/bbmap-help.html

Address of the bookmark: https://www.biostarhandbook.com/tools/bbmap/bbmap-help.html