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

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

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

FERMI

Jit — Fri, 09 Sep 2016 05:37:13 -0500

Fermi is a de novo assembler with a particular focus on assembling Illumina short sequence reads from a mammal-sized genome. In addition to the role of a typical assembler, fermi also aims to preserve heterozygotes which are often collapsed by other assemblers. Its ultimate goal is to find a minimal set of
unitigs to represent all the information in raw reads.

Fermi follows the overlap-layout-consensus paradigm and uses the FM-DNA-index (FMD-index) as the key data structure. It is inspired by the string graph assembler (Simpson and Durbin, 2010 and 2012) and has a similar workflow.

As a typical de novo assembler, fermi tends to produce contigs with slightly longer N50. However, the major weakness of fermi is the high misassembly rate. Although fermi provides a tool to fix misassemblies by using paired-end reads to achieve an accuracy comparable to other assemblers, this is not a favorable solution.

Fermi is designed to be used on a multi-core Linux machine with large shared memory. The easiest way to run fermi is to use the run-fermi.pl script. It generates a Makefile. The actual assembly is done by invoking make. Premature assembly processes can be resumed. Here is an example:

run-fermi.pl -dAPe ./fermi -p NA12878 -t16 -f18 reads*.fq.gz > NA12878.mak
make -f NA12878.mak -j16

Address of the bookmark: https://github.com/lh3/fermi

GenomeScope: open-source web tool to rapidly estimate the overall characteristics of a genome, including genome size, heterozygosity rate, and repeat content from unprocessed short reads

Jit — Fri, 21 Oct 2016 05:46:43 -0500

Summary: GenomeScope is an open-source web tool to rapidly estimate the overall characteristics of a genome, including genome size, heterozygosity rate, and repeat content from unprocessed short reads. These features are essential for studying genome evolution, and help to choose parameters for downstream analysis. We demonstrate its accuracy on 324 simulated and 16 real datasets with a wide range in genome sizes, heterozygosity levels, and error rates. Availability and Implementation: http://qb.cshl.edu/genomescope/, https://github.com/schatzlab/genomescope.git

Address of the bookmark: http://qb.cshl.edu/genomescope/

Statistics Using R with Biological Examples

Neel — Thu, 03 Nov 2016 04:55:41 -0500

This book is a manifestation of my desire to teach researchers in biology a bit more about statistics than an ordinary introductory course covers and to introduce the utilization of R as a tool for analyzing their data. My goal is to reach those with little or no training in higher level statistics so that they can do more of their own data analysis, communicate more with statisticians, and appreciate the great potential statistics has to offer as a tool to answer biological questions.

This is necessary in light of the increasing use of higher level statistics in biomedical research. I hope it accomplishes this mission and encourage its free distribution and use as a course text or supplement.

K Seefeld, May 2007

RECORD

Bulbul — Fri, 25 Nov 2016 08:23:36 -0600

Background. Next-generation sequencing technologies are now producing multiple times the genome size in total reads from a single experiment. This is enough information to reconstruct at least some of the differences between the individual genome studied in the experiment and the reference genome of the species. However, in most typical protocols, this information is disregarded and the reference genome is used. Results. We provide a new approach that allows researchers to reconstruct genomes very closely related to the reference genome (e.g., mutants of the same species) directly from the reads used in the experiment. Our approach applies de novo assembly software to experimental reads and so-called pseudoreads and uses the resulting contigs to generate a modified reference sequence. In this way, it can very quickly, and at no additional sequencing cost, generate new, modified reference sequence that is closer to the actual sequenced genome and has a full coverage. In this paper, we describe our approach and test its implementation called RECORD. We evaluate RECORD on both simulated and real data. We made our software publicly available on sourceforge. Conclusion. Our tests show that on closely related sequences RECORD outperforms more general assisted-assembly software.

More at https://sourceforge.net/projects/record-genome-assembler/files/

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pubmed/26558255

SWALO

Jit — Wed, 30 Nov 2016 05:06:05 -0600

SWALO (scaffolding with assembly likelihood optimization) is a method for scaffolding based on likelihood of genome assemblies computed using generative models for sequencing.

Download

Git repository of SWALO is at https://github.com/atifrahman/SWALO.

Address of the bookmark: https://atifrahman.github.io/SWALO/