BOL: Related items

YAHA

Jit — Fri, 20 Jan 2017 05:38:05 -0600

YAHA, a fast and flexible hash-based aligner. YAHA is as fast and accurate as BWA-SW at finding the single best alignment per query and is dramatically faster and more sensitive than both SSAHA2 and MegaBLAST at finding all possible alignments. Unlike other aligners that report all, or one, alignment per query, or that use simple heuristics to select alignments, YAHA uses a directed acyclic graph to find the optimal set of alignments that cover a query using a biologically relevant breakpoint penalty. YAHA can also report multiple mappings per defined segment of the query. We show that YAHA detects more breakpoints in less time than BWA-SW across all SV classes, and especially excels at complex SVs comprising multiple breakpoints.

Availability: YAHA is currently supported on 64-bit Linux systems. Binaries and sample data are freely available for download from http://faculty.virginia.edu/irahall/YAHA.

Contact:

http://genome.wustl.edu/people/groups/detail/hall-lab/

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3463118/

Statistics and probability

Jit — Tue, 08 Nov 2016 07:34:25 -0600

Topics

Displaying and describing data

Modeling distributions of data

Describing relationships in quantitative data

Designing studies

Probability

Random variables

Sampling distributions

Confidence intervals (one sample)

Significance tests (one sample)

Significance tests and confidence intervals (two samples)

Inference for categorical data (chi-square tests)

Advanced regression (inference and tran

Address of the bookmark: https://www.khanacademy.org/math/statistics-probability

fineSTRUCTURE v2 & GLOBETROTTER

Shruti Paniwala — Mon, 13 Feb 2017 08:40:23 -0600

Software available at this site

FineSTRUCTURE version 2, a pipeline for running ChromoPainter and FineSTRUCTURE for population inference. A GUI is available for interpretation. Download from the Downloads page.
FineSTRUCTURE R scripts, a facility for exploring the results when the GUI is unavailable.
GLOBETROTTER, the admixture dating method based on ChromoPainter. Download from the Downloads page.
AdmixturePainting, A set of R tools to inmterpret the results of ADMIXTURE and STRUCTURE-like mixture models.
RADpainter, finestructure and ChromoPainter for RAD tag data used for non-model organisms.
Scripts to perform many types of conversion. Included in the main software download from the Downloads page.

What this page is This page provides information about and downloads for methodology for Chromosome Painting. It is not a facility to analyse your genome. Sorry if you were misled by the punchy name!
About Chromosome Painting Painting is an efficient way of identifying important haplotype information from dense genotype data. It describes ancestry in an efficient way suitable for a range of further analyses, including population identification and admixture dating.

Address of the bookmark: http://paintmychromosomes.com/

Standardized velvet assembly report

Poonam Mahapatra — Fri, 09 Dec 2016 03:59:59 -0600

Requirements:

velvet (velveth velvetg should be in your PATH)
R (with Sweave)
pdflatex (usually part of TeTeX)
ggplot2 (from R prompt type install.packages("ggplot2","proto","xtable"))
Perl

Optional:

BLAT or BLAST (to generate alignments against a reference genome). If using BLAT, add faToTwoBit,gfClient,gfServer to your PATH. If using BLAST, add blastall and formatdb.

Edit permute.sh to your liking, paying particular attention to the kmer, cvCut, expCov, and other flags

To Run:

perl fastaAllSize mysequences.fa > mysequences.stat or gunzip -c mysequences.fa.gz | fastaAllSize > mysequences.stat Substitute fastqAllSize for fastq files.
./permute.sh mysequences (leave out the .fa)

https://github.com/leipzig/standardized-velvet-assembly-report

Address of the bookmark: https://github.com/leipzig/standardized-velvet-assembly-report

GAM-NGS: genomic assemblies merger for next generation sequencing

Jit — Mon, 19 Dec 2016 06:07:05 -0600

GAM-NGS (Genomic Assemblies Merger for Next Generation Sequencing), whose primary goal is to merge two or more assemblies in order to enhance contiguity and correctness of both. GAM-NGS does not rely on global alignment: regions of the two assemblies representing the same genomic locus (called blocks) are identified through reads' alignments and stored in a weightedgraph. The merging phase is carried out with the help of this weighted graph that allows an optimal resolution of local problematic regions.

Address of the bookmark: https://github.com/vice87/gam-ngs

Genome Assembly Tutorial

Abhimanyu Singh — Tue, 20 Dec 2016 07:56:01 -0600

If genomes were completely random sequences in a statistical sense, 'overlap-consensus-layout' method would have been enough to assemble large genomes from Sanger reads. In contrast, real genomes often have long repetitive regions, and they are hard to assemble using overlap-consensus-layout approach. De Bruijn graph-based assembly approach was originally proposed to handle the assembly of repetitive regions better.

More at http://www.homolog.us/Tutorials/index.php?p=1.4&s=1

Address of the bookmark: http://www.homolog.us/Tutorials/index.php?p=1.4&s=1

HTSlib

Jit — Wed, 15 Mar 2017 11:38:05 -0500

Samtools is a suite of programs for interacting with high-throughput sequencing data. It consists of three separate repositories:

Samtools: Reading/writing/editing/indexing/viewing SAM/BAM/CRAM format
BCFtools: Reading/writing BCF2/VCF/gVCF files and calling/filtering/summarising SNP and short indel sequence variants
HTSlib: A C library for reading/writing high-throughput sequencing data

Samtools and BCFtools both use HTSlib internally, but these source packages contain their own copies of htslib so they can be built independently.

Address of the bookmark: http://www.htslib.org/

MetaBAT: An Efficient Tool for Accurately Reconstructing Single Genomes from Complex Microbial Communities

Jit — Mon, 06 Mar 2017 03:44:34 -0600

MetaBAT, An Efficient Tool for Accurately Reconstructing Single Genomes from Complex Microbial Communities

Grouping large genomic fragments assembled from shotgun metagenomic sequences to deconvolute complex microbial communities, or metagenome binning, enables the study of individual organisms and their interactions. Here we developed an automated metagenome binning software, called MetaBAT, which integrates empirical probabilistic distances of genome abundance and tetranucleotide frequency. Tested on both synthetic and real metagenome datasets, MetaBAT outperforms alternative methods in both accuracy and computational efficiency. Applying MetaBAT to an assembly from 1,704 human gut samples formed 1,634 genome bins (>200kb) in 3 hours, where 621 genome bins are >50% complete with <5% contamination from other species. Further analysis shows that the quality of these genome bins approaches manually curated genomes.

Address of the bookmark: https://bitbucket.org/berkeleylab/metabat

gbtools: Interactive Visualization of Metagenome Bins in R

Jit — Sun, 26 Mar 2017 15:41:31 -0500

We have developed gbtools, a software package that allows users to visualize metagenomic assemblies by plotting coverage (sequencing depth) and GC values of contigs, and also to annotate the plots with taxonomic information. Different sets of annotations, including taxonomic assignments from conserved marker genes or SSU rRNA genes, can be imported simultaneously; users can choose which annotations to plot. Bins can be manually defined from plots, or be imported from third-party binning tools and overlaid onto plots, such that results from different methods can be compared side-by-side. gbtools reports summary statistics of bins including marker gene completeness, and allows the user to add or subtract bins with each other.

Tool at https://github.com/kbseah/genome-bin-tools

Address of the bookmark: http://journal.frontiersin.org/article/10.3389/fmicb.2015.01451/full

Understanding PacBio

Jitendra Narayan — Fri, 24 Feb 2017 10:17:36 -0600

This tutorial includes resources for learning more about PacBio data and bioinformatics analysis, and includes content suitable for both beginners and experts. Below are links to training modules (webinars and PowerPoint presentations) to help you get started with your data processing, as well as information for specialized applications.

Training Resources:

Specialized Applications:

Address of the bookmark: https://github.com/PacificBiosciences/Bioinformatics-Training/wiki