BOL: Related items

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

Beagle

Jit — Thu, 27 Oct 2016 11:19:00 -0500

Beagle is a software package that performs genotype calling, genotype phasing, imputation of ungenotyped markers, and identity-by-descent segment detection.

Beagle version 4.1 has a more accurate genotype phasing algorithm and a very fast and accurate genotype imputation algorithm. Version 4.1 also has several changes to the command line arguments which are described in the release notes. The "ped" argument has no effect in version 4.1. If your data contains nuclear families and you want to model the parent-offspring relationships when phasing genotypes, please use version 4.0.

If you use Beagle 4.1 in a published analysis, please report the program version and cite the appropriate article.

The citation for Beagle's phasing algorithm is:

S R Browning and B L Browning (2007) Rapid and accurate haplotype phasing and missing data inference for whole genome association studies by use of localized haplotype clustering. Am J Hum Genet 81:1084-1097.doi:10.1086/521987

The citation for Beagle's genotype imputation algorithm is:

B L Browning and S R Browning (2016). Genotype imputation with millions of reference samples. Am J Hum Genet 98:116-126.doi:10.1016/j.ajhg.2015.11.020

The citation for Beagle's IBD detection algorithm is:

B L Browning and S R Browning (2013). Improving the accuracy and efficiency of identity-by-descent detection in population data. Genetics 194(2):459-71.doi:10.1534/genetics.113.150029

Address of the bookmark: http://faculty.washington.edu/browning/beagle/beagle.html

HGA

Jit — Tue, 29 Nov 2016 07:25:53 -0600

HGA tool version 1.0 This tool helps to apply the Hierarchical Genome Assembly (HGA) method. The tool will apply: 1. Partitioning a given reads dataset into a given number of partitions. 2. Assembling each partitions using a pre-specified assembler (Velvet or SPAdes in this version) and using a given kmer size. 3. Merging all the assemblies of the partition. 4. Combining all the assemblies of the partition (using velvet with kmer value of 31). 5. Finaly, re-assembling the whole dataset with the merged contigs or the combined contigs, using a given kmer size.

https://github.com/aalokaily/Hierarchical-Genome-Assembly-HGA

Address of the bookmark: https://github.com/aalokaily/Hierarchical-Genome-Assembly-HGA

MyPro: A seamless pipeline for automated prokaryotic genome assembly and annotation

Neel — Thu, 15 Dec 2016 05:47:35 -0600

MyPro is an improved genomics software pipeline for prokaryotic genomes. MyPro is user-friendly and requires minimal programming skills. High-quality prokaryotic genome assembly and annotation can be obtained with ease. It performed better than de novo assemblers and contig integration software. Produces more contiguous assemblies, higher N50 values and lower number of contigs.

More at https://sourceforge.net/projects/sb2nhri/files/MyPro/

Address of the bookmark: http://www.sciencedirect.com/science/article/pii/S0167701215001207

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/

Randomness and Probability

Jit — Tue, 08 Nov 2016 07:17:32 -0600

Randomness and Probability

Randomness and probability are two differnet concepts: probaility is a measure (according to measure theory) which measures the randomness. Randomness is the object to be measured by probability. For example, probability is a mapping from randomness to the real number between 0 and 1. The similar examples are that the entropy measures the uncertanity; product of length and width measures the area of rectangle etc.

Please see “A mathematical theory of ability measure” by N. Kong ets for more examples to answer this question.

Bioistats Online course

Abhimanyu Singh — Thu, 10 Nov 2016 04:22:51 -0600

One of our primary focuses will be to develop an understanding of the various ways in which we can assign a probability to some chance event. We'll also learn the fundamental properties of probability, investigate how probability behaves, and learn how to calculate the probability of a new chance event.

This book is handy understanding basic concepts.

Address of the bookmark: https://onlinecourses.science.psu.edu/stat414/node/287

Prodigal (Prokaryotic Dynamic Programming Genefinding Algorithm)

Abhimanyu Singh — Thu, 29 Dec 2016 03:26:45 -0600

Prodigal (Prokaryotic Dynamic Programming Genefinding Algorithm) is a microbial (bacterial and archaeal) gene finding program developed at Oak Ridge National Laboratory and the University of Tennessee. Key features of Prodigal include:

Speed: Prodigal is an extremely fast gene recognition tool (written in very vanilla C). It can analyze an entire microbial genome in 30 seconds or less.
Accuracy: Prodigal is a highly accurate gene finder. It correctly locates the 3' end of every gene in the experimentally verified Ecogene data set (except those containing introns). It possesses a very sophisticated ribosomal binding site scoring system that enables it to locate the translation initiation site with great accuracy (96% of the 5' ends in the Ecogene data set are located correctly).
Specificity: Prodigal's false positive rate compares favorably with other gene identification programs, and usually falls under 5%.
GC-Content Indifferent: Prodigal performs well even in high GC genomes, with over a 90% perfect match (5'+3') to the Pseudomonas aeruginosa curated annotations.
Metagenomic Version: Prodigal can run in metagenomic mode and analyze sequences even when the organism is unknown.
Ease of Use: Prodigal can be run in one step on a single genomic sequence or on a draft genome containing many sequences. It does not need to be supplied with any knowledge of the organism, as it learns all the properties it needs to on its own.
Open Source: Prodigal source code is freely available under the General Public License.

Download the latest version of Prodigal at the Prodigal github page.
or
Browse the wiki documenation.

Address of the bookmark: http://prodigal.ornl.gov/

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/

DeCoSTAR - Detection of Co-evolution

Jit — Fri, 14 Apr 2017 06:27:25 -0500

DeCoSTAR is a software which aims at reconstructing ancestral gene or genome organizations, in the form of sets of neighborhood relations -adjacencies- between pairs of ancestral genes or gene domains.
Ancestral genes or domains are deduced from reconciled gene trees in a context of birth, speciation, duplication, loss, transfer, which are either given as input or computed with the ecceTERA package, to which DeCoSTAR is integrated. DeCoSTAR constructs parsimonious scenarios of gains and breakages of adjacencies, and contains in particular all the features of previous software DeCo, DeCoLT, ArtDeCo and DeClone. It provides statistical supports on ancestral adjacencies, or the possibility to handle badly assembled genomes.
DeCoSTAR is able to reconstruct the histories of domains inside genes, including gene fusion and fission events, as well as ancestral genome structures for dozens of whole genomes from all kingdoms of life in a few minutes.

Address of the bookmark: http://pbil.univ-lyon1.fr/software/DeCoSTAR/