BOL: Related items

ACANA: An accurate and consistent alignment tool for DNA sequences

Jit — Wed, 06 Dec 2017 09:45:29 -0600

ACANA is an accurate and consistent alignment tool for DNA sequences. ACANA is specifically designed for aligning sequences that share only some moderately conserved regions and/or have a high frequency of long insertions or deletions. It attempts to combine the best of local and global alignments algorithms in searching for evolutionarily related regions of sequences in order to achieve the best alignment. ACANA is also robust to the small changes of alignment parameters, particularly the gap extension score. As an accurate alignment tool, ACANA is particularly useful in comparative sequence analysis for identifying conserved functional regulatory elements.

Address of the bookmark: https://www.niehs.nih.gov/research/resources/software/biostatistics/acana/index.cfm

Instructions for Creating Your Own R Package

Jit — Wed, 19 Feb 2020 01:22:48 -0600

The following is a step-by-step guide to creating your own R package. Even beyond this course, youmay find this useful for storing functions you create for your own research or for editing existingR packages to suit your needs.

This guide contains three different sets of instructions. If you use RStudio, you can follow the “Ba-sic Instructions” in Section 2 which involve using RStudio’s interface.

Address of the bookmark: http://web.mit.edu/insong/www/pdf/rpackage_instructions.pdf

dupRadar package

Jit — Sun, 04 Feb 2018 14:28:57 -0600

The dupRadar package gives an insight into the duplication problem by graphically relating the gene expression level and the duplication rate present on it. Thus, failed experiments can be easily identified at a glance

Address of the bookmark: https://bioconductor.org/packages/3.7/bioc/vignettes/dupRadar/inst/doc/dupRadar.html

PANEV: an R package for a pathway-based network visualization

Jit — Sun, 09 Feb 2020 12:41:52 -0600

PANEV (PAthway NEtwork Visualizer) is an R package set for gene/pathway-based network visualization. Based on information available on KEGG, it visualizes genes within a network of multiple levels (from 1 to n) of interconnected upstream and downstream pathways. The network graph visualization helps to interpret functional profiles of a cluster of genes.

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3371-7

Address of the bookmark: https://github.com/vpalombo/PANEV

kebabs: package provides functionality for kernel based analysis of biological sequences via Support Vector Machine (SVM) based methods

Rahul Nayak — Fri, 04 Mar 2022 00:14:11 -0600

The kebabs package provides functionality for kernel based analysis of biological sequences via Support Vector Machine (SVM) based methods. Biological sequences include DNA, RNA, and amino acid (AA) sequences. Sequence kernels define similarity measures between sequences. The package implements some of the most important kernels for sequence analysis in a very flexible and efficient way and extends the standard position-independent functionality of these kernels in a novel way to take the position of patterns in the sequences into account for the similarity measure.

http://www.bioinf.jku.at/software/kebabs/

http://bioconductor.org/packages/release/bioc/vignettes/kebabs/inst/doc/kebabs.pdf

Address of the bookmark: http://www.bioinf.jku.at/software/kebabs/

Alignment of closely related whole genomes/scaffolds

Rahul Nayak — Fri, 29 Jan 2016 10:37:27 -0600

With the relative ease and low cost of current generation sequencing technologies has led to a dramatic increase in the number of sequenced genomes for species across the tree of life. This increasing volume of data requires tools that can quickly compare multiple whole-genome sequences, millions of base pairs in length, to aid in the study of populations, pan-genomes, and genome evolution.This bookmaks have been created to report new tools for whole genome alignments.

Please report new whole genome alignment tools under comment sections.

Address of the bookmark: http://www.cs.utoronto.ca/~brudno/721.full.pdf

Understanding reads mapping and flags !

Jit — Thu, 25 Apr 2019 09:06:20 -0500

Linear Alignment: An alignment of a read to a single reference sequence that may include insertions, deletions, skips and clipping, but may not include direction changes (i.e. one portion of the alignment on forward strand and another portion of alignment on reverse strand).

Chimeric Alignment: An alignment of a read that cannot be represented as a linear alignment. Typically, one of the linear alignments in a chimeric alignment is considered the “representative” alignment, and the others are called “supplementary” and are distinguished by the supplementary alignment flag.

Chimeric reads are indicative of structural variation in DNA-seq and it may indicate the presence of chimeric genes in RNA-seq.

In short, chimeric reads can be split in to two or more parts, each part would be mapped to reference(it’s not hard-clipped), the total length of the mapped part is longger than read length.

Representative alignment: A chimeric alignment that is represented as a set of linear alignments that do not have large overlaps typically has one linear alignment that is considered the representative alignment.

One read can align to multiple positions, we can find one alignmnet position which sequence do not have large overlaps, it called representative alighment, for other alignment positions, we called them supplementary alignment.

It seems that GATK can realignment those representative reads to the correctly position via RealignerTargetCreator and IndelRealigner. (WARNING: I am not quite sure if I understand this correctly. If someone could help me, please leave me a message below, thanks, thanks.)

Supplementary Alignment: A chimeric reads but not a representative reads.

Primary Alignment and Secondary Alignment: A read may map ambiguously to multiple locations, e.g. due to repeats. Only one of the multiple read alignments is considered primary, and this decision may be arbitrary. All other alignments have the secondary alignment flag.

Many-to-many pairwise alignments of two sequence sets

Poonam Mahapatra — Tue, 19 Jun 2018 08:34:15 -0500

needleall reads a set of input sequences and compares them all to one or more sequences, writing their optimal global sequence alignments to file. It uses the Needleman-Wunsch alignment algorithm to find the optimum alignment (including gaps) of two sequences along their entire length. The algorithm uses a dynamic programming method to ensure the alignment is optimum, by exploring all possible alignments and choosing the best. A scoring matrix is read that contains values for every possible residue or nucleotide match. Needleall finds the alignment with the maximum possible score where the score of an alignment is equal to the sum of the matches taken from the scoring matrix, minus penalties arising from opening and extending gaps in the aligned sequences. The substitution matrix and gap opening and extension penalties are user-specified.

Address of the bookmark: http://emboss.sourceforge.net/apps/release/6.6/emboss/apps/needleall.html

BamView: a free interactive display of read alignments in BAM data files

Neel — Fri, 09 Nov 2018 13:43:22 -0600

To run the application on UNIX from the downloaded jar file run the UNIX:

java -mx512m -jar BamView.jar

and extra command line options are given when '-h' is used:

java -jar BamView.jar -h

BAM files can be specified on the command line with the '-a' option:

java -mx512m -jar BamView.jar -a pathToFile/sorted.bam

If a BAM filename is not given on the command line BamView will prompt for a file to be entered. The BAM index file should have the same name as the BAM file but with a '.bai' suffix. Multiple BAM files can be loaded and overlaid in the viewer. To make this easier BamView will read in files that contain a list of filenames.

Address of the bookmark: http://bamview.sourceforge.net/

Want to Know which genome assembler rule the world ?

Rahul Agarwal — Sun, 11 Aug 2013 11:42:32 -0500

Assemblathon 2: evaluating de novo methods of genome assembly

http://www.gigasciencejournal.com/content/2/1/10/abstract

http://blogs.nature.com/news/2013/07/genome-assembly-contest-prompts-soul-searching.html

http://assemblathon.org/post/44431915644/feedback-and-analysis-of-the-assemblathon-2-p