<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/41009?offset=450 https://bioinformaticsonline.com/bookmarks/view/27113/picard Fri, 29 Apr 2016 08:21:54 -0500 https://bioinformaticsonline.com/bookmarks/view/27113/picard <![CDATA[Picard]]> Picard is a set of command line tools for manipulating high-throughput sequencing (HTS) data and formats such as SAM/BAM/CRAM and VCF. These file formats are defined in the Hts-specs repository. See especially the SAM specification and the VCF specification.

Note that the information on this page is targeted at end-users. For developers, the source code, building instructions and implementation/development resources are available on GitHub.

The Picard toolkit is open-source under the MIT license and free for all uses.

Enjoy!

Address of the bookmark: http://broadinstitute.github.io/picard/

]]> Neel https://bioinformaticsonline.com/bookmarks/view/27110/easyfig Fri, 29 Apr 2016 05:49:39 -0500 https://bioinformaticsonline.com/bookmarks/view/27110/easyfig <![CDATA[Easyfig]]> Easyfig has moved to github, for newer releases of Easyfig please visit our new webpage - https://mjsull.github.io/Easyfig.  Easyfig is a Python application for creating linear comparison figures of multiple genomic loci with an easy-to-use graphical user interface (GUI).

More at http://easyfig.sourceforge.net/

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

]]> Poonam Mahapatra https://bioinformaticsonline.com/bookmarks/view/26968/scalce Fri, 15 Apr 2016 05:09:51 -0500 https://bioinformaticsonline.com/bookmarks/view/26968/scalce <![CDATA[SCALCE]]> SCALCE (/skeɪlz/, a.k.a. boosting Sequence Compression Algorithms using Locally ConsistentEncoding) is a tool for compressing FASTQ files. It is designed specifically for the Illumina-generated FASTQ files, but supports any valid FASTQ with consistent read lengths. 

More at http://sfu-compbio.github.io/scalce/

Address of the bookmark: http://sfu-compbio.github.io/scalce/

]]> Surabhi Chaudhary https://bioinformaticsonline.com/bookmarks/view/27035/spades Tue, 19 Apr 2016 08:37:08 -0500 https://bioinformaticsonline.com/bookmarks/view/27035/spades <![CDATA[SPAdes]]> SPAdes – St. Petersburg genome assembler – is intended for both standard isolates and single-cell MDA bacteria assemblies. This manual will help you to install and run SPAdes. SPAdes version 3.7.1 was released under GPLv2 on March 8, 2016 and can be downloaded from http://bioinf.spbau.ru/en/spades.

Manual at http://spades.bioinf.spbau.ru/release3.7.1/manual.html

Address of the bookmark: http://bioinf.spbau.ru/spades

]]> Abhimanyu Singh https://bioinformaticsonline.com/bookmarks/view/27078/homer-software-for-motif-discovery-and-next-gen-sequencing-analysis Tue, 26 Apr 2016 03:48:23 -0500 https://bioinformaticsonline.com/bookmarks/view/27078/homer-software-for-motif-discovery-and-next-gen-sequencing-analysis <![CDATA[HOMER: Software for motif discovery and next-gen sequencing analysis]]> This tutorial covers topics independently of HOMER, and represents knowledge which is important to know before diving head first into more advanced analysis tools such as HOMER.

  1. Setting up your computing environment
  2. Retrieving and storing sequencing files (your own data or from public sources)
  3. Checking sequence quality, trimming, general sequence manipulation
  4. Mapping reads to a reference genome
  5. Manipulating SAM/BAM alignment files
  6. Visualizing data in a genome browser


RNA-Seq

  1. De novo transcript discovery and differential analysis with Cufflinks
  2. Differential expression analysis with R/Bioconductor
  3. Clustering of large expression datasets (microarray or RNA-Seq)


Microarray

  1. Basic analysis of Affymetrix Gene Expression Arrays using R/Bioconductor

General Tips for Data Analysis

  1. Excel workarounds, adding gene annotation, X-Y plots tips, etc.

Address of the bookmark: http://homer.salk.edu/homer/basicTutorial/

]]> Neel https://bioinformaticsonline.com/bookmarks/view/27094/smash-an-alignment-free-method-to-find-and-visualise-rearrangements-between-pairs-of-dna-sequences Tue, 26 Apr 2016 12:18:49 -0500 https://bioinformaticsonline.com/bookmarks/view/27094/smash-an-alignment-free-method-to-find-and-visualise-rearrangements-between-pairs-of-dna-sequences <![CDATA[Smash: An alignment-free method to find and visualise rearrangements between pairs of DNA sequences]]> Smash is a completely alignment-free method/tool to find and visualise genomic rearrangements. The detection is based on conditional exclusive compression, namely using a FCM (Markov model), of high context order (typically 20). For visualisation, Smash outputs a SVG image, with an ideogramoutput architecture, where the patterns are represented with several HSV values (only value varies). The method can perform both in small- and large-scale. Nevertheless is more directed to large-scale since that the main aim of the research is to know where the large-scale [chromosomal by chromosome] of several primates was equal/different, having at a glance a map of the entire genomes.

Address of the bookmark: http://bioinformatics.ua.pt/software/smash/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/29343/accnet Fri, 07 Oct 2016 05:22:11 -0500 https://bioinformaticsonline.com/bookmarks/view/29343/accnet <![CDATA[AccNET]]> AccNET is a Perl application that presents a new way to study the accessory genome of a given set of organisms. Using the proteomes of these organisms, AccNET create a bipartite network compatible with common network analysis platforms. AccNET collects phylogenetic and functional information in a network improving the analysis capability. Networks offer a new perspective of organism organization through elements acquired by horizontal gene transfers and not constricted by hierarchical structures.

More at https://www.youtube.com/watch?v=vdGuy1GAJrQ

Address of the bookmark: https://sourceforge.net/projects/accnet/

]]> Jitendra Narayan https://bioinformaticsonline.com/bookmarks/view/27427/rcircos-an-r-package-for-circos-2d-track-plots Fri, 20 May 2016 11:01:13 -0500 https://bioinformaticsonline.com/bookmarks/view/27427/rcircos-an-r-package-for-circos-2d-track-plots <![CDATA[RCircos: an R package for Circos 2D track plots]]> RCircos package provides a simple and flexible way to make Circos 2D track plots with R and could be easily integrated into other R data processing and graphic manipulation pipelines for presenting large-scale multi-sample genomic research data. It can also serve as a base tool to generate complex Circos images.

More at https://bitbucket.org/henryhzhang/rcircos/src

Address of the bookmark: https://bitbucket.org/henryhzhang/rcircos/src

]]> Jit https://bioinformaticsonline.com/bookmarks/view/28809/kissplice Tue, 16 Aug 2016 08:34:19 -0500 https://bioinformaticsonline.com/bookmarks/view/28809/kissplice <![CDATA[KisSplice]]> KisSplice is a software that enables to analyse RNA-seq data with or without a reference genome. It is an exact local transcriptome assembler that allows to identify SNPs, indels and alternative splicing events. It can deal with an arbitrary number of biological conditions, and will quantify each variant in each condition. It has been tested on Illumina datasets of up to 1G reads. Its memory consumption is around 5Gb for 100M reads.

KisSplice is not a full-length transcriptome assembler. This means that it will output the variable regions of the transcripts, not reconstruct them entirely.

KisSplice comes as a workflow, with several possible post-treatments meant to facilitate the analysis of the results. The choice of the post-treatment depends on the availability of a reference genome/transcriptome and on the need to perform a differential analysis, as summarised in the following table.

Address of the bookmark: http://kissplice.prabi.fr/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/27818/gaemr Tue, 14 Jun 2016 06:18:37 -0500 https://bioinformaticsonline.com/bookmarks/view/27818/gaemr <![CDATA[GAEMR]]> The Genome Assembly Evaluation Metrics and Reporting (GAEMR) package is an assembly analysis framework composed a number of integrated modules. These modules can be executed as a single program to generate a complete analysis report, or executed individually to generate specific charts and tables. GAEMR standardizes input by converting a variety of read types to Binary Alignment Map (BAM) format, allowing a single input format to be entered into GAEMR’s analysis pipeline, hence enabling the generation of standard reports.

GAEMR’s analysis philosophy is centered on contiguity, correctness, and completeness -- how many pieces in an assembly composed of, how well those pieces accurately represent the genome sequenced, and how much of that genome is represented by those pieces. By performing over twenty different analyses based on these principles, GAEMR gives a clear picture of the condition of a genome assembly. 

Address of the bookmark: https://www.broadinstitute.org/software/gaemr/

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