BOL: Related items

HOMER: Software for motif discovery and next-gen sequencing analysis

Neel — Tue, 26 Apr 2016 03:48:23 -0500

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.

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

RNA-Seq

Microarray

Basic analysis of Affymetrix Gene Expression Arrays using R/Bioconductor

General Tips for Data Analysis

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

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

YASS :: genomic similarity search tool

Jit — Mon, 02 May 2016 09:26:00 -0500

YASS is a genomic similarity search tool, for nucleic (DNA/RNA) sequences in fasta or plain text format (it produces local pairwise alignments). Like most of the heuristic pairwise local alignment tools for DNA sequences (FASTA, BLAST, PATTERNHUNTER, BLASTZ/LASTZ, LAST ...), YASS uses seeds to detect potential similarity regions, and then tries to extend them to local alignments. This genomic search tool uses multiple transition constrained spaced seeds that enable to search more fuzzy repeats, as non-coding DNA/RNA. Another simple, but interesting feature is that you can specify the seed pattern used in the search step (as provided for example by iedera).

Main features of YASS are:

multiple, possibly overlapping seeds and a new hit criterion to ensure a good sensitivity/selectivity trade-off
transition-constrained spaced seeds to improve sensitivity (transition mutations are purine to purine [A<->G] or pyrimidine to pyrimidine [C<->T])
using different scoring schemes with bit-score and E-value evaluated according to the sequence background frequencies
parameterizable output filter for low complexity repeats
reporting of various alignment statistical parameters (mutation bias along triplets, transition/transversion)
post-processing step to group gapped alignments

Address of the bookmark: http://bioinfo.lifl.fr/yass/

EXCAVATOR2tool

Bulbul — Wed, 30 Nov 2016 04:09:19 -0600

EXCAVATOR2 is a collection of bash, R and Fortran scripts and codes that analyses Whole Exome Sequencing (WES) data to identify CNVs. EXCAVATOR2 enhances the identification of all genomic CNVs, both overlapping and non-overlapping targeted exons by integrating the analysis of In-targets and Off- targets reads. Specifically, it improves the precision of calling CNVs overlapping targeted exons from WES data and enlarges the spectrum of detectable CNVs to off-target events.
EXCAVATOR2 can be effectively employed for the identification of CNVs in small as well as large-scale re-sequencing population and cancer studies. Lastly, it’s of particular interest that all WES experiments can be re-analysed using our method with the beneficial effect to identify novelCNVs in extra-exonic regions by having the full-genome CN profile.

Address of the bookmark: https://sourceforge.net/projects/excavator2tool/

fqtools

Jit — Thu, 08 Dec 2016 09:31:12 -0600

fqtools is a software suite for fast processing of FASTQ files. Various file manipulations are supported. See below for a full list of the subcommands available and a brief description of their purpose. Most of the individual subcommands will take either a single file or a pair of files as input. If no input file is specified, fqtools will attempt to read data from stdin. In this case, it is advisabe to specify the format of the data provided. For subcommands that generate FASTQ data, either a single file or a pair of files will be generated. If no -o argument is provided, single files will be writted to stdout.

Address of the bookmark: https://github.com/alastair-droop/fqtools

4DGenome

Jitendra Narayan — Mon, 04 Jul 2016 00:44:55 -0500

Records in 4DGenome are compiled through comprehensive literature curation of experimentally-derived and computationally-predicted interactions. The current release contains 4,433,071 experimentally-derived and 3,605,176 computationally-predicted interactions in 5 organisms. Experimental data cover both high throughput datasets and individiual focused studies.

All interaction data are freely available in a standardized file format. Records can be queried by genomic regions, gene names, organism, and detection technology.

Address of the bookmark: http://4dgenome.research.chop.edu/

CLgenomics

Radha Agarkar — Fri, 03 Mar 2017 09:57:28 -0600

CLgenomics is a standalone desktop software specifically designed for bacterial genome analysis. This program has a powerful multi-genome browser, which enables rapid and responsive exploration of bacterial genomes.

To use CLgenomics, individual genome data (genome sequences + annotation details) are compiled and saved in a specially formatted file called CLG (ChunLab Genomics). Each CLG file corresponds with one bacterial genome. If multiple genomes are being considered and compared, multiple CLG files are needed. ChunLab offers >40,000 CLG files of publicly available Bacterial and Archaeal genomes.

Address of the bookmark: https://chunlab.wordpress.com/clgenomics-software/

Sample bandage input file for visual analysis

Jit — Wed, 06 Jan 2021 03:51:50 -0600

Sample bandage input file for visual analysis ...

LAST

Bulbul — Mon, 19 Dec 2016 14:07:53 -0600

LAST can:

Handle big sequence data, e.g:
- Compare two vertebrate genomes
- Align billions of DNA reads to a genome
Indicate the reliability of each aligned column.
Use sequence quality data properly.
Compare DNA to proteins, with frameshifts.
Compare PSSMs to sequences
Calculate the likelihood of chance similarities between random sequences.
Do split and spliced alignment.
Train alignment parameters for unusual kinds of sequence (e.g. nanopore).

Address of the bookmark: http://last.cbrc.jp/

coursera genome assembly tutorial

Jit — Sat, 25 Nov 2017 08:57:25 -0600

Solutions to Coursera Genome Sequencing (Bioinformatics II)

Address of the bookmark: https://github.com/iansealy/coursera-assembly

Nanopolis: polish a genome assembly

Rahul Nayak — Thu, 26 Jul 2018 04:51:28 -0500

Software package for signal-level analysis of Oxford Nanopore sequencing data. Nanopolish can calculate an improved consensus sequence for a draft genome assembly, detect base modifications, call SNPs and indels with respect to a reference genome and more (see Nanopolish modules, below).

Quickstart

http://nanopolish.readthedocs.io/en/latest/quickstart_consensus.html

Algorithms

http://simpsonlab.github.io/2017/06/30/nanopolish-v0.7.0/

Address of the bookmark: https://github.com/jts/nanopolish