BOL: Related items

GKNO

Neel — Fri, 20 May 2016 18:56:37 -0500

gkno opens the world of complex bioinformatic analysis to people of all level of computational expertise. This site contains documentation, tutorials and information on all the tools that comprise gkno.

http://gkno.me/how-to/install.html

http://gkno.me/software.html

Address of the bookmark: http://gkno.me/

LoRMA: a tool for correcting sequencing errors in long reads such those produced by Pacific Biosciences sequencing machines

Jit — Wed, 15 Jun 2016 17:18:36 -0500

LoRMA is a tool for correcting sequencing errors in long reads such those produced by Pacific Biosciences sequencing machines.

Publication:

L. Salmela, R. Walve, E. Rivals, and E. Ukkonen: Accurate selfcorrection of errors in long reads using de Bruijn graphs. Accepted to RECOMB-Seq 2016.

Download:

Address of the bookmark: https://www.cs.helsinki.fi/u/lmsalmel/LoRMA/

HivePlot

Jit — Thu, 16 Feb 2017 11:39:34 -0600

The hive plot is a rational visualization method for drawing networks. Nodes are mapped to and positioned on radially distributed linear axes — this mapping is based on network structural properties. Edges are drawn as curved links. Simple and interpretable.

The purpose of the hive plot is to establish a new baseline for visualization of large networks — a method that is both general and tunable and useful as a starting point in visually exploring network structure.

More at http://www.hiveplot.com/

Address of the bookmark: http://www.hiveplot.com/

BBSplit: Read Binning Tool for Metagenomes and Contaminated Libraries

Poonam Mahapatra — Wed, 03 Jan 2018 00:25:27 -0600

BBSplit internally uses BBMap to map reads to multiple genomes at once, and determine which genome they match best. This is different than with ordinary mapping. If a genome (say, human) contains an exact repeat somewhere, reads mapping to it will be mapped ambiguously. But if you want to determine whether reads are mouse or human, it does not matter whether they map ambiguously within human, only whether they are ambiguous between human and mouse. BBSplit tracks this additional ambiguity information and decides how to use it based on the “ambig2” flag. The normal use of BBSplit is like Seal, either quantifying how many reads go to each reference, or splitting the reads into multiple output files, one per reference. BBSplit can only be run using references indexed with BBSplit, as they contain additional information regarding which sequences came from which reference file.

BBSplit is a tool that bins reads by mapping to multiple references simultaneously, using BBMap. The reads go to the bin of the reference they map to best. There are also disambiguation options, such that reads that map to multiple references can be binned with all of them, none of them, one of them, or put in a special "ambiguous" file for each of them. Paired reads will always be kept together.

For example, if you had a library of something that was contaminated with e.coli and salmonella, you could do this:

bbsplit.sh in=reads.fq ref=ecoli.fa,salmonella.fa basename=out_%.fq outu=clean.fq int=t

This will produce 3 output files:
out_ecoli.fq (ecoli reads)
out_salmonella.fq (salmonella reads)
clean.fq (unmapped reads)

In this case, "int=t" means that the input file is paired and interleaved. For single-end reads you would leave that out. For paired reads in 2 files, you would do this:
bbsplit.sh in1=reads1.fq in2=reads2.fq ref=ecoli.fa,salmonella.fa basename=out_%.fq outu1=clean1.fq outu2=clean2.fq

BBSplit is available here:
https://sourceforge.net/projects/bbmap/

The sensitivity can be raised to be equivalent to BBMap with these flags: "minratio=0.56 minhits=1 maxindel=16000"

lordFAST: sensitive and Fast Alignment Search Tool for LOng noisy Read sequencing Data

BioJoker — Tue, 27 Nov 2018 04:43:57 -0600

lordFAST is a sensitive tool for mapping long reads with high error rates. lordFAST is specially designed for aligning reads from PacBio sequencing technology but provides the user the ability to change alignment parameters depending on the reads and application.

lordFAST, a novel long-read mapper that is specifically designed to align reads generated by PacBio and potentially other SMS technologies to a reference. lordFAST not only has higher sensitivity than the available alternatives, it is also among the fastest and has a very low memory footprint.

Address of the bookmark: https://github.com/vpc-ccg/lordfast

G-NEST: The Gene NEighborhood Scoring Tool

Neel — Fri, 25 Sep 2020 20:09:18 -0500

The Gene NEighborhood Scoring Tool (G-NEST) combines genomic location, gene expression, and evolutionary sequence conservation data to score putative gene neighborhoods across all window sizes. Primary author of final code = William F. Martin. Example data files are in the separate repository.

Address of the bookmark: https://github.com/dglemay/G-NEST

Tools to access the quality of your assembled genome !

LEGE — Thu, 08 Aug 2024 23:31:18 -0500

FASTA VALIDATOR + SEQKIT RMDUP: FASTA validation
GENOMETOOLS GT GFF3VALIDATOR: GFF3 validation
ASSEMBLATHON STATS: Assembly statistics
GENOMETOOLS GT STAT: Annotation statistics
NCBI FCS ADAPTOR: Adaptor contamination pass/fail
NCBI FCS GX: Foreign organism contamination pass/fail
BUSCO: Gene-space completeness estimation
TIDK: Telomere repeat identification
LAI: Continuity of repetitive sequences
KRAKEN2: Taxonomy classification
HIC CONTACT MAP: Alignment and visualisation of HiC data
MUMMER → CIRCOS + DOTPLOT & MINIMAP2 → PLOTSR: Synteny analysis
MERQURY: K-mer completeness, consensus quality and phasing assessment

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/

Mulan: MUltiple sequence Local AligNment and conservation visualization tool

Rahul Nayak — Thu, 20 Jul 2017 08:02:32 -0500

Mulan performs multiple (2 or more) sequence alignments with an efficient and rapid "full local" alignment strategy that ensures a recapitulation of evolutionary sequence rearrangements (such as inversions and reshuffling) in any of the species. It combines refine and tba tools to align either "draft" or "finished" quality sequences. Mulan provides a dynamic graphical interface to align and visualize conservation profiles for evolutionarily distant and closely related species.

Input formats, automated data upload from the UCSC Genome Browser, gene annotation, annotation of repetitive elements, and progress report were previously described in the zPicture instructions and we refer the users to these materials for more details. This introduction is mainly focused on some novel features unique to the Mulan.

Address of the bookmark: https://mulan.dcode.org/mulanInstructions.php

COPE: an accurate k-mer-based pair-end reads connection tool to facilitate genome assembly

Jit — Wed, 06 Dec 2017 02:08:14 -0600

An efficient tool called Connecting Overlapped Pair-End (COPE) reads, to connect overlapping pair-end reads using k-mer frequencies. We evaluated our tool on 30× simulated pair-end reads from Arabidopsis thaliana with 1% base error. COPE connected over 99% of reads with 98.8% accuracy, which is, respectively, 10 and 2% higher than the recently published tool FLASH. When COPE is applied to real reads for genome assembly, the resulting contigs are found to have fewer errors and give a 14-fold improvement in the N50 measurement when compared with the contigs produced using unconnected reads.

Address of the bookmark: ftp://ftp.genomics.org.cn/pub/cope