<![CDATA[BOL: All site bookmarks]]> https://bioinformaticsonline.com/bookmarks/all?offset=740 https://bioinformaticsonline.com/bookmarks/view/36512/hisat2-a-fast-and-sensitive-alignment-program-for-mapping-next-generation-sequencing-reads Tue, 08 May 2018 04:27:22 -0500 https://bioinformaticsonline.com/bookmarks/view/36512/hisat2-a-fast-and-sensitive-alignment-program-for-mapping-next-generation-sequencing-reads <![CDATA[HISAT2: a fast and sensitive alignment program for mapping next-generation sequencing reads]]> HISAT2 is a fast and sensitive alignment program for mapping next-generation sequencing reads (both DNA and RNA) to a population of human genomes (as well as to a single reference genome). Based on an extension of BWT for graphs [Sirén et al. 2014], we designed and implemented a graph FM index (GFM), an original approach and its first implementation to the best of our knowledge. In addition to using one global GFM index that represents a population of human genomes, HISAT2 uses a large set of small GFM indexes that collectively cover the whole genome (each index representing a genomic region of 56 Kbp, with 55,000 indexes needed to cover the human population). These small indexes (called local indexes), combined with several alignment strategies, enable rapid and accurate alignment of sequencing reads. This new indexing scheme is called a Hierarchical Graph FM index (HGFM). 

more at https://ccb.jhu.edu/software/hisat2/index.shtml

Address of the bookmark: https://github.com/infphilo/hisat2

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/36510/scallop-reference-based-transcriptome-assembler-for-rna-seq Tue, 08 May 2018 04:23:27 -0500 https://bioinformaticsonline.com/bookmarks/view/36510/scallop-reference-based-transcriptome-assembler-for-rna-seq <![CDATA[Scallop: reference-based transcriptome assembler for RNA-seq]]> Scallop is an accurate reference-based transcript assembler. Scallop features its high accuracy in assembling multi-exon transcripts as well as lowly expressed transcripts. Scallop achieves this improvement through a novel algorithm that can be proved preserving all phasing paths from reads and paired-end reads, while also achieves both transcripts parsimony and coverage deviation minimization.

Scallop paper has been published at Nature Biotechnology. The datasets and scripts used in this paper to compare the performance of Scallop and other assemblers are available at scalloptest.

Please also checkout the podcast about Scallop (thanks Roman Cheplyaka for the interview). It is available at both the bioinformatics chat and iTunes.

 

https://github.com/Kingsford-Group/scallop

Address of the bookmark: https://github.com/Kingsford-Group/scallop

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/36508/mitobim-mitochondrial-baiting-and-iterative-mapping Tue, 08 May 2018 04:15:25 -0500 https://bioinformaticsonline.com/bookmarks/view/36508/mitobim-mitochondrial-baiting-and-iterative-mapping <![CDATA[MITObim - mitochondrial baiting and iterative mapping]]> This document contains instructions on how to use the MITObim pipeline described in Hahn et al. 2013. The full article can be found here. Kindly cite the article if you are using MITObim in your work. The pipeline was originally developed for Illumina data, but thanks to the versatility of the MIRA assembler, MITObim supports in principle also data from the Iontorrent, 454 and PacBio sequencing platforms.

Below you can find a few basic tutorials for how to run MITObim and I encorage you to give them a try with the testdata that comes with this Repo, just to make sure everything is running smoothly on your system. It'll only take a few minutes and will potentially safe you a lot of time down the line.

I provide further examples here as Jupyter notebooks. Get in touch if you feel like sharing your particular MITObim solution and I'd be happy to put it up here, too!

Address of the bookmark: https://github.com/chrishah/MITObim

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/36478/the-marvel-assembler Fri, 04 May 2018 19:18:41 -0500 https://bioinformaticsonline.com/bookmarks/view/36478/the-marvel-assembler <![CDATA[The MARVEL assembler]]> MARVEL consists of a set of tools that facilitate the overlapping, patching, correction and assembly of noisy (not so noisy ones as well) long reads.

The assembly process can be summarized as follows:

  1. overlap
  2. patch reads
  3. overlap (again)
  4. scrubbing
  5. assembly graph construction and touring
  6. optional read correction
  7. fasta file creation

Address of the bookmark: https://github.com/schloi/MARVEL

]]> Jit https://bioinformaticsonline.com/bookmarks/view/36476/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads Fri, 04 May 2018 19:16:22 -0500 https://bioinformaticsonline.com/bookmarks/view/36476/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads <![CDATA[Flye: Fast and accurate de novo assembler for single molecule sequencing reads]]> Flye is a de novo assembler for long and noisy reads, such as those produced by PacBio and Oxford Nanopore Technologies. The algorithm uses an A-Bruijn graph to find the overlaps between reads and does not require them to be error-corrected. After the initial assembly, Flye performs an extra repeat classification and analysis step to improve the structural accuracy of the resulting sequence. The package also includes a polisher module, which produces the final assembly of high nucleotide-level quality.

Address of the bookmark: https://github.com/fenderglass/Flye

]]> Jit https://bioinformaticsonline.com/bookmarks/view/36456/alpaca-a-hybrid-strategy-for-assembly-of-genomic-dna-shotgun-sequencing-reads Mon, 30 Apr 2018 04:38:40 -0500 https://bioinformaticsonline.com/bookmarks/view/36456/alpaca-a-hybrid-strategy-for-assembly-of-genomic-dna-shotgun-sequencing-reads <![CDATA[ALPACA: A hybrid strategy for assembly of genomic DNA shotgun sequencing reads.]]> ALPACA requires Celera Assembler 8.3 or later. It is recommended to build Celera Assembler from source. (Why? The pre-built binaries CA_8.3rc1 and CA8.3rc2 will work for any large data set. 

Detail paper at https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-017-3927-8

Address of the bookmark: https://github.com/VicugnaPacos/ALPACA

]]> Seema Singh https://bioinformaticsonline.com/bookmarks/view/36403/ngmlr-long-read-mapper-designed-to-align-pacbio-or-oxford-nanopore Wed, 25 Apr 2018 07:30:54 -0500 https://bioinformaticsonline.com/bookmarks/view/36403/ngmlr-long-read-mapper-designed-to-align-pacbio-or-oxford-nanopore <![CDATA[NGMLR: long-read mapper designed to align PacBio or Oxford Nanopore]]> CoNvex Gap-cost alignMents for Long Reads (ngmlr) is a long-read mapper designed to sensitively align PacBilo or Oxford Nanopore to (large) reference genomes. It was designed to quickly and correctly align the reads, including those spanning (complex) structural variations. Ngmlr uses an SV aware k-mer search to find approximate mapping locations for a read and then a banded Smith-Waterman alignment algorithm to compute the final alignment. Ngmlr uses a convex gap cost model that penalizes gap extensions for longer gaps less than for shorter ones to compute precise alignments. The gap model allows ngmlr to account for both the sequencing error and real genomic variations at the same time and makes it especially effective at more precisely identifying the position of breakpoints stemming from structural variations. The k-mer search helps to detect and split reads that cannot be aligned linearly, enabling ngmlr to reliably align reads to a wide range of different structural variations including nested SVs (e.g. inversions flanked by deletions).

Address of the bookmark: https://github.com/philres/ngmlr

]]> Jit https://bioinformaticsonline.com/bookmarks/view/36368/d3-javascript-for-visualization Mon, 23 Apr 2018 08:42:22 -0500 https://bioinformaticsonline.com/bookmarks/view/36368/d3-javascript-for-visualization <![CDATA[D3 javascript for visualization !]]> Welcome to the D3 gallery! More examples are available on bl.ocks.org/mbostock. If you want to share an example and don't have your own hosting, consider using Gist and bl.ocks.org. If you want to share or view live examples try vida.io.

Address of the bookmark: https://github.com/d3/d3/wiki/Gallery

]]> Jit https://bioinformaticsonline.com/bookmarks/view/36360/dendropy-a-python-library-for-phylogenetic-computing Mon, 23 Apr 2018 05:49:50 -0500 https://bioinformaticsonline.com/bookmarks/view/36360/dendropy-a-python-library-for-phylogenetic-computing <![CDATA[DendroPy: a Python library for phylogenetic computing]]> DendroPy is a Python library for phylogenetic computing. It provides classes and functions for the simulation, processing, and manipulation of phylogenetic trees and character matrices, and supports the reading and writing of phylogenetic data in a range of formats, such as NEXUS, NEWICK, NeXML, Phylip, FASTA, etc. Application scripts for performing some useful phylogenetic operations, such as data conversion and tree posterior distribution summarization, are also distributed and installed as part of the libary. DendroPy can thus function as a stand-alone library for phylogenetics, a component of more complex multi-library phyloinformatic pipelines, or as a scripting “glue” that assembles and drives such pipelines.

The primary home page for DendroPy, with detailed tutorials and documentation, is at:

DendroPy is also hosted in the official Python repository:

Requirements and Installation

DendroPy 4.x runs under Python 3 (all versions > 3.1) and Python 2 (Python 2.7 only).

You can install DendroPy by running:

 

More information is available here:

Address of the bookmark: https://pypi.org/project/DendroPy/

]]> Seema Singh https://bioinformaticsonline.com/bookmarks/view/36271/heap-a-highly-sensitive-and-accurate-snp-detection-tool-for-low-coverage-high-throughput-sequencing-data Thu, 19 Apr 2018 08:06:03 -0500 https://bioinformaticsonline.com/bookmarks/view/36271/heap-a-highly-sensitive-and-accurate-snp-detection-tool-for-low-coverage-high-throughput-sequencing-data <![CDATA[Heap: a highly sensitive and accurate SNP detection tool for low-coverage high-throughput sequencing data]]> Heap, that enables robustly sensitive and accurate calling of SNPs, particularly with a low coverage NGS data, which must be aligned to the reference genome sequences in advance. To reduce false positive SNPs, Heap determines genotypes and calls SNPs at each site except for sites at the both end of reads or containing a minor allele supported by only one read. Performance comparison with existing tools showed that Heap achieved the highest F-scores with low coverage (7X) restriction-site associated DNA sequencing reads of sorghum and rice individuals. This will facilitate cost-effective GWAS and GP studies in this NGS era. Code and documentation of Heap are freely available from https://github.com/meiji-bioinf/heap and our web site (http://bioinf.mind.meiji.ac.jp/lab/en/tools.html).

Address of the bookmark: https://github.com/meiji-bioinf/heap

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