<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/41896?offset=20 https://bioinformaticsonline.com/bookmarks/view/34328/dfast-a-flexible-prokaryotic-genome-annotation-pipeline-for-faster-genome-publication Tue, 14 Nov 2017 10:26:16 -0600 https://bioinformaticsonline.com/bookmarks/view/34328/dfast-a-flexible-prokaryotic-genome-annotation-pipeline-for-faster-genome-publication <![CDATA[DFAST: a flexible prokaryotic genome annotation pipeline for faster genome publication]]> We developed a prokaryotic genome annotation pipeline, DFAST, that also supports genome submission to public sequence databases. DFAST was originally started as an on-line annotation server, and to date, over 7,000 jobs have been processed since its first launch in 2016. Here, we present a newly implemented background annotation engine for DFAST, which is also available as a standalone command-line program. The new engine can annotate a typical-sized bacterial genome within 10 minutes, with rich information such as pseudogenes, translation exceptions, and orthologous gene assignment between given reference genomes. In addition, the modular framework of DFAST allows users to customize the annotation workflow easily and will also facilitate extensions for new functions and incorporation of new tools in the future.

Availability and Implementation

The software is implemented in Python 3 and runs in both Python 2.7 and 3.4– on Macintosh and Linux systems. It is freely available at https://github.com/nigyta/dfast_core/ under the GPLv3 license with external binaries bundled in the software distribution. An on-line version is also available at https://dfast.nig.ac.jp/.

Address of the bookmark: https://dfast.nig.ac.jp/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/36918/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads Tue, 12 Jun 2018 08:14:41 -0500 https://bioinformaticsonline.com/bookmarks/view/36918/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads <![CDATA[P_RNA_scaffolder: a fast and accurate genome scaffolder using paired-end RNA-sequencing reads]]> Address of the bookmark: http://www.fishbrowser.org/software/P_RNA_scaffolder/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/37796/grsr-a-tool-for-deriving-genome-rearrangement-scenarios-from-multiple-unichromosomal-genome-sequences Fri, 28 Sep 2018 09:35:10 -0500 https://bioinformaticsonline.com/bookmarks/view/37796/grsr-a-tool-for-deriving-genome-rearrangement-scenarios-from-multiple-unichromosomal-genome-sequences <![CDATA[GRSR: a tool for deriving genome rearrangement scenarios from multiple unichromosomal genome sequences]]> GRSR is a Tool for Deriving Genome Rearrangement Scenarios for Multiple Uni-chromosomal Genomes. This tool will do the following steps:

  • Step 1. Run mugsy to get multiple sequence alignment results.
  • Step 2 & 3. Extraction of the Coordinates of Core Blocks, Construction of Synteny Blocks and Generating Signed Permutations.
  • Step 4. Generate pairwise genome rearrangement scenarios and find repeats at the breakpoints of each rearrangement events.

https://github.com/DanwangJessica/GRSR

Address of the bookmark: https://github.com/DanwangJessica/GRSR

]]> Jit https://bioinformaticsonline.com/bookmarks/view/40792/haslr-a-tool-for-rapid-genome-assembly-of-long-sequencing-reads Fri, 31 Jan 2020 05:50:15 -0600 https://bioinformaticsonline.com/bookmarks/view/40792/haslr-a-tool-for-rapid-genome-assembly-of-long-sequencing-reads <![CDATA[HASLR: a tool for rapid genome assembly of long sequencing reads]]> HASLR is a tool for rapid genome assembly of long sequencing reads. HASLR is a hybrid tool which means it requires long reads generated by Third Generation Sequencing technologies (such as PacBio or Oxford Nanopore) together with Next Generation Sequencing reads (such as Illumina) from the same sample. 

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

]]> LEGE https://bioinformaticsonline.com/blog/view/43634/illumina-based-assembly-pipeline-steps Fri, 10 Dec 2021 06:22:54 -0600 https://bioinformaticsonline.com/blog/view/43634/illumina-based-assembly-pipeline-steps <![CDATA[Illumina based assembly pipeline steps !]]> Illumina
  1. Merge re-sequenced FastQ files (cat)
  2. Read QC (FastQC)
  3. Adapter trimming (fastp)
  4. Removal of host reads (Kraken 2; optional)
  5. Variant calling
    1. Read alignment (Bowtie 2)
    2. Sort and index alignments (SAMtools)
    3. Primer sequence removal (iVar; amplicon data only)
    4. Duplicate read marking (picard; optional)
    5. Alignment-level QC (picard, SAMtools)
    6. Genome-wide and amplicon coverage QC plots (mosdepth)
    7. Choice of multiple variant calling and consensus sequence generation routes (iVar variants and consensus; default for amplicon data || BCFTools, BEDTools; default for metagenomics data)
      • Variant annotation (SnpEff, SnpSift)
      • Consensus assessment report (QUAST)
      • Lineage analysis (Pangolin)
      • Clade assignment, mutation calling and sequence quality checks (Nextclade)
      • Individual variant screenshots with annotation tracks (ASCIIGenome)
    8. Intersect variants across callers (BCFTools)
  6. De novo assembly
    1. Primer trimming (Cutadapt; amplicon data only)
    2. Choice of multiple assembly tools (SPAdes || Unicycler || minia)
  7. Present QC and visualisation for raw read, alignment, assembly and variant calling results (MultiQC)
]]> Surabhi Chaudhary https://bioinformaticsonline.com/bookmarks/view/43711/vcf-compare Wed, 19 Jan 2022 10:30:14 -0600 https://bioinformaticsonline.com/bookmarks/view/43711/vcf-compare <![CDATA[VCF Compare !]]> compare two BWA mapping methods with the online hg18-mapped data

We first operate a rapid inspection of the different BAM files using samtools flagstat. Illumina provided chr21 read mapping obtained with their GA IIx deep sequencing platform <ftp://webdata:webdata@ussd-ftp.illumina.com/Data/SequencingRuns/NA18507_GAIIx_100_chr21.bam>, aligned to the b36/hg18 reference genome)

Address of the bookmark: https://wiki.bits.vib.be/index.php/NGS_Exercise.6#compare_aln_.26_mem_results_with_vcf-compare

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/30144/bima-v3-an-aligner-customized-for-mate-pair-library-sequencing Wed, 14 Dec 2016 15:20:00 -0600 https://bioinformaticsonline.com/bookmarks/view/30144/bima-v3-an-aligner-customized-for-mate-pair-library-sequencing <![CDATA[BIMA V3: an aligner customized for mate pair library sequencing]]> Summary: Mate pair library sequencing is an effective and economical method for detecting genomic structural variants and chromosomal abnormalities. Unfortunately, the mapping and alignment of mate pair read pairs to a reference genome is a challenging and
time consuming process for most NGS alignment programs. Large insert sizes, introduction of library preparation protocol artifacts (biotin junction reads, paired-end read contamination, chimeras, etc.), and presence of structural variant breakpoints within reads increases mapping and alignment complexity. We describe an algorithm that is up to 20 times faster and 25% more accurate than popular NGS alignment programs when processing mate pair sequencing.
Availability: http://bioinformaticstools.mayo.edu/research/bima/
Contact: vasmatzis.george@mayo.edu

Address of the bookmark: http://bioinformatics.oxfordjournals.org/content/early/2014/02/12/bioinformatics.btu078.full.pdf

]]> Abhimanyu Singh https://bioinformaticsonline.com/bookmarks/view/31156/splitbam-splits-a-bam-by-chromosomes Tue, 28 Feb 2017 09:01:28 -0600 https://bioinformaticsonline.com/bookmarks/view/31156/splitbam-splits-a-bam-by-chromosomes <![CDATA[splitbam: splits a BAM by chromosomes]]> splitbam splits a BAM by chromosomes.

Using the reference sequence dictionary (*.dict), it also creates some empty BAM files if no sam record was found for a chromosome. A pair of 'mock' SAM-Records can also be added to those empty BAMs to avoid some tools (like samtools) to crash.

Usage

java -jar splitbam.jar -p OUT/__CHROM__/__CHROM__.bam -R ref.fasta (bam|sam|stdin)

Options

  • -h help; This screen.
  • -R (indexed reference file) REQUIRED.
  • -u (unmapped chromosome name): default:Unmapped
  • -e | --empty : generate EMPTY bams for chromosome having no read mapped
  • -m | --mock : if option '-e', add a mock pair of sam records to the empty bam
  • -p (output file/bam pattern) REQUIRED. MUST contain __CHROM__ and end with .bam
  • -s assume input is sorted.
  • -x | --index create index.
  • -t | --tmp (dir) tmp file directory
  • -G (file) chrom-group file (see below)

Address of the bookmark: https://code.google.com/archive/p/jvarkit/wikis/SplitBam.wiki

]]> Jit https://bioinformaticsonline.com/bookmarks/view/31568/pacbio-long-reads-compatible-software-and-tools Wed, 15 Mar 2017 14:19:01 -0500 https://bioinformaticsonline.com/bookmarks/view/31568/pacbio-long-reads-compatible-software-and-tools <![CDATA[Pacbio Long Reads Compatible Software and Tools]]> The following software packages are known to be compatible with PacBio® data, in addition to PacBio's own SMRT® Analysis suite. All packages are believed to be open source or freely available for non-commercial use. See the individual project sites for up-to-date license information. A separate page lists commercial software.

Know of any other open source software for PacBio data? Email us.

Software categories:

Address of the bookmark: https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software

]]> Archana Malhotra https://bioinformaticsonline.com/bookmarks/view/34216/meraculous-de-novo-genome-assembly-with-short-paired-end-reads Tue, 07 Nov 2017 04:36:10 -0600 https://bioinformaticsonline.com/bookmarks/view/34216/meraculous-de-novo-genome-assembly-with-short-paired-end-reads <![CDATA[Meraculous: De Novo Genome Assembly with Short Paired-End Reads]]> We describe a new algorithm, meraculous, for whole genome assembly of deep paired-end short reads, and apply it to the assembly of a dataset of paired 75-bp Illumina reads derived from the 15.4 megabase genome of the haploid yeast Pichia stipitis. More than 95% of the genome is recovered, with no errors; half the assembled sequence is in contigs longer than 101 kilobases and in scaffolds longer than 269 kilobases. Incorporating fosmid ends recovers entire chromosomes. Meraculous relies on an efficient and conservative traversal of the subgraph of the k-mer (deBruijn) graph of oligonucleotides with unique high quality extensions in the dataset, avoiding an explicit error correction step as used in other short-read assemblers. A novel memory-efficient hashing scheme is introduced. The resulting contigs are ordered and oriented using paired reads separated by ∼280 bp or ∼3.2 kbp, and many gaps between contigs can be closed using paired-end placements. Practical issues with the dataset are described, and prospects for assembling larger genomes are discussed.

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3158087/

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