<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/38199?offset=140 https://bioinformaticsonline.com/bookmarks/view/37835/variantbam-filtering-and-profiling-of-next-generational-sequencing-data-using-region-specific-rules Thu, 04 Oct 2018 16:30:44 -0500 https://bioinformaticsonline.com/bookmarks/view/37835/variantbam-filtering-and-profiling-of-next-generational-sequencing-data-using-region-specific-rules <![CDATA[VariantBam: Filtering and profiling of next-generational sequencing data using region-specific rules]]> VariantBam is a tool to extract/count specific sets of sequencing reads from next-generational sequencing files. To save money, disk space and I/O, one may not want to store an entire BAM on disk. In many cases, it would be more efficient to store only those read-pairs or reads who intersect some region around the variant locations. Alternatively, if your scientific question is focused on only one aspect of the data (e.g. breakpoints), many reads can be removed without losing the information relevant to the problem.

 

Address of the bookmark: https://github.com/broadinstitute/VariantBam

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/40699/kevler-reference-free-variant-discovery-in-large-eukaryotic-genomes Tue, 28 Jan 2020 03:21:53 -0600 https://bioinformaticsonline.com/bookmarks/view/40699/kevler-reference-free-variant-discovery-in-large-eukaryotic-genomes <![CDATA[Kevler: Reference-free variant discovery in large eukaryotic genomes]]> Welcome to kevlar, software for predicting de novo genetic variants without mapping reads to a reference genome! kevlar's k-mer abundance based method calls single nucleotide variants (SNVs), multinucleotide variants (MNVs), insertion/deletion variants (indels), and structural variants (SVs) simultaneously with a single simple model. 

More at https://kevlar.readthedocs.io/en/latest/

https://www.cell.com/iscience/pdf/S2589-0042(19)30259-7.pdf

Address of the bookmark: https://github.com/kevlar-dev/kevlar

]]> Jit https://bioinformaticsonline.com/bookmarks/view/41148/pbmm2a-minimap2-frontend-for-pacbio-native-data-formats Tue, 18 Feb 2020 03:36:22 -0600 https://bioinformaticsonline.com/bookmarks/view/41148/pbmm2a-minimap2-frontend-for-pacbio-native-data-formats <![CDATA[pbmm2:A minimap2 frontend for PacBio native data formats]]> pbmm2 is a SMRT C++ wrapper for minimap2's C API. Its purpose is to support native PacBio in- and output, provide sets of recommended parameters, generate sorted output on-the-fly, and postprocess alignments. Sorted output can be used directly for polishing using GenomicConsensus, if BAM has been used as input to pbmm2. Benchmarks show that pbmm2 outperforms BLASR in sequence identity, number of mapped bases, and especially runtime. pbmm2 is the official replacement for BLASR.

Address of the bookmark: https://github.com/PacificBiosciences/pbmm2

]]> BioStar https://bioinformaticsonline.com/blog/view/38277/understating-pacbio-reads-name Fri, 23 Nov 2018 07:36:46 -0600 https://bioinformaticsonline.com/blog/view/38277/understating-pacbio-reads-name <![CDATA[Understating pacbio reads name !]]> m140415_143853_42175_c100635972550000001823121909121417_s1_p0/553/3100_11230 0.99 24 └1┘└─────2─────┘└──3─┘└────────────────4────────────────┘└5┘└6┘└7┘└────8────┘└─9─┘└10┘
  1. "m" = movie
  2. Time of Run Start (yymmdd_hhmmss)
  3. Instrument Serial Number
  4. SMRT Cell Barcode
  5. Set Number (a.k.a. "Look Number". Deprecated field, used in earlier version of RS)
  6. Part Number (usually "p0", "X0" when using expired reagents)
  7. ZMW hole number
  8. Subread Region (start_stop using polymerase read coordinates)
  9. readScore
  10. barcodeScore
]]> BioJoker https://bioinformaticsonline.com/bookmarks/view/34445/inc-seq-accurate-single-molecule-reads-using-nanopore-sequencing Mon, 27 Nov 2017 10:38:56 -0600 https://bioinformaticsonline.com/bookmarks/view/34445/inc-seq-accurate-single-molecule-reads-using-nanopore-sequencing <![CDATA[INC-Seq: accurate single molecule reads using nanopore sequencing]]> INC-Seq reads enabled accurate species-level classification, identification of species at 0.1 % abundance and robust quantification of relative abundances, providing a cheap and effective approach for pathogen detection and microbiome profiling on the MinION system.

Address of the bookmark: https://github.com/CSB5/INC-Seq

]]> 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/pages/view/36630/frequent-paired-end-reads-pe-2x100-mapping-command-lines Tue, 15 May 2018 08:59:29 -0500 https://bioinformaticsonline.com/pages/view/36630/frequent-paired-end-reads-pe-2x100-mapping-command-lines <![CDATA[Frequent Paired-end reads (PE 2x100) mapping command lines]]> bowtie2 -x hs37m -X 650 -q -1 r1.fq -2 r2.fq -S r12.bowtie2.sam

bwa aln hs37m.fa r1.fq > r1.sai && bwa aln hs37m.fa r2.fq > r2.sai \
&& bwa sampe hs37m r1.sai r2.sai r1.fq r2.fq > r12.bwa.sam

bwa bwasw ../index/bwa/hs37m.fa r12.fq > r12.bwasw.sam

gsnap -A sam -d hs37m r1.fq r2.fq > r12.gsnap.sam

novoalign -r Random -o SAM -f r1.fq r2.fq -i 500 50 -d hs37m-k14s3.novo > r12.novo.sam

smalt map -f samsoft -i 650 -o r12.smalt-k20s13.sam hs37m-k20s13 r1.fq r2.fq

stampy.py -g hs37m -h hs37m -o r12.stampy.sam -M r1.fq,r2.fq

soap -D hs37m.fa.index -a r1.fq -b r2.fq -l 32 -g 3 -u dummy -2 dummy -o r12.soap

]]> 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/37650/p-rna-scaffolder-a-fast-and-accurate-genome-scaffolder-using-paired-end-rna-sequencing-reads Fri, 07 Sep 2018 05:19:06 -0500 https://bioinformaticsonline.com/bookmarks/view/37650/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]]> P_RNA_scaffolder is a novel scaffolding tool using Pair-end RNA-seq to scaffold genome fragments. The method is suitable for most genomes. The program could utilize Illumina Paired-end RNA-sequencing reads from target speciesies. Our method provides another practical alternative to existing mate-pair_based approaches or other Protein-based approaches (for instance, PEP_scaffolder ) for scaffolding genome sequences. The most important feature of this method is to improve the completeness of gene regions and long-coding gene regions (for instance, circRNA).

Address of the bookmark: http://www.fishbrowser.org/software/P_RNA_scaffolder/#

]]> BioStar https://bioinformaticsonline.com/bookmarks/view/39671/flye-fast-and-accurate-de-novo-assembler-for-single-molecule-sequencing-reads Sat, 06 Jul 2019 03:48:22 -0500 https://bioinformaticsonline.com/bookmarks/view/39671/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 single molecule sequencing reads, such as those produced by PacBio and Oxford Nanopore Technologies. It is designed for a wide range of datasets, from small bacterial projects to large mammalian-scale assemblies. The package represents a complete pipeline: it takes raw PB / ONT reads as input and outputs polished contigs. Flye also includes a special mode for metagenome assembly.

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

]]> Rahul Nayak