<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/38199?offset=330 https://bioinformaticsonline.com/opportunity/view/40770/scientist-bioinformatics-positions Thu, 30 Jan 2020 06:53:40 -0600 <![CDATA[Scientist Bioinformatics Positions]]> Bioinformatics-Multi_Omics_Integration

https://www.researchgate.net/job/939073_Senior_Scientist_Bioinformatics-Multi_Omics_Integration


Senior_Scientist_Bioinformatics-Transcriptomics_Analysis

https://www.researchgate.net/job/939075_Senior_Scientist_Bioinformatics-Transcriptomics_Analysis-Belgium_France_Switzerland_The_Netherlands

Senior Scientist Bioinformatics - Network Analytics

https://www.researchgate.net/job/939070_Senior_Scientist_Bioinformatics-Network_Analytics_Belgium_France_Switzerland_the_Netherlands

Team Leader Bioinformatics Data Sciences - Mechelen, Belgium

https://www.researchgate.net/job/938787_Team_Leader_Bioinformatics_Data_Sciences-Mechelen_Belgium

]]> https://bioinformaticsonline.com/bookmarks/view/41730/parliament2-runs-a-combination-of-tools-to-generate-structural-variant-calls-on-whole-genome-sequencing-data Thu, 28 May 2020 21:57:03 -0500 https://bioinformaticsonline.com/bookmarks/view/41730/parliament2-runs-a-combination-of-tools-to-generate-structural-variant-calls-on-whole-genome-sequencing-data <![CDATA[Parliament2: Runs a combination of tools to generate structural variant calls on whole-genome sequencing data]]> Parliament2 identifies structural variants in a given sample relative to a reference genome. These structural variants cover large deletion events that are called as Deletions of a region, Insertions of a sequence into a region, Duplications of a region, Inversions of a region, or Translocations between two regions in the genome.

Parliament2 runs a combination of tools to generate structural variant calls on whole-genome sequencing data. It can run the following callers: Breakdancer, Breakseq2, CNVnator, Delly2, Manta, and Lumpy. Because of synergies in how the programs use computational resources, these are all run in parallel. Parliament2 will produce the outputs of each of the tools for subsequent investigation.

Address of the bookmark: https://github.com/dnanexus/parliament2

]]> Jit https://bioinformaticsonline.com/opportunity/view/43227/project-associate-i-project-associate-ii-senior-project-associate-igib Thu, 05 Aug 2021 16:11:32 -0500 <![CDATA[Project Associate-I | Project Associate-II | Senior Project Associate @ IGIB]]> Experience in Next Generation Sequencing (NGS) application and interest in Genomics/ Clinical / Translational Applications. OR Good computational programming skills and deep interest in working on interface of Genomics and Clinical application.

Project Scientist-I
Experimental / Computation analysis experience in highthroughput genomics/ clinical application.

Project Manager
Experience in handling large biological projects involving high-throughput genomics/ clinical application.

Scientific Administrative Assistant
Lab Work.

More at https://vinodscaria.genomes.in/positionsopen

]]> 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

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