Welcome to phylobabble.org, a discussion forum for phylogenetic theory and applications. The primary goal of this forum is to discuss best practice and new developments in phylogenetics. Although we do have a Troubleshooting category for getting feedback on analyses, this is not a help site for running phylogenetics programs.

A great place to chat about phylogenetics for researchers and the broader community of students and science-interested citizens. 

Address of the bookmark: http://phylobabble.org/

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)
      • Blast to reference genome (blastn)
      • Contiguate assembly (ABACAS)
      • Assembly report (PlasmidID)
      • Assembly assessment report (QUAST)
7. Present QC and visualisation for raw read, alignment, assembly and variant calling results (MultiQC)

Like other indel callers, Scalpel works by performing de novo assembly of regions of interest, so that misalignment to the reference genome cannot obscure the presence of an insertion or deletion. Scalpel's innovation is to repeatedly check its assembly before comparing to the reference genome, to account for simple sequence repeats that are a regular source of error in indel calling. When Scalpel assembles an exon, it collects reads that map to that exon (including partial matches), splits them into k-mers, and creates a de Bruijn graph to span the exon; however, if it detects repeats in the map, it iteratively increases the size of the k-mers by one base until the repeats are eliminated. This ensures that the final assembly of the exon is highly accurate while minimizing compute time.

The Cold Spring Harbor team's validation of Scalpel, published over the weekend in Nature Methods, compares Scalpel's performance on a live whole exome against HaplotypeCaller and SOAPindel. The donor is an individual with serious neurological disorders, which may be linked to a high incidence of indels. One thousand indels from this individual's exome, called by one or more of the informatics pipelines, were selected for focused resequencing. This resequencing revealed a 77% true positive rate for Scalpel calls, dramatically better than the rates for either of the competing tools; Scalpel performed especially well with indels longer than five base pairs, a traditional weak point for indel callers.

Finally, the authors demonstrate Scalpel's use on a large set of genetic data from nearly 600 families who donated samples to the Simons Simplex Collection, a project of the Simons Foundation Autism Research Initiative. Scalpel found a very high enrichment for indels in children affected by autism, compared with their unaffected siblings, a pattern that persisted even after excluding common variants.

Algorithms scripts @ https://github.com/jschendel/bioinformatics-algorithms-coursera

Address of the bookmark: https://github.com/jorvis/biocode

USAGE:

• -query: sequence A in fasta format
• -db: sequence B in fasta format
• -out: output matrix
• -kmer Integer: k>1 (default 32) Use 32 for chromosomes and genomes and 16 for small bacteria
• -diffuse Integer: z>0 (default 4) Use 4 for everything - if using large plant genomes you can try using 1
• -dimension Size of the output matrix and plot. Integer: d>0 (default 1000) Use 1000 for everything that is not full genome size, where 2000 is recommended

Address of the bookmark: https://github.com/estebanpw/chromeister

WALK IN INTERVIEW

A walk-in Interview for the following position tenable at the Bioinformatics Infrastructure Facility (BIF), Department of Biotechnology, Alagappa University will be held at the Department of Biotechnology, Alagappa University, Karaikudi 630 003 on 15.05.2014 (Thursday) at 01:00 PM. This national facility is funded by the Department of Biotechnology, Ministry of Science and Technology, Government of India, New Delhi. The main objectives of the Centre involve teaching and research activities in bioinformatics/biotechnology.

RA (One Post):

Salary : Rs. 11000 p.m. plus admissible HRA

Qualification: M.Sc., in Bioinformatics/Biotechnology/Biophysics/Biochemistry/ Life Sciences

Interested candidates are encouraged to send their Curriculum Vitae by email to “sk_pandian@rediffmail.com” in advance. On the day of interview, the candidates must produce original certificates in proof of their educational qualification and experience and a recommendation letter from the Head of the Department/Institution where last studied/worked. Candidates who have already passed the required Degree alone are eligible to appear for interview. No TA&DA will be given for attending the interview.

Advertisement: http://www.alagappabiotech.org/Walk%20in%20interview.pdf

Address of the bookmark: https://www.science.org/doi/10.1126/science.abj6987

Pay scale: Pay Band of Rs. 37400-67000 with AGP of Rs. 9000.

i. Educational Qualification: Good academic record with a Ph.D. Degree in the concerned/allied/relevant disciplines.

ii. A Master's Degree with at least 55% marks (or an equivalent grade in a point scale wherever grading system is followed).

iii. A minimum of eight years of experience of teaching and/or research in an academic/research position equivalent to that of Assistant Professor in a University, College or Accredited Research Institution/industry excluding the period of Ph.D. research with evidence of published work and a minimum of 5 publications as books and/or research/policy papers.

iv. Contribution to educational innovation, design of new curricula and courses, and technology - mediated teaching learning process with evidence of having guided doctoral candidates and research students.

v. A minimum score as stipulated in the Academic Performance Indicator (API) based Performance Based Appraisal System (PBAS), set out in UGC Regulation.

Download application form from website: http://www.allduniv.ac.in/

Send your application to the Registrar, University of Allahabad, Allahabad-211002 (U.P.) on or before 30th April 2014

For more details: http://www.allduniv.ac.in/images/adv/backlog/advt-details.pdf OR http://www.allduniv.ac.in/images/news/extension-notice.pdf

Last Apply Date: 30 May 2014

• Clustering module Predicts, clusters and annotates the genes of every input genome
• Lifestyle prediction Employs a machine learning model to forecast bacterial lifestyle or other specified metadata
• Analitical module (Shiny app) Results from the previous modules are embedded in a user-friendly interface for comprehensive and interactive comparative genomics.

You can find the complete wiki here [https://github.com/Carrion-lab/bacLIFE/wiki/bacLIFE-wiki]

Address of the bookmark: https://github.com/Carrion-lab/bacLIFE