Variant calling and/or genotyping

• DiscoSNP++ and discoSnpRAD: Reference-free small variant discovery (SNPs and indels)
• MindTheGap: Detection and assembly of large insertion variants
• TakeABreak: reference-free inversion discovery tool
• SVJedi: Structural Variant genotyper with long read data
• SVJedi-graph: Structural Variant genotyper with long read data using a variation graph

Sequence assembly

• MinYS: reference-guided genome assembly in metagenomics data
• MTG-link: local assembly tool for linked-read data
• Minia: De novo short read assembler
• de-novo pipeline: de-novo assembly pipeline (error correction / contigs / scaffolding) for genomes and meta-genomes
• Mapsembler2: Targeted assembly (not maintained)

Managing k-mers & indexation

• findere: simple strategy for speeding up queries and for reducing false positive calls from any Approximate Membership Query data structure.
  • fimpera extends findere adding the abundance information.
• kmtricks: modular tool suite for counting kmers, and constructing Bloom filters or kmer matrices, for large collections of sequencing data.
• kmindex is a tool for indexing and querying sequencing samples. It is built on top of kmtricks.
• back to sequences: Find sequences (reads, unitigs, genes) related to a set of kmers in large datasets, in a matter of seconds.
• Backpack Quotient Filter: k-mer indexing data structure with abundance
• short read connector: Detect similar reads from potentially large read set
• DSK: Count K-mer in sequences

Pangenome graph manipulation

• Pancat: Pangenome Comparison and Analysis Toolkit
• GFAGraphs: a Python library to handle pangenome graph files in GFA format.

Comparative metagenomics with k-mers

• Simka and SimkaMin: Comparative metagenomics for large-scale datasets
• Comparead & Commet: comparison of metagenomic datasets

Species and bacterial strains identification

• ORI: software using long nanopore reads to identify bacteria present in a sample at the strain level
• StrainFLAIR: STRAIN-level proFiLing using vArIation gRaph

General-purpose sequencing data manipulation

• GASSST: long read mapper
• Leon: short read compressor (now included in GATB-core)
• Bloocoo: short read corrector
• BCALM: Construct compacted de Bruijn graphs (unitigs)

 Protein Structure

• A_Purva: Contact Map Overlap solver
• MD-Jeep: Distance Geometry solver
• CSA: Comparative Structural Alignment

Workflow

• SLICEE: parallel execution of bioinformatics workflows

Comparative Genomics

• CASSIS: detection of rearrangement breakpoints
• PLAST: intensive bank-to-bank sequence comparison
• DRJBreakpointFinder: detection and precise localization of excision sites in proviral segments

• Whole-genome sequencing
• Whole-exome sequencing
• RNA-seq (speical mode available)
• ChIP-seq

Address of the bookmark: http://qualimap.bioinfo.cipf.es/

A swift, versatile phylogenomic and high-throughput sequencing simulator https://jackalope.lucasnell.com

Address of the bookmark: https://github.com/lucasnell/jackalope

More at https://software.broadinstitute.org/gatk/download/bundle

ftp://ftp.ncbi.nlm.nih.gov/snp/organisms/human_9606/VCF/GATK/.

ftp://ftp.broadinstitute.org/bundle/hg38/hg38bundle/

Address of the bookmark: https://console.cloud.google.com/storage/browser/genomics-public-data/resources/broad/hg38/v0?pli=1

Bactopia can be split into two main parts: Bactopia Analysis Pipeline, and Bactopia Tools.

Bactopia Analysis Pipeline is the main per-isolate workflow in Bactopia. Built with Nextflow, input FASTQs (local or available from SRA/ENA) are put through numerous analyses including: quality control, assembly, annotation, minmer sketch queries, sequence typing, and more.

Bactopia Tools are a set a independent workflows fo

Address of the bookmark: https://github.com/bactopia/bactopia

Abstract: Strand NGS includes comprehensive workflows for DNA-Seq, RNA-Seq, Small RNA-Seq, ChIP-Seq, MeDIP-Seq, and Methyl-Seq analysis. Each workflow includes a quality assessment and filter section, followed by a workflow-specific analysis section. The pipeline functionality in Strand NGS allows users to execute a sequence of analysis steps with specific parameters - all without any manual intervention. This simplifies the analysis in large scale sequencing projects where every sample needs to be processed identically.

In this webinar we will discuss the pre-packaged pipelines present in Strand NGS. The packaged pipelines have well-chosen default parameters and are suitable for users analyzing data for the first time in the tool. We will also show how advanced users can customize pipelines and share them with other Strand NGS users. Finally, we will show a brief glimpse of an elaborate pipeline that aligns reads, filters poor-quality matches, computes coverage metrics, identifies variants, checks for sample cross-contamination, and emails quality reports - all from within Strand NGS.

Speaker: Dr. Vamsi Veeramachaneni, Vice President - Bioinformatics, Strand Life Sciences

Details: Session 1: 2:30 PM IST, Session 2 : 10:30 PM IST
Register here: http://www.strand-ngs.com/webinar_registration

1. Reducing time in analysis and increasing accuracy of results by only considering those reads which should assemble together.
2. Reducing/removing reference bias as compared to mapping based approaches.

The software is designed to work in situations where a whole-genome assembly is not the objective, but rather when the researcher wishes to assemble discreet 'targets' contained within next-generation shotgun sequence data. ARC decomplexifies the traditionally difficult problem of assembly by breaking the reads into small, manageable subsets which can then be assembled quickly and efficiently in parallel. Applications include those in which the researcher wishes to de novo assemble specific content and a set of semi-similar reference targets is available to initialize the assembly process.

https://ibest.github.io/ARC/

Address of the bookmark: https://ibest.github.io/ARC/

Bachelor/ BS Bioinformatics at
1. Al-khair University, Bhimber
2. Government College University, Faisalabad
3. University Of Agriculture, Faisalabad
4. Comsats Institute Of Information Technology [isb], Islamabad
5. International Islamic University, Islamabad
6. Quaid-e-azam University, Islamabad
7. Khushal Khan Khattak University, Karak
8. Virtual University Of Pakistan, Lahore
9. Virtual University Of Pakistan, Lahore
10. Hazara University, Mansehra
11. Shaheed Benazir Bhutto Women University, Peshawar
12. Comsats Institute Of Information Technology, Sahiwal
13. Capital University Of Science And Technology, Islamabad
14. Foundation University, Islamabad
15. Baqai Medical University/hospital, Karachi
16. Institute Of Business And Technology(main Campus), Karachi
17. Sir Syed University Of Engineering & Technology, Karachi
18. Forman Christian College, Lahore
19. Qarshi University (lhr), Lahore
20. The Superior University, Lahore
21. University Of Management And Technology, Lahore
22. Federal Institute Of Health Sciences, Lahore
23. Shaheed Benazir Bhutto Women University Peshawar, Sub Campus, Swabi
24. Government Postgraduate College ( Mandian), Abbottabad
25. Federal Institute Of Health Sciences, Multan
26. Fedral Institute Of Health Sciences, Muzaffarabad
27. The Limit Institution Of Health Sciences, Sahiwal

Master/ MS Bioinformatics cources at
1. Government College University, Faisalabad
2. Comsats Institute Of Information Technology [isb], Islamabad
3. International Islamic University, Islamabad
4. National University Of Science & Technology, Islamabad
5. Quaid-e-azam University, Islamabad
6. University Of Sindh, Jamshoro
7. Virtual University Of Pakistan, Lahore
8. Hazara University, Mansehra
9. Shaheed Benazir Bhutto Women University, Peshawar
10. Capital University Of Science And Technology, Islamabad
11. Cecos University Of Information Tech. & Emerging Sciences, Peshawar

The real bioinformatics scope lies if there are research labs which work in this field. One has to take account of that. If so then try to get information of those labs and visit them to get a hang of the work they pursue.

There is a huge buzz of precision medicine in light of genomics all around the world. One should also try to see how genomics infrastructure is built up or standing in Pakistan. If research labs having collaboration with hospitals employ genomics then one must also visit such labs. This will bring new avenues in healthcare advances. Not only it opens up the wealth of knowledge one can make out of genomics study but will also advance the critical thinking of therapies.

So I would encourage to target research labs working in the fields and also get information of hospitals employing genomics, this will give you an overall understanding of the fields demand in your country.

https://github.com/clemgoub/dnaPipeTE/wiki/dnaPipeTE-WIKI-home

Address of the bookmark: https://github.com/clemgoub/dnaPipeTE

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6733440/

Address of the bookmark: https://github.com/kammoji/gapFinisher