• biopython
• intervaltree
• numpy
• scipy
• tqdm
• PyYAML

Address of the bookmark: https://github.com/cerebis/sim3C

MGI, a subsidiary of global genomics leader BGI Group, announced pricing and its first early access customer for the new ultra high-throughput sequencer, MGISEQ-T7, saying it has driven down sequencing cost to $5 per gigabyte, with exceptionally high accuracy. Such innovations are helping more people to realize the benefits of genomic information.

In October, MGI launched the MGISEQ-T7, a highly flexible production-scale platform that is the most powerful sequencer to date. It can produce as many as 60 whole human genomes in one day. The instrument sells for $1 million.

The T7 enables simultaneous but independent operation of up to four flow cells, which means different applications such as single-cell RNA sequencing, whole exome sequencing and whole genome sequencing can be run in different flow cells at the same time. This helps to reduce costs, allowing MGI to offer the most competitive sequencing price in the market.

Powered by DNBseq™, MGISEQ delivers quality data with accuracy for SNP and Indel calling rate of 99.9% and 99%, respectively, along with decreased duplication rate down to less than 2 percent, and almost zero Index mis-assignment rate.

SOURCE MGI

https://www.bgi.com/global/company/news/bgis-mgi-tech-launches-two-new-ngs-platforms/

http://en.mgitech.cn/

per-base depth about 2x as fast samtools depth--about 25 minutes of CPU time for a 30X genome.
mean per-window depth given a window size--as would be used for CNV calling.
the mean per-region given a BED file of regions.
a distribution of proportion of bases covered at or above a given threshold for each chromosome and genome-wide.
quantized output that merges adjacent bases as long as they fall in the same coverage bins e.g. (10-20)
threshold output to indicate how many bases in each region are covered at the given thresholds.
A summary of mean depths per chromosome and within specified regions per chromosome.

Address of the bookmark: https://github.com/brentp/mosdepth

http://cancerwebpa.jefferson.edu/iSeqQC/

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-3399-8

Address of the bookmark: https://github.com/gkumar09/iSeqQC

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

Address of the bookmark: http://disco.omicsbio.org/

To error-correct reads:
tadpole.sh in=reads.fq out=corrected.fq mode=correct

To extend reads by 50bp in each direction:
tadpole.sh in=reads.fq out=extended.fq mode=extend el=50 er=50

To error-correct and extend at the same time, using a kmer length of 62:
tadpole.sh in=reads.fq out=extended.fq mode=extend el=50 er=50 k=62 ecc=t

More at http://seqanswers.com/forums/showthread.php?t=61445

Address of the bookmark: https://jgi.doe.gov/data-and-tools/bbtools/bb-tools-user-guide/tadpole-guide/

Address of the bookmark: http://omega.omicsbio.org/

Address of the bookmark: https://sourceforge.net/projects/contiguator/