Jiang Tao

Bioinformatics, Genomics and Computational Biology.
Interested in human genomic structural variations calling.
Professor(PhD) at Harbin Institute of Technology.

[Jiang Tao @Cannot__Change]

Excited to share our latest work in @NatureMethods: SVPG — pangenome-based SV detection + rapid graph augmentation from long reads. Better rare/somatic SV calls; ~10× faster graph augmentation.
https://t.co/w05769ElIJ
#Pangenome #LongRead

[antisense. @razoralign]

cuteFC: regenotyping structural variants through an accurate and efficient force-calling method https://t.co/CvrDLYlYjR

[Albert Vilella @AlbertVilella]

Updated #NGS Yield low/high and Price per Gbp max/min of all the companies with defined products so far. Coloured in green/red shades.

[Adam Ameur @_adameur]

Happy to share this new work, where SVs from @nanopore PromethION and @PacBio RSII were compared for two individuals from the #SweGen population. Great job by @_nazeefatima who pushed this all the way from MSc project to a final publication! https://t.co/NEMeYqfgQQ

[Oxford Nanopore @nanopore]

New blog! Tao Jiang (@Cannot__Change) describes his work on the development of the structural variant (SV) caller cuteSV. Find out how the cuteSV bioinformatics pipeline works, how it performs relative to other SV callers and Tao’s future development plans
https://t.co/iD7Jz2qwOP

[Oxford Nanopore @nanopore]

Now available: cuteSV, developed with nanopore long-read sequencing has 'outstanding ability to detect SVs with low coverage sequencing data, and it also has high scalability for handling large-scale datasets'

Read more: https://t.co/QIwBtvSBaA

[Genome Biology @GenomeBiology]

cuteSV, from Jiang, Liu, Wang and co, a tool for identifying structural variants using long reads. Different SV types have different signatures, which the method identifies. cuteSV can work with Nanopore and PacBio data. https://t.co/uEk5PPTFli

[Genome Biology @GenomeBiology]

Liu, Liu, Zang, Wang and co present deSALT, for aligning long RNA-seq reads. it takes a two-pass approach, using a graph-based index to match blocks between read and genome, and then relocating short matches between read and detected exons. https://t.co/HVtdirlDt0

[Nature Methods @naturemethods]

Ruan and Li @lh3lh3 report wtdbg2, a genome assembler that achieves comparable contiguity and accuracy to existing tools using long-read sequencing data, and is fast especially for large genomes. https://t.co/GHKbrbkI1R

[Jiang Tao @Cannot__Change]

@SigmaFacto Furthermore, the complex region within multi-type SVs (complex SVs) also hinders the high-quality SV calling. In a word, all the factors that can make the signature worse are the root of the performance degradation of SV detection.

[Jiang Tao @Cannot__Change]

Long Read based Human Genomic Structural Variation Detection with cuteSV https://t.co/rYBk5io5Cq

[Jiang Tao @Cannot__Change]

@SigmaFacto Hello, I show an example of the density of SVs in my latest twitter. cuteSV give an integration insertion call rely on its signatures combination. I think the signature abundant region maybe mislead the SV caller to generate inappropriately calls.

[Jiang Tao @Cannot__Change]

An interesting question: how many insertions in this region? Giab gives 5 insertions here including 4 small insertions from Illumina technology and 1 large insertion from PacBio. Crazy problem!😰

[Jiang Tao @Cannot__Change]

@SigmaFacto I think if you want to implementation of SV calling with low coverage, pls increase the read length as far as possible when library construction and sequencing.

[Jiang Tao @Cannot__Change]

@SigmaFacto Meantime, the alternative read alignments generate misplacement of SV signatures, which will increase the difficulties of clustering. Both two main reasons decrease sensitivity and accuracy in SV calling.

[Jiang Tao @Cannot__Change]

@SigmaFacto This is a good question. Analysis and resolving repeat region is the most complicated scientific problem in genomics all the time. The higher the repeatability of these elements is, the lower the accuracy of the read alignments is. So we will miss quite a lot of SV signatures.

[Jiang Tao @Cannot__Change]

@SigmaFacto Now, I am busy improving the genotyping performance of cuteSV. I put it on my to-do list and I will try it if I have time.😀

[Nature Reviews Genetics @NatureRevGenet]

Structural variation in the sequencing era https://t.co/cL80Tzgxpm #Review by Steve S. Ho, Alexander E. Urban & Ryan E. Mills

[Jiang Tao @Cannot__Change]

Identifying and removing haplotypic duplication in primary genome assemblies https://t.co/b7npng67HE