Address of the bookmark: http://www.littlest.co.uk/software/bioinf/old_packages/miropeats/

More at http://bmbl.sdstate.edu/DMINDA2/

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086085/

Address of the bookmark: http://bmbl.sdstate.edu/DMINDA2/

Link to the article: https://academic.oup.com/bioinformaticsadvances/article/3/1/vbad174/7455250?searchresult=1

Link to the software:
https://github.com/Sammccarthypotter/ExRec

Address of the bookmark: https://github.com/Sammccarthypotter/ExRec

There are Neanderthal bones. Denisovan remains. Fossils from ancient relatives of our species. Each specimen gives us another piece of the story of how Homo sapiens came to be.

But now imagine that one of the most important characters in that story has left behind no fossil, no skull, no bone, and no genome.

Nothing that a paleontologist could put behind glass.

And yet, somehow, that ancient population is still speaking.

It is speaking through us.

A fascinating new study published in Science (https://www.science.org/doi/10.1126/science.aef8874?) introduces a computational method called TRACE, which allows scientists to search modern human genomes for genetic traces of ancient populations that have never been directly identified.

For years, scientists have known that our ancestors interacted with Neanderthals and Denisovans. Their DNA still survives in modern human populations. But these may not have been the only ancient humans who crossed paths with our ancestors.

Using TRACE, researchers found evidence of an unknown archaic population that contributed DNA to the ancestors of modern humans before humans spread beyond Africa.

Even more surprisingly, they found evidence of a much older lineage—possibly around 1.8 million years old—whose genetic legacy may have reached some modern humans indirectly through Denisovans.

The extraordinary part is that researchers did not need DNA from these mysterious populations to detect them. Instead, they studied the ancestry of modern genomes and looked for genetic patterns that revealed unusually ancient branches of our family history.

It is almost like finding the footprints of someone who disappeared thousands of years ago—without ever finding the person themselves.

These discoveries suggest that human evolution was far more complicated than a simple family tree. Ancient human populations repeatedly separated, migrated, met and exchanged genes. Some eventually disappeared, but pieces of their genetic legacy survived.

And that means our DNA is more than a biological instruction manual.

It is also an archive of human history.

Some of the people recorded in that archive may never have a name or a fossil. But thanks to methods like TRACE, their genetic echoes are finally becoming visible.

The next big discovery about our ancient past may not come from a fossil in the ground.

It may already be inside us.

Reference: Zhang et al., “Recovering signatures of archaic hominin introgression using ancestral recombination graphs,” Science (2026), DOI: 10.1126/science.aef8874. Detail paper @ https://www.science.org/doi/10.1126/science.aef8874?

The TRACE repository (https://github.com/YulinZhang9806/trace) contains the Python package and command-line tools used to infer archaic admixture tracts from ancestral recombination graphs.

Annotation

https://bigd.big.ac.cn/ncov/variation/annotation

Genome wharehouse 

https://bigd.big.ac.cn/gwh/browse/index

Released Genome

https://bigd.big.ac.cn/ncov/release_genome

Download data 

ftp://download.big.ac.cn/Genome/Viruses/Coronaviridae/

Raw data

https://bigd.big.ac.cn/gsa/browse/run/?tag=Coronaviridae

Address of the bookmark: https://bigd.big.ac.cn/ncov/about

Arlequin: http://cmpg.unibe.ch/software/arlequin3/

BEAGLE: http://faculty.washington.edu/browning/beagle/beagle.html

fastPHASE: http://stephenslab.uchicago.edu/software.html

GENEHUNTER: http://linkage.rockefeller.edu/soft/gh/

The Genome Analysis Toolkit:

http://www.broadinstitute.org/gsa/wiki/index.php/The_Genome_Analysis_Toolkit

IMPUTE2: https://mathgen.stats.ox.ac.uk/impute/impute_v2.html

MACH: http://www.sph.umich.edu/csg/abecasis/MACH/

MERLIN: http://www.sph.umich.edu/csg/abecasis/Merlin/

PHASE: http://stephenslab.uchicago.edu/software.html

PL-EM: http://www.people.fas.harvard.edu/~junliu/plem/

“Read-backed phasing” algorithm: http://www.broadinstitute.org/gsa/wiki/index.php/Read-backed_phasing_algorithm

SHAPE-IT: http://www.griv.org/shapeit/

Title: Comparison of Short Read De Novo Alignment Algorithms 

Author: Nikhil Gopal

Address of the bookmark: http://biochem218.stanford.edu/Projects%202011/Gopal%202011.pdf

High Throughput Sequencing Analysis
Comparative Genomics
Identification and Annotation of Non-coding RNAs
Bioinformatic Analysis and System Biology of Viruses
Coevolution of Proteins and RNAs
Algorithmic Bioinformatics
Phylogenetic Analysis

http://www.rna.uni-jena.de/index.php