The world is not linear.
Most of the time you need multiple variables.
Sometimes you would need a square, a cube, or even a log.
Even with lots of trials, it might still be difficult to fit in.
And, if you try to hard, you might end up being too over-fitting.
After all, it is quite a curvaceous world.
Accidentally stumbling upon this paper about the Mexican genome study.
The Mexican people have already ventured into their genome since 2009! Analysis of genomic diversity in Mexican Mestizo populations to develop genomic medicine in Mexico, published in PNAS 2009.
Although the sample size was not very big and the genotypes were done on a platform with only 100000 SNPs, they started this nine years already.
Anonymous blood samples from 300 non-related and self-defined Mestizos and 30 Amerindian Zapotecos were collected in 7 states in Mexico: Guanajuato, Guerrero, Sonora, Veracruz, Yucatan, Zacatecas, and Oaxaca (ZAP). Genotyping was performed according to the Affymetrix 100K SNP array protocol…
May be there are several other publications coming out after this one?
Setting: You want to allow user to upload data to S3 bucket using amazon cli, but do not want this specific user to see what other buckets are there in you aws account.
Solution: This can be done by setting up a policy below.
If you also want to user to list all other buckets as well. Add the following additional statement to the statement section
Note: Replace “bucket-name” with the name of your bucket. Also, note the Sid should be your Sid. I use the “policy generator” to help generate the policy by modifying the setting from the reference below.
Listing the content of bucket-name
aws s3 ls s3://bucket-name --region ap-northeast-2 --profile s3-bucket-username
Uploading the directory
myfile_folder to the bucket
aws s3 cp myfile_folder s3://bucket-name --region ap-northeast-2 --profile s3-bucket-username
You can also try
aws s3 sync myfile_folder s3://bucket-name --region ap-northeast-2 --profile s3-bucket-username
Although I don’t really support doing a brute-force approach doing manual variants review, if you only have some of your top signal that you would like to confirm for further wet-lab experiment validation, IGV might still proves helpful.
This review by Robinson, et al from a group at UCSD shed some lights and detail into how you can do the manual review in IGV: http://cancerres.aacrjournals.org/content/77/21/e31
I also found the IGV manual describing all the options in the preference menu to be quite useful: https://software.broadinstitute.org/software/igv/Preferences
Through careful characterization of specimens, a new study has come up with some conclusion on how we can improve the quality of cancer specimens for research.
Read the summary on NCI Blog post https://www.cancer.gov/news-events/cancer-currents-blog/2018/improving-cancer-research-biopsies?cid=eb_govdel
Full article is published in Journal of Oncology Practice: https://www.ncbi.nlm.nih.gov/pubmed/?term=30285529
Checkout the new software release TRAPD, which stands for (Test Rare vAriants with Public Data) https://github.com/mhguo1/TRAPD
Read the detail on the article published in AJHG this month at https://www.cell.com/ajhg/fulltext/S0002-9297(18)30284-2