Pipeline release! nf-core/phaseimpute v1.1.0 - 1.1.0 - Purple Beagle!
A bioinformatics pipeline to phase and impute genetic data
Please see the changelog: https://github.com/nf-core/phaseimpute/releases/tag/1.1.0
#genomics #genotype #imputation #lowpasssequencing #phasing #nfcore #openscience #nextflow #bioinformatics
Final reminder: the Statistics Globe online course, "Missing Data Imputation in R," starts today!
It would be great to see you in the course. If you’re interested, you can still register here: https://statisticsglobe.com/online-course-missing-data-imputation-r
The Statistics Globe online course, "Missing Data Imputation in R," starts tomorrow: statisticsglobe.com/online-cours...
Two free modules:
- Module 1: statisticsglobe.com/online-cours...
- Module 4: statisticsglobe.com/online-cours...
Just a quick reminder that the early bird promotion for my upcoming online course Missing Data Imputation in R ends tomorrow, November 19.
More info and registration: https://statisticsglobe.com/online-course-missing-data-imputation-r
#missingdata #imputation #bias #datascience #rstats #statistics
Get one of my other courses for free if you register for my online course on Missing Data Imputation in R by November 19: https://statisticsglobe.com/online-course-missing-data-imputation-r
LIfBi + @destatis = Intensiver Austausch unter Statistikerinnen und Statistikern 📊 💻
Bei einem Workshop zusammen mit der Otto-Friedrich-Universität Bamberg ging es darum, wie mit fehlenden oder unplausiblen Werten in der amtlichen Statistik und in längsschnittlichen Erhebungen umgegangen werden kann.
Danke für den Besuch in Bamberg!
#Imputation #Coding #Statistik #Erhebungen #Kooperation
Final reminder: the Statistics Globe online workshop, "Missing Data Imputation in R," starts in just 24 hours!
It would be great if you also took part in the workshop. So if you are interested, please register now: https://statisticsglobe.com/online-workshop-missing-data-imputation-r
Looking forward to seeing you there!
Joachim
Only 3 days left until the start of the Statistics Globe online workshop, Missing Data Imputation in R.
Kicking off on February 20, this workshop includes eight weekly live sessions, beginning with the basics of handling missing data and advancing to sophisticated imputation techniques in R.
The workshop is limited to 15 participants, so enroll now to secure your spot.
Learn more and sign up here: https://statisticsglobe.com/online-workshop-missing-data-imputation-r
New year, new learning format! I'm thrilled to announce the very first interactive online workshop ever conducted at Statistics Globe!
The Topic: Missing Data Imputation in R
Click here for more info about the workshop: https://statisticsglobe.com/online-workshop-missing-data-imputation-r
Pipeline release! nf-core/phaseimpute v1.0.0 - 1.0.0 - Black Labrador!
Please see the changelog: https://github.com/nf-core/phaseimpute/releases/tag/1.0.0
#genomics #genotype #imputation #lowpasssequencing #phasing #nfcore #openscience #nextflow #bioinformatics
And it’s finally here 🥳 {resurface} my #rstats package for imputing missing genotype allele frequencies, such as those from pooled samples or populations. Stems from some scripts I wrote nearly 10 years ago, which I can now finally say is open. I hope to progressively add more imputation options.
#imputation #genomics #genotyping #bioinformatics
https://github.com/lpembleton/resurface
1/🧵I’ve been developing some genotype allele frequency (AF) #imputation #rstat scripts. While my algorithm returns a low raw bias (RB) of 0.05 to 0.1, simply imputing with the meanAF gives slightly worse but largely similar RB values. I’m wanting to quantifying accuracy better because despite the similar RB values, I find meanAF imputation inferior.
#genomics
'Nonparametric Copula Models for Multivariate, Mixed, and Missing Data', by Joseph Feldman, Daniel R. Kowal.
http://jmlr.org/papers/v25/23-0495.html
#copula #imputation #missingness
'Semi-supervised Inference for Block-wise Missing Data without Imputation', by Shanshan Song, Yuanyuan Lin, Yong Zhou.
http://jmlr.org/papers/v25/21-1504.html
#imputation #supervised #neuroimaging
😏 #imputation #statistics #math
... The student contacted Heshmati and eventually obtained spreadsheets of the data he had used in the paper. Heshmati acknowledged that, although he and his coauthor had not mentioned this fact in the paper, the data had gaps. He revealed in an email that these gaps had been filled by using Excel’s autofill function”....
"Heshmati told the student he had used Excel’s autofill function to mend the data. ... where there were no observations to use for the autofill operation, the professor had taken the values from an adjacent country in the spreadsheet."
#economics #imputation #heshmati #retraction #retractionwatch #Excel #AutoFill #datainvention #fudge #fake
"Journal of Cleaner Production":
https://www.sciencedirect.com/science/article/pii/S0959652623022503
"#Green #innovations and #patents in #OECD countries"
What model #statistics should one report after using multiple #imputation and #multilevel regressions, and how are they obtained? I'm using the #mice package in #rstats, and #lme4 on each imputed dataset. When pooling results, summary() yields what I need for each model term, but nothing for the whole model. If I didn't impute but deleted listwise, I would normally report AIC, BIC, Loglik. These are all in the mipo object, for each result for each imputed dataset, but they're not pooled. I'm sure I'm missing something here. Does anyone know an example article where such results are presented neatly?
'Surrogate Assisted Semi-supervised Inference for High Dimensional Risk Prediction', by Jue Hou, Zijian Guo, Tianxi Cai.
http://jmlr.org/papers/v24/21-1075.html
#imputation #predictors #supervised
RIFLE: Imputation and Robust Inference from Low Order Marginals
