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4 results for “generalized linear mixed models”
Minimal dataset for "Insights to HIV-1 coreceptor usage by estimating HLA adaptation with Bayesian generalized linear mixed models"
<p>This repository contains a minimal data set to reproduce all results that don't compromise the privacy concerns for the manuscript "Insights to HIV-1 coreceptor usage by estimating HLA adaptation with Bayesian generalized linear mixed models".<br> <br> The repository contains the following data:</p> <ul> <li>adaptscore_acute.csv <ul> <li>A csv file that contains the estimated adaptation scores for the acute data set with HLA I model.</li> </ul> </li> <li>adaptscore_leftout.csv <ul> <li>A csv file that contains the estimated adaptation scores for the leftout data set with the joint HLA I and HLA II model</li> </ul> </li> <li>adaptscore_training.csv <ul> <li>A csv file that contains the estimated adaptation scores for the traininig data set with the joint HLA I and HLA II model</li> </ul> </li> <li>adaptscore_training_hla1_without_clin.csv <ul> <li>A csv file that contains the estimated adaptation scores for the training data set with the HLA I model (via cross-validation)</li> </ul> </li> <li>adaptscore_training_seed2.csv <ul> <li>A csv file that contains the estimated adaptation scores for the training data set with the joint HLA I and HLA II model via cross-validation with another seed</li> </ul> </li> </ul>
Consensus nucleotide sequences for env and gag for paper: Insights to HIV-1 coreceptor usage by estimating HLA adaptation with Bayesian generalized linear mixed models
<p>This is the consensus sequence repository to the manuscript "Insights to HIV-1 coreceptor usage by estimating HLA adaptation with Bayesian generalized linear mixed models".<br> It contains the 10% consensus nucleotide sequences of the env and gag (only p24) protein of HIV-1 used for the training and leftout data set. The NGS sequences are available under BioProject ID PRJNA810303 and the corresponding BioSample Accession IDs are SAMN26241863:26242168 and SAMN28728524:SAMN28728529</p> <ul> <li>env_leftout.fasta <ul> <li>A fasta file that contains the consensus nucleotide sequences for the env protein for the leftout data set</li> </ul> </li> <li>env_nt_274.fasta <ul> <li>A fasta file that contains the consensus nucleotide sequences for the env protein for the training data set</li> </ul> </li> <li>gag_leftout.fasta <ul> <li>A fasta file that contains the consensus nucleotide sequences for the gag protein for the leftout data set</li> </ul> </li> <li>gag_nt_274.fasta <ul> <li>A fasta file that contains the consensus nucleotide sequences for the gag protein for the training data set</li> </ul> </li> </ul>
Data from: miRglmm: a generalized linear mixed model of isomiR-level counts improves estimation of miRNA-level differential expression and uncovers variable differential expression between isomiRs
<p>These datasets can be used to reproduce all analyses from the publication "miRglmm: a generalized linear mixed model of isomiR-level counts improves estimation of miRNA-level differential expression and uncovers variable differential expression between isomiRs" in conjunction with codes found at https://github.com/mccall-group/miRglmm_paper. </p> <p>"Monocyte_data_subset.rda", "monocyte_exact_subset_filtered2.rda" and "sims_N100_m2_s1_rtruncnorm.rda" can be used to reproduce the simulation analysis. </p> <p>"panel_B_SE.rda" and "ERCC_filtered.rda" can be used to reproduce the ERCC synthetic data analysis with known ground truth.</p> <p>"study89_data_subset.rda" and "study89_data_subset_filtered2.rda" can be used to reproduce the immune cell-type analysis. </p> <p>"bladder_testes_data_subset.rda" and "bladder_testes_data_subset_filtered2.rda" can be used to reproduce the bladder vs testes tissue analysis.</p>
Data from: Generalized linear mixed models for mapping multiple quantitative trait loci
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