Questions tagged [linear-regression]
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Statistical approach to link DNA methylation with toxic element exposure and health outcome
I would be thankful to you if you can help with the statistical approach for case-control study to link DNA methylation (epic array) with toxic element exposure (arsenic) and health outcome (...
M__♦
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Advise on building an effect ML model for predicting important proteins for drug response
I want to create a model to predict proteins which could be associated with drug response in cancer cell lines. I have cell line proteomics data, with compound screening data they have gained for a ...
CommunityBot
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Model the effect of treatment on mutation burden
I am struggling a bit to model the following problem. Basically, I would like to model tumor mutation burden (mutations per megabase, a continuous) as a function of treatment (categorical). The ...
CommunityBot
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What are the fastest way of feature selection in R for large dataset in Machine Learning?
I have about 100 data sets with over 100,000 rows and 27 predictor variables and multiple response variable on each dataset. I want to select the most essential Features for these datasets. I used ...
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How to get coefficient tables from multiple regression model result!
I've done multiple regression modeling in R using the below script. Now I'm wondering how can I make a table for the coefficients of each model of all models from lm, glm, and rf separately.
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PLINK linear association testing command with an interaction and 2 covariates term
I am trying to write the right command for my association testing using PLINK 1.9 but I could not find a clear answer so far and not sure how to wrtie it correct.
I have genotype variants called and ...
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How do I resolve disagreements in the determination of significant genes?
I want to find some good predictors (genes). I have checked the Spearman correlation of the expression of each of 23 genes with dependent variables (responders Vs non-responders and I saw only the 5 ...
- 13.8k
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Trouble optimizing Five Parameter Logistic (5PL) Standard Curve for ELISA data using Python
I am writing a Python script to automate a 5PL Standard Curve for ELISA data, using an XLSX file template. I am using pandas dataframes to hold the 96 wells as ...
M__♦
- 11.9k
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Inflated p-values in quantitative trait analysis
I am performing a quantitative trait association between the expression of one gene and ~400,000 methylation values. First, both variables are rank inverse normal transformed, adjusted for confounders ...
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Can I use a regular liner regression model when I'm working with DNA methylation data?
I'm new on working with genetics data and I'm just wondering if I can use the lm function when I'm building my models or do I have to use ...
CommunityBot
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What is the difference between fixed effects and random effects in the context of Linear-mixed models?
The terms in LME i.e. fixed and random create confusion? What is the genesis that can distinguish between the two ?
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GWAS, MWAS, EWAS: what are the (in)dependent variables?
I started reading some papers on X-wide association studies, where X can be metabolome, epigenome, etc... The authors usually describe which are the dependent and which are the independent variables ...
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How do I Investigate and test the hypothesis on the effect of street-light regime on insects?
I need advice on a suitable analysis of a dataset that has an akward design because we investigate a real-world situation. We have two sites (A, B) where we can conduct the research. The hypothesis ...
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Detect differentially expressing cells
after comments on my original post, I will ask my question again here
I have data (RNA expression values, obtained with multi-channel in situ hybridization) collected from 1mio human cells. For each ...
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Doing plot with this data
I have normalized expression values of some genes in some patients and the how many days they have survived from their diagnosis with cancer like below
EDITED
I have taken mean of the expression ...
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How are residuals used as new phenotype?
I'm a novice trying to wrap my head around with fancy jargons. If I search residual, I understand that it represents the difference between the observed value of the dependent variable (y) and the ...
M__♦
- 11.9k
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Scaling by linear regression against the number of reads
I am trying to build the preprocessing pipeline presented in The Tabula Muris Consortium et al. (pp).
It is a pipeline to preprocess single-cell sequencing data. There is one step that is not clear:
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Regressing out unwanted sources of variation in single cell RNA-seq data
I have a dataset of single cell count data and I want to regress out the variation caused by the number of UMI's and the percentage of mitochondrial genes.
I know that count data is discrete data, ...
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