mitools | yet another Next Generation Sequencing data | Genomics library
kandi X-RAY | mitools Summary
kandi X-RAY | mitools Summary
MiTools: yet another Next Generation Sequencing (NGS) data processing tool (based on MiLib)
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Top functions reviewed by kandi - BETA
- Perform the actual processing
- Get the total trimmed reads
- Returns the number of nucleotides left in the molecule
- Returns the number of removed nucleotides
- Generate and write out the part files
- Convert part index to string
- Gets the sequence reader
- Gets a sequence writer
- Main method
- Creates a single fastq writer
- Creates a single fast read fastq reader
- Main function
- Returns an InputStream for the given file name
- Processes the actions
- Main entry point
- Process a single read operation
- Do the actual processing
- Randomize chunks
- The main method
- Process a single read
- Takes a read of the next available read
- Checks if the minimum length is greater than minLength
- Get the number of left reads left to the left
- Returns the number of reads left to right
mitools Key Features
mitools Examples and Code Snippets
Community Discussions
Trending Discussions on mitools
QUESTION
I am trying to print a regression model using tbl_regression() on a plm object with multiply imputed data. I've found that I can print the regression table if the plm has one independent variable, but not if it has two or more independent variables.
I understand that the below error message is common, but I don't understand what it means in the context of tbl_regression and multiply imputed data. Is there a bug in gtsummary, or is something wrong with my code?
ANSWER
Answered 2022-Jan-28 at 02:51Thank you! This code now works under the current version of gtsummary.
QUESTION
I need to calculate the sum of some variables with imputed values. I did this with complete --> as.mids --> with --> do.call
I needed to do the same thing but in a survey context. Therefore, I did: update --> with --> MIcombine
The means of the variables calculated both ways do not match. Which one is correct?
You may check this different behavior in this toy database:
...ANSWER
Answered 2021-Jun-07 at 10:54Answer
Replace do.call(mean, res$analyses) with mean(unlist(res$analyses)).
Rationale
In the first code snippet, res$analyses is a list. When entering it into do.call, you are essentially calling:
QUESTION
I am using multiple imputation on missing data and then using the pool_mi function to get coefficients. Since my data is clustered I also had to calculate cluster robust SE my regression model using the lm.cluster function. However the output for the coefficients is in log odds form I believe. How can I convert the coefficients to be marginal effects? Or if that is not possible to be in probabilities? I've tried to follow this posts (linked here) but can't figure it out since my situation is a bit more complicated... Below is the example code for what I have done with the function and images of the output. Thank you!
...ANSWER
Answered 2021-May-11 at 04:45Loop through the datlist using for loop to calculate cluster robust SE of you regression model using the lm_robust function. In assigning mod using lapply by default takes a closure type object that is not subsettable:
QUESTION
I am using multiple imputation on missing data and then using the pool_mi function to fit the results of the imputation trials to my regression model. However the output is not formatted in an easily interpretable way and I am hoping to get some guidance on how to do so. Below is the example code for what I have done with the function and images of the output vs my desired output.
...ANSWER
Answered 2021-Apr-25 at 23:42I do not know how to achieve this in stargazer, but it is very easy to do with the modelsummary package for R (disclaimer: I am the author).
modelsummary supports 100+ models out-of-the-box, but not model objects of class pool_mi, which is what your code produces. Fortunately, it is very easy to add support for new models, as described in detail in the documentation.
Specifically, we need to define two S3 methods called tidy.CLASSNAME and glance.CLASSNAME. The first method returns a data.frame with one coefficient per row and with column names that follow the standard terminology from the broom package. The second method returns a one-row data.frame with goodness-of-fit or other model characteristics, one per column.
In your case, these simple methods seem to do the job (obviously, you can customize):
QUESTION
I'm trying to analyze complex survey data with Survey. I imputed missing data with mice and, following the instructions in the documentation, have converted the imputations to an imputationList object with imputationList()in mitools. But when I try to use that object as data in svydesign(), I get this error message:
...ANSWER
Answered 2021-Mar-24 at 21:45Here's the example from the documentation
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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Install mitools
You can use mitools like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the mitools component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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