gene | Code generation for projects | JSON Processing library
kandi X-RAY | gene Summary
kandi X-RAY | gene Summary
JSON Schema specifies a JSON-based format to define the structure of your data for various cases, like validation, documentation, and interaction control. A JSON Schema provides a contract for the JSON data required by a given application, and how that data can be modified. TLDR: here is an example tinder.json.
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Top functions reviewed by kandi - BETA
- GenerateJSValidator generates JS validator
- Main entry point for testing
- generate runs the given Schema against the given schema .
- Configure implements ClientOption .
- execute executes the given op and returns the output .
- configure configures an OpenAPI schema
- GenerateModelStatements generates the statements for the given schema .
- GenerateModel generates a model for the given schema .
- AccountRowsScan scan rows .
- pluginCmd builds the exec . Cmd for the plugin .
gene Key Features
gene Examples and Code Snippets
Community Discussions
Trending Discussions on gene
QUESTION
I would like to standardize a dataframe by the value in one specific column. In other words, I would like to divide all the values in each row by the value in a specific column.
For example:
The dataframe is
Gene P1 P2 P3
A1 6 8 2
A2 12 6 3
A3 8 4 8
I would like to divide all the values in each row by the value in that row for column P3.
Gene P1 P2 P3
A1 6/2 8/2 2/2
A2 12/3 6/3 3/3
A3 8/8 4/8 8/8
The new dataframe would be:
Gene P1 P2 P3
A1 3 4 1
A2 4 2 1
A3 1 .5 1
Thank you for your help.
...ANSWER
Answered 2021-Jun-15 at 01:22Using tidyverse functions:
QUESTION
I have the following data frame:
...ANSWER
Answered 2021-Jun-14 at 17:25We can use sub
to match the .
(metacharacter - so escape) followed by one or more digits (\\d+
) at the end ($
) of the string and replace with blank (""
)
QUESTION
I have the following data frame:
...ANSWER
Answered 2021-Jun-11 at 18:41You could use split.default
:
QUESTION
I have a data set similar to this tibble:
...ANSWER
Answered 2021-Jun-11 at 18:53We could select
the columns that starts_with
'A', then reshape to 'long' format with pivot_longer
and get the count
QUESTION
I need to submit a slurm array that will run the same script 18000 times (for independent genes), and I wanted to do this in a way that won't cause problems for my Uni's cluster.
Currently, the MaxArraySize
set by the admins is 2048
. I was going to manually set my options like:
First array script:
...ANSWER
Answered 2021-Jun-11 at 11:31You can submit two jobs with
QUESTION
I have the following dataframe:
...ANSWER
Answered 2021-Jun-09 at 09:59QUESTION
I am struggling to separate a single string input into a series of inputs. The user gives a list of FASTA formatted sequences (see example below). I'm able to separate the inputs into their own
ex:
...ANSWER
Answered 2021-Jun-09 at 19:37One option with tidyverse
QUESTION
my dataframe looks like this:
...ANSWER
Answered 2021-Jun-09 at 21:45If I understand your question correctly, this is what you're trying to achieve:
QUESTION
I'm trying to use fuzzy string matching to convert strings to specific ids and perform grouped summarization using dplyr. The basic idea is combining imperfect gene sequences into a single gene name via a dictionary lookup approach and counting how many times the gene is detected. This way, counts for sequences aaaaaa
and aaaxaa
match to gene1
and get added together.
I can do what I want using for
and if
statements via a row-by-row comparison of the raw data against the dictionary but I find this will be inefficient when I scale up (raw data files have 15k rows on average, the dictionary has 200 rows). Please see my solution below I'm trying to improve and let me know if you can think of a more efficient and elegant way of doing this.
ANSWER
Answered 2021-Jun-08 at 21:12perhaps a fuzzyjoin
would be more easier
QUESTION
I have a tab delimited binary matrix of bacterial strain names and genes, listed as present (1) or absent (0), which is output by ROARY (pangenome pipeline).
This is a mock version of the data:
...ANSWER
Answered 2021-Jun-08 at 19:55We can do a group by operation i.e. grouped by 'gene', check if all
the 'a', 'b' are found in the 'strain' where the 'pres_abs' value is 0 and to avoid getting the 1 values in pres_abs, create a second condition i.e. 'pres_abs' as 0
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