Genome | type safe , failure driven mapping library | Serialization library

by loganwright Swift Version: 3.2.0 License: MIT

X-Ray Key Features Code Snippets(2)Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | Genome Summary

Genome is a Swift library typically used in Utilities, Serialization applications. Genome has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

Welcome to Genome 3.0. This library seeks to satisfy the following goals:.

Support

Quality

Security

License

Reuse

Support

Genome has a medium active ecosystem.

It has 779 star(s) with 61 fork(s). There are 27 watchers for this library.

It had no major release in the last 12 months.

There are 12 open issues and 25 have been closed. On average issues are closed in 42 days. There are 4 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of Genome is 3.2.0

Quality

Genome has no bugs reported.

Security

Genome has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

Genome is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

Genome releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

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Genome Key Features

No Key Features are available at this moment for Genome.

Genome Examples and Code Snippets

Main method to test out the genome .

java

Lines of Code : 40

License : Permissive (MIT License)

Copy

public static void main(String[] args) throws Exception{
		Scanner scan=new Scanner(new File("cownomics.in"));
		PrintWriter writer = new PrintWriter(new File("cownomics.out"));
		
		int n=scan.nextInt();
		int m=scan.nextInt();
		scan.nextLine();

Return the fitness of the genome .

python

Lines of Code : 19

License : No License

Copy

def fitness(self):
        """
        Function to calculate the fitness of the current organism. 
        B{This function MUST be over-ridden by the inherited class or 
        substituted as fitness function is highly dependent on utility.} The

Community Discussions

Trending Discussions on Genome

Failed to convert a NumPy array ((the whole sequence is a string)) to a Tensor, in genome sequence classification for CNN?

add text to a path by adding text to it with python (FTP Path NCBI)

How to plot rarefaction curves in R using Vegan?

Learn structure of XML file in preparation for CSV or RDF conversion

Change separator just between specific columns

How to add rows to dataframe by combining values of already existing rows with R dplyr

Multiple condition between two pandas dataframe

Turning multiple rows into a string by merging on ID in R

Splitting columns by values in a lookup table in R

parsing text into pandas using regular expressions, but empty dataframe produced

QUESTION

Failed to convert a NumPy array ((the whole sequence is a string)) to a Tensor, in genome sequence classification for CNN?

Asked 2021-Jun-10 at 21:54

The data is basically in CSV format, which is a fasta/genome sequence, basically the whole sequence is a string. To pass this data into a CNN model I convert the data into numeric. The genome/fasta sequence, which I want to change into tensor acceptable format so I convert this string into float e.g., "AACTG,...,AAC.." to [[0.25,0.25,0.50,1.00,0.75],....,[0.25,0.25,0.50.....]]. But the conversion data shows like this (see #data show 2). But, when I run tf.convert_to_tensor(train_data) it gives me an error of Failed to convert a NumPy array to a Tensor (Unsupported object type numpy.ndarray). But in order to pass the data into CNN model, it has to be a tensor, but I don't know why it gives an error! What will be the solution to it?

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ANSWER

Answered 2021-Jun-10 at 21:47

The problem is probably in your numpy array dtype.

Using array with dtype float32 should fix problem: tf.convert_to_tensor(train_data.astype(np.float32))

Source https://stackoverflow.com/questions/67928717

QUESTION

add text to a path by adding text to it with python (FTP Path NCBI)

Asked 2021-Jun-10 at 18:06

I'm in a bind please. do you know if i can duplicate the last folder in the path please and add "_genomic.fna.gz" to it for example how to change from this

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ANSWER

Answered 2021-Jun-10 at 18:06

urllib.parse.urlparse can split your URL into parts we can work with. posixpath.join can help us build the full path. urllib.parse.urlunparse can help us get a complete URL back.

Source https://stackoverflow.com/questions/67926197

QUESTION

How to plot rarefaction curves in R using Vegan?

Asked 2021-Jun-07 at 15:01

I have a dataset containing genes identified in different reference genomes. So, the reference genomes are in the Rows and the genes are in the columns of the table. The table is coded as a binary where 0 means the gene is absent and 1 means the gene is present. I made gene accumulation curves, which indicates that the number of genes per genomes is approaching a plateau. Now, I am trying to plot the rarefaction curves using the R-package vegan. I used the following codes:

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ANSWER

Answered 2021-Jun-07 at 15:01

rarefy function rarefies individual rows of your data: it takes a subsample of your occurrences ("individuals") within each row. If all these sampled individuals have value 1, you will have a subsample of ones, and the sum of ones is the sample size: that was what you got. There is no meaningful way of rarefying a vector of ones: you need count data with some counts > 1.

You were perhaps looking for accumulation of genes in your whole data set when subsampling rows of the matrix. This is done in vegan function specaccum (argument method = "exact") which has its own plot etc methods.

Source https://stackoverflow.com/questions/67863207

QUESTION

Learn structure of XML file in preparation for CSV or RDF conversion

Asked 2021-Jun-06 at 17:58

I would like to convert NCBI's Biosample Metadata XML file to CSV, or RDF/XML as a second choice. To do that, I believe I have to learn more about the structure of this file. I can run basic XQueries in BaseX*, like just listing all values, but then I've been using shell tools like sort|uniq -c to count them. I have heard about XSLT transformations and GRDDL in passing, but I don't think a style sheet is provided for this XML document, and I don't know how to create or discover one.

For example, can I get a count of the number of s for each ? Are there any with more than one primary ? What are the most common db attributes of the primary Ids?

Here's a query that shows my maximum level of XQuery sophistication at this point:

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ANSWER

Answered 2021-Jun-06 at 17:58

similar to my answer for https://www.biostars.org/p/280581/ using my tool xsltstream:

Source https://stackoverflow.com/questions/67850041

QUESTION

Change separator just between specific columns

Asked 2021-May-27 at 11:07

I am trying to change the separator just between columns 1 and 9. After that, I would like to maintain the original separator.

Those are first lines of my file both when directly reading it and when od -c file is executed:

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ANSWER

Answered 2021-May-26 at 11:22

By default sed s/.../.../ replaces only the first occurrence. Therefore you can repeat this substitution 8 times. Here, we also ignore lines starting with #.

In bash, repeating can be done by using the brace expansion {1..8} and printf.

Source https://stackoverflow.com/questions/67703405

QUESTION

How to add rows to dataframe by combining values of already existing rows with R dplyr

Asked 2021-May-26 at 14:35

I have the following table, which i would like to modify:

type position ratio number percentage DNA intergenic 0.00026933362 225173 40.757876065 DNA intragenic 0.00021799943 41250 7.466536342 LINE intergenic 0.00027633335 48619 8.800376494 LINE intragenic 0.00031015097 9578 1.733684487

I want to add rows that contain the following modifications:

type: if the value "type" is identical between two rows (it always is in my case), add it again in a separate row of the column "type".
position: change the value from intergenic/intragenic to "genome" if (1)
ratio: ratio value would be the weighted mean calculated from the ratio of intergenic and intragenic rows of the same type value:
((number_intragenic * ratio_intragenic) + (number_intergenic * ratio_intergenic))/(number_intragenic + number_intergenic)
number: sum of number values for the same type: sum(number_intergenic + number_intragenic)
sum of the percentage values for the same type: sum(percentage_intergenic + percentage_intragenic)

My problem is that I do not know how to add rows to dataframe by making specific calculation from already existing rows. It is easy to add columns using mutate in dplyr. How can I do this for rows?

I would much prefer if the solution is provided in dplyr.

Edit: The formula of the weighted mean was wrong. I had added a + sign instead of a * sign in the following part of the formula: (number_intergenic + ratio_intergenic). It has now been fixed.

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ANSWER

Answered 2021-May-12 at 17:43

Dedicated to dear @akrun who taught me how to do this:

Source https://stackoverflow.com/questions/67507460

QUESTION

Multiple condition between two pandas dataframe

Asked 2021-May-19 at 18:05

I am working on a variant calling Format(.vcf) file. I am separating genotype Allele from individual genome data and calculating the chance of having the specific disease. Based on my analysis I need to implement a condition like : I have two different panda data frame which are extracted from .vcf file

Diseases

SNP EfectSize MinorAlleFrequency rs05 0.32 0.09 rs012 0.5 0.20 rs02 0.8 0.29

2.IndividualSNPs

SNP cola colb rs02 0 1 rs03 1 1 rs12 0 0

my condition will be like: if number 1.dataframe (Diseases) column 'SNP' is match with number 2. dataframe (individualSNPs) column 'SNP'. then I will check from individualSNPs dataframe cola and colb column.

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ANSWER

Answered 2021-May-19 at 18:05

First you could start by merging your dataframes so that you get a new dataframe with columns from both dataframes, and only keep rows from the Diseases dataframe (column SNP) that exist in the IndividualSNPs dataframe (column SNP). It would be like :

Source https://stackoverflow.com/questions/67482929

QUESTION

Turning multiple rows into a string by merging on ID in R

Asked 2021-May-12 at 13:49

Table1:(there are hundreds of IDs)

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ANSWER

Answered 2021-May-12 at 13:46

There are several things to say with your data.

First, your table1 has duplicated columns: year_of_birth, affected_relative, and genome are the same for a given participant.

This should better be stored in a separate table, which I named table1_short.

For your very question, it is only a matter of checking whether a term is in a vector, which is done using %in%.

Here is how you could write the code:

Source https://stackoverflow.com/questions/67504636

QUESTION

Splitting columns by values in a lookup table in R

Asked 2021-May-12 at 11:43

I have a table, one one line per hpo_term so a single patient can have many lines per ID.

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ANSWER

Answered 2021-May-06 at 15:17

Here's a dplyr solution:

Source https://stackoverflow.com/questions/67420453

QUESTION

parsing text into pandas using regular expressions, but empty dataframe produced

Asked 2021-May-12 at 04:13

I am trying to parse the following data into pandas from a text file:

...

ANSWER

Answered 2021-May-12 at 03:46

the parse_file function needs some logical correction.

Changes are like:

case sensitive 'Source' vs 'source'
moved data.append(row)
readline() vs readlines(), read line will read one line ; so "for loop" was looping on characters which was not the intend here.

Source https://stackoverflow.com/questions/67496527

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install Genome

Let's take the following hypothetical JSON. Here's how we might create the model for this.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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