OpEx | The OpEx pipeline | Genomics library

by RahmanTeam Python Version: v1.0.0 License: MIT

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

kandi X-RAY | OpEx Summary

OpEx is a Python library typically used in Artificial Intelligence, Genomics applications. OpEx has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However OpEx build file is not available. You can download it from GitHub.

OpEx runs on Linux. It requires Python 2.7.3 or later (< Python 3) with Numpy version 1.11.0 installed and Java 1.6. At least 3 Gb of memory is required, and 8 Gb is recommended. In order to make use of the optional multithreading feature, OpEx requires a multicore CPU environment.

Support

Quality

Security

License

Reuse

Support

OpEx has a low active ecosystem.

It has 6 star(s) with 3 fork(s). There are 3 watchers for this library.

It had no major release in the last 12 months.

There are 2 open issues and 1 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of OpEx is v1.0.0

Quality

OpEx has no bugs reported.

Security

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

License

OpEx 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

OpEx releases are available to install and integrate.

OpEx has no build file. You will be need to create the build yourself to build the component from source.

Installation instructions are available. Examples and code snippets are not available.

Top functions reviewed by kandi - BETA

kandi has reviewed OpEx and discovered the below as its top functions. This is intended to give you an instant insight into OpEx implemented functionality, and help decide if they suit your requirements.

Return the class annotation for a variant
Return the length of the nucleotide with the given index
Checks if the given variant is in a potential split site
Check if this variant is outside the translated region
Create CSNAnnot object
Transform genomic position to CSN coordinates
Return True if the given position is in utR
Calculates the coordinates of the given variant
Get a dictionary mapping transcript coordinates to transcript coordinates
Find transcript objects for a given position
Returns the protein sequence
Returns the coding sequence

Get all kandi verified functions for this library.

OpEx Key Features

No Key Features are available at this moment for OpEx.

OpEx Examples and Code Snippets

No Code Snippets are available at this moment for OpEx.

Community Discussions

Trending Discussions on OpEx

Improve performance of converting list of JSON string to Dataframe

Google cloud console [GCP] not working properly with k8s

How do I transfer values of a CSV files between certain dates to another CSV file based on the dates in the rows in that file?

How to solve a Pandas Merge Error: key must be integer or timestamp?

How to solve ValueError: left keys must be sorted when merging two Pandas dataframes?

How to get values from a dict into a new column, based on values in column

How to append something in a CSV file to a column in all the rows where the cell of the ticker column = 'AAPL'?

How do I keep the column names in a data frame when I am trying to drop all of the rows that don't start with specific names?

Check if files exists in PowerShell

Powershell Remove Lst element from array

QUESTION

Improve performance of converting list of JSON string to Dataframe

Asked 2021-May-24 at 11:13

For input, I have a dictionary

...

ANSWER

Answered 2021-May-24 at 11:13

You can use fast third-party libraries to parse json first (orjson, ujson), then feed them into pandas as dicts. An example using orjson:

Source https://stackoverflow.com/questions/67670710

QUESTION

Google cloud console [GCP] not working properly with k8s

Asked 2021-Apr-07 at 08:38

I have a problem with Google cloud console and kubernates

i have two projects:

...

ANSWER

Answered 2021-Apr-07 at 08:38

kubectl commands don't work based on gcloud project config. They work based on kubeconfig set in your local environment. To set kubeconfig to point to a particular project's cluster, run gcloud container clusters get-credentials cluster-name command after you change your gcloud project config. Read here for more info.

Source https://stackoverflow.com/questions/66965440

QUESTION

How do I transfer values of a CSV files between certain dates to another CSV file based on the dates in the rows in that file?

Asked 2021-Mar-16 at 04:46

Long question: I have two CSV files, one called SF1 which has quarterly data (only 4 times a year) with a datekey column, and one called DAILY which gives data every day. This is financial data so there are ticker columns.

I need to grab the quarterly data for SF1 and write it to the DAILY csv file for all the days that are in between when we get the next quarterly data.

For example, AAPL has quarterly data released in SF1 on 2010-01-01 and its next earnings report is going to be on 2010-03-04. I then need every row in the DAILY file with ticker AAPL between the dates 2010-01-01 until 2010-03-04 to have the same information as that one row on that date in the SF1 file.

So far, I have made a python dictionary that goes through the SF1 file and adds the dates to a list which is the value of the ticker keys in the dictionary. I thought about potentially getting rid of the previous string and just referencing the string that is in the dictionary to go and search for the data to write to the DAILY file.

Some of the columns needed to transfer from the SF1 file to the DAILY file are:

['accoci', 'assets', 'assetsavg', 'assetsc', 'assetsnc', 'assetturnover', 'bvps', 'capex', 'cashneq', 'cashnequsd', 'cor', 'consolinc', 'currentratio', 'de', 'debt', 'debtc', 'debtnc', 'debtusd', 'deferredrev', 'depamor', 'deposits', 'divyield', 'dps', 'ebit']

Code so far:

...

ANSWER

Answered 2021-Feb-27 at 12:10

The solution is merge_asof it allows to merge date columns to the closer immediately after or before in the second dataframe.

As is it not explicit, I will assume here that daily.date and sf1.datekey are both true date columns, meaning that their dtype is datetime64[ns]. merge_asof cannot use string columns with an object dtype.

I will also assume that you do not want the ev evebit evebitda marketcap pb pe and ps columns from the sf1 dataframes because their names conflict with columns from daily (more on that later):

Code could be:

Source https://stackoverflow.com/questions/66378725

QUESTION

How to solve a Pandas Merge Error: key must be integer or timestamp?

Asked 2021-Feb-28 at 10:49

I'm trying to merge to pandas dataframes, one is called DAILY and the other SF1.

DAILY csv:

...

ANSWER

Answered 2021-Feb-27 at 16:26

You are facing this problem because your date column in 'daily' and calendardate column in 'sf1' are of type object i.e string

Just change their type to datatime by pd.to_datetime() method

so just add these 2 lines of code in your Datasorting/cleaning code:-

Source https://stackoverflow.com/questions/66400763

QUESTION

How to solve ValueError: left keys must be sorted when merging two Pandas dataframes?

Asked 2021-Feb-27 at 19:10

I'm trying to merge two Pandas dataframes, one called SF1 with quarterly data, and one called DAILY with daily data.

Daily dataframe:

...

ANSWER

Answered 2021-Feb-27 at 19:10

The sorting by ticker is not necessary as this is used for the exact join. Moreover, having it as first column in your sort_values calls prevents the correct sorting on the columns for the backward-search, namely date and calendardate.

Try:

Source https://stackoverflow.com/questions/66402405

QUESTION

How to get values from a dict into a new column, based on values in column

Asked 2021-Feb-07 at 07:30

I have a dictionary that contains all of the information for company ticker : sector. For example 'AAPL':'Technology'.

I have a CSV file that looks like this:

...

ANSWER

Answered 2021-Feb-07 at 07:29

Use .map, not .apply to select values from a dict, by using a column value as a key, because .map is the method specifically implemented for this operation.
- .map will return NaN if the ticker is not in the dict.
.apply can be used, but .map should be used
- df['sector'] = df.ticker.apply(lambda x: company_dict.get(x))
- .get will return None if the ticker isn't in the dict.

Source https://stackoverflow.com/questions/66085264

QUESTION

How to append something in a CSV file to a column in all the rows where the cell of the ticker column = 'AAPL'?

Asked 2021-Jan-17 at 05:12

Quick question: I am trying to do some analysis on the tickers in a CSV file.

Example of CSV file (Note that these are only the first two lines and there are around 200 tickers in total):

...

ANSWER

Answered 2021-Jan-17 at 05:10

If you want to set some column value based on condition consider apply or iterrows

Source https://stackoverflow.com/questions/65757064

QUESTION

How do I keep the column names in a data frame when I am trying to drop all of the rows that don't start with specific names?

Asked 2020-Dec-18 at 18:50

I need to drop the majority of the companies in a historical stock market data CSV. The only companies I want to keep are 'GOOG', 'AAPL', 'AMZN', 'NFLX'. Note that there are over 20 000 companies listed in the CSV. I also want to filter out these companies while only using certain columns in the CSV. The columns are: 'ticker', 'datekey', 'assets', 'eps', 'pe', 'price', 'revenue'.

The code to filter out these companies is:

...

ANSWER

Answered 2020-Dec-18 at 18:50

list = ['GOOG', 'AAPL', 'AMZN', 'NFLX']
first = True

for tickers in list:
    df1 = df[df.ticker == tickers]
    if first:
        df1.to_csv("20CompanyAnalysisData1.csv", mode='a', header=True)
        first = False
    else: 
        df1.to_csv("20CompanyAnalysisData1.csv", mode='a', header=False)
    continue

Source https://stackoverflow.com/questions/65362151

QUESTION

Check if files exists in PowerShell

Asked 2020-Nov-02 at 23:38

I'm trying to copy some files from one diretory to another, check if exists and replace name if yes. And copy all files.

But it gives me the above message:

...

ANSWER

Answered 2020-Nov-02 at 19:52

The syntax is Copy-Item -Path "yourpathhere" -Destination "yourdestinationhere"

You've not specified path.

Source https://stackoverflow.com/questions/64651145

QUESTION

Powershell Remove Lst element from array

Asked 2020-Aug-07 at 23:54

I need to remove the last element from my array. This is adulterating the results.

...

ANSWER

Answered 2020-Aug-07 at 23:54

As you said,

the goal is to check only if there are duplicate names.

The short way

Source https://stackoverflow.com/questions/63308644

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

Vulnerabilities

No vulnerabilities reported

Install OpEx

OpEx can be downloaded from https://github.com/RahmanTeam/OpEx/releases. To install OpEx, unpack the tgz file and run the installation script (install.py) in the opex-v1.0.0 directory (see details below).
In order to set up the pipeline correctly, we recommend running Full Installation. In Full Installation, the GRCh37 reference genome file has to be provided when running the installation script. The reference genome file will be automatically indexed by BWA and Stampy upon installation and therefore it can take a while (approx. 2-3 hours). There is also a Quick Installation option (Section 2.3). Go into the opex-v1.0.0 folder and run: ./install.py -r /path/to/reference/human_g1k_v37.fasta. where human_g1k_v37.fasta is the file of the GRCh37 reference genome sequence which (together with the corresponding .fai file) can be downloaded from the 1000G website: - ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/technical/reference/human_g1k_v37.fasta.gz - ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/technical/reference/human_g1k_v37.fasta.fai. Note that OpEx expects the unzipped .fasta file, and the .fai file will also need to be in the same folder as the .fasta file. Once the installation script has finished, OpEx is ready for use.
In Quick Installation one is not required to provide the reference genome, instead a path pointing to an existing genome installation can be set manually or the reference can be supplied upon the first run. Go into the opex-v1.0.0 folder and run: ./install.py. Once the installation script has finished, OpEx is ready for use. However, the GRCh37 reference genome must be set manually or supplied upon first run.
A test dataset is included with the package to confirm OpEx is installed correctly.
Input test files: Two gzipped FASTQ files (test_R1.fastq.gz, test_R2.fastq.gz) containing 372 read pairs mapping to three exons of BRCA2 and a BED file (test.bed) containing the coding exons of BRCA2 in hg19 genomic coordinates.
Expected test output files: Eleven output files generated by a correct installation of OpEx. Four files (the bash script file, the log file, the Picard metrics file, and the Platypus log file) are not included as these are dependent on the date, time, and system and are thus not informative as a test of successful installation.

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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