jvfe

Este é um guia básico para configurar algumas configurações básicas para executar pipelines Nextflow no NPAD.

Primeiro, estou assumindo que sua análise ocupará mais de 9 GB (sua cota de espaço no diretório home), então você precisará usar o disco scratch para armazenar os resultados e as imagens Singularity.

0. Instalar conda e nf-core

Aqui, recomendo usar o conda para instalar o Nextflow e o nf-core.

Baixe e instale o conda: https://docs.conda.io/en/latest/miniconda.html

jvfe

ch = Channel.empty()
ch2 = Channel.empty()

ch = ch.mix(Channel.value('database'))
Channel.value('database').set{ ch2 }


println(ch)
println(ch2)

jvfe

R Community Explorer - Exploration of the R community on Twitter

Mentors: Ben Ubah, Rick Pack and Gergely Daroczi

Mentee: João Vitor F. Cavalcante

Main Project Repository: https://github.com/r-community/central

Commit log in main repository: https://github.com/r-community/central/commits?author=jvfe

jvfe

read1	WP_005581541.1	98.2	40	1	0	129	299	1	57	7.7e-22	113.6
read2	WP_005575885.1	100.0	60	0	0	181	2	1	60	2.2e-24	122.1
read3	WP_005580014.1	100.0	50	0	0	2	151	385	434	3.6e-19	104.8
read4	WP_005576929.1	100.0	98	0	0	296	3	308	405	6.7e-42	180.3
read5	ELY74166.1	98.0	100	2	0	300	1	80	179	7.9e-43	183.3
read5	WP_015233403.1	98.0	100	2	0	300	1	98	197	7.9e-43	183.3
read6	WP_005578121.1	100.0	52	0	0	1	156	124	175	1.6e-22	115.9
read7	WP_005576999.1	92.0	100	8	0	1	300	14	113	1.1e-47	199.5
read8	WP_005579760.1	98.0	100	2	0	2	301	214	313	1.8e-42	182.2
read8	AFZ74922.1	98.0	100	2	0	2	301	188	287	1.8e-42	182.2

jvfe

#!/bin/bash

curl https://www.toptal.com/developers/gitignore/api/python,r,linux,visualstudiocode >> .gitignore

jvfe

from pyshex.shex_evaluator import ShExEvaluator
from pyshex.user_agent import SlurpyGraphWithAgent
from pyshex.utils.sparql_query import SPARQLQuery
import pandas as pd


def test_query_against_shex(schema, sparql):
    """Checks the items resulting from a Wikidata query against a shex schema
    
    Using PyShEx, we can check the validity of multiple items against a predefined

jvfe

#!/bin/bash

libreoffice --headless --convert-to pdf:writer_pdf_Export "$1" --outdir .

jvfe

from collections import defaultdict
import pandas as pd
import requests


def perform_query(query):
    """Performs a SPARQL query to the wikidata endpoint

    Args:
        query: A string containing a functional sparql query

jvfe

from bokeh.io import show
from bokeh.models import Range1d, Plot, Circle, HoverTool, MultiLine
from bokeh.models.graphs import NodesAndLinkedEdges
from bokeh.plotting import from_networkx
import networkx as nx

def plot_network(network, tooltip, layout=nx.kamada_kawai_layout):
    """Makes a nice network plot with Bokeh

    Mostly stuff I pieced together from the bokeh tutorials.

jvfe

get_summary <- function(geneids){
  summary_list <- entrez_summary("gene", id = geneids, ) %>% 
    extract_from_esummary(elements = c("uid", "summary"), simplify = TRUE) %>% 
    as_tibble() %>% 
    unnest()
  
  gene_names <- summary_list %>% 
    slice(1) %>% 
    as.character()