There are 399 articles for you to read.

RNAseq processing (1457)

Author: gene_x

Abstract: 1. construct DESeqDataSet from Matrix library("AnnotationDbi") library("clusterProfiler") library("ReactomePA") library("org.Hs.eg.db") library(DESeq2) library(gplots) library(ggplot2)

Exploring Integrative Analysis of Multi-Omics Data from Public Repositories

Author: gene_x

Abstract: 1. Integration and analysis of multi-omics data: Explore the integration of different types of omics data (e.g., genomics, transcriptomics, proteomics) from public repositories to uncover novel biolog

Defining and Categorizing Promoter Types Based on the 'GRGGC' Motif Frequency and Distance to TSS

Author: gene_x

Abstract: 1. generate_promter_sequences #!/usr/bin/env python3 #./1_generate_promoter_sequences.py gencode.v43.annotation.gtf.db import gffutils from pyfaidx import Fasta import argparse from Bio i

Antibodies and cell lines that are commonly used in research

Author: gene_x

Abstract: >http://genome.ucsc.edu/cgi-bin/hgTrackUi?db=hg19&g=wgEncodeBroadHistone Antibody: - CBP (SC-369) - H3K4me1 - H3K4me2 - H3K4me3 - H3K9ac - H3K9me1 - H3K9me3 - H3K27ac - H3K27me3 - H3K36me3 - H3K79me

Gonna、wanna、gotta

Author: huang

Abstract: 1. Gonna 將會 Gonna 是 (be) going to 的非正式用法,表示「某人將會/將要做某事」的意思,常見於口語對話或是流行歌曲中,是一種比較輕鬆的表達方式,其句型為「主詞+be 動詞+gonna+原形動詞」。 A: Dylan, do you have any plans for Chinese New Year ? A:Dylan,你農曆年有沒有什麼計畫? B: Oh

Identifying the Nearest Genomic Peaks within Defined Regions

Author: gene_x

Abstract: To find the closest peaks in the genome regions defined by a bed file, you can use a tool like BEDTools. BEDTools provides a function `closest` which allows you to find the closest feature in a second

LiftOver: An Essential Utility for the Conversion of Genomic Coordinates

Author: gene_x

Abstract: If you have genomic coordinates (like gene positions, SNP positions etc) in hg19 and want to convert them to hg38, you'd use what's known as a "liftover". The UCSC Genome Browser provides a tool speci

Analysis of Peak Distribution in Promoters

Author: gene_x

Abstract: import pprint import argparse import matplotlib.pyplot as plt import pandas as pd import gffutils import numpy as np #db = gffutils.create_db('gencode.v43.annotation.gtf', dbfn='gencode.v43.an

Clustering of Promoter Types Based on Motif Frequency and Distribution

Author: gene_x

Abstract: To implement the clustering of promoter types based on motif frequency and distribution using Python, you can follow these steps: 1. Import the required libraries: import pandas as pd import num

Snakefile

Author: gene_x

Abstract: import os ####################################################### ############### Snakefile Configuration ############### ####################################################### configfile: "ba


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