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The thresholds were chosen to balance the number of high-risk and low-risk patients. Details of the SEQC-neuroblastoma dataset are provided in Supplementary Table S9. We also used an 87-sample lung adenocarcinoma RNA-seq dataset from The Cancer Genome Atlas (TCGA) repository. The prediction ...
B Quality control of sequenced data shows the number of raw counts per genome feature in the nuclear transcriptome. C Violin plots comparing the high number of genes detected using snRNA-seq2 to publicly available single-cell RNA-seq datasets. Light brown: droplet-based methods (n = 10,...
we describe a technique for measuring fold change that takes into account the uncertainty of gene expression measurement by RNA-seq.Our representation of fold change is derived from the posterior distribution of the raw fold change.This representation, denoted as GFOLD, balances the estimated degree ...
After running nanopolish eventalign, we need to preprocess the segmented raw signal file using 'm6anet dataprep':: m6anet dataprep --eventalign /path/to/m6anet/m6anet/tests/data/eventalign.txt \ --out_dir /path/to/output --n_processes 4 ...
We used Trim Galore v0.6.6 to trim the adapter and low-quality raw reads. Random sampling of a desired number of sequencing reads was done using the Seqtk tool (v1.3). Reads were then aligned to the human reference genome GRCh38-2020-A with STAR tools (v2.7.9a) [11]. Reads per ...
高通量测序(如Illumina NovaSeq 6000等测序平台)得到的原始图像数据文件,经碱基识别(Base Calling)分析转化为原始测序序列(Sequenced Reads),我们称之为Raw Data或Raw Reads,结果以FASTQ(简称为fq)文件格式存储,其中包含测序序列(Reads)的序列信息以及其对应的测序质量信息。测序样品中真实数据随机截取结果如下: ...
The pre-processing of the raw FastQ file consists of quality check, adapter removal, trimming, and filtering (Figure 2). Figure 2. Data pre-processing steps. Checking the quality of the reads in the raw FastQ files is a crucial step in the sequencing data analysis pipeline. The quality of...
Raw sequencing data processing For sample-wise allocation of the sequencing data, the raw reads from each lane of flow cell were demultiplexed using the respective index sequence. Initial processing of sequencing data was performed using MCIC galaxy tools available at http://www.oardc.ohio-state....
Figure S4. Copy number alterations (CNAs) analysis from scRNA-seq data. Figure S5. Characterization of nPCs from healthy donors and myeloma cells from MM. Figure S6. Intra-tumor heterogeneity of MM. Figure S7. Analysis of myeloma cells pre/post-treatment. Figure S8. Analysis of myeloma cells...