CaClust: linking genotype to transcriptional heterogeneity of follicular lymphoma using BCR and exomic variants [0.03%]
利用BCR和外显子变异对 follicular淋巴瘤进行基因型到转录异质性联系的CaClust研究
Kazimierz Oksza-Orzechowski,Edwin Quinten,Shadi Shafighi et al.
Kazimierz Oksza-Orzechowski et al.
Tumours exhibit high genotypic and transcriptional heterogeneity. Both affect cancer progression and treatment, but have been predominantly studied separately in follicular lymphoma. To comprehensively investigate the evolution and genotype...
TDFPS-Designer: an efficient toolkit for barcode design and selection in nanopore sequencing [0.03%]
TDFPS-Designer：纳米孔测序条形码设计与选择的高效工具包
Junhai Qi,Zhengyi Li,Yao-Zhong Zhang et al.
Junhai Qi et al.
Oxford Nanopore Technologies (ONT) offers ultrahigh-throughput multi-sample sequencing but only provides barcode kits that enable up to 96-sample multiplexing. We present TDFPS-Designer, a new toolkit for nanopore sequencing barcode design,...
Benchmarking and building DNA binding affinity models using allele-specific and allele-agnostic transcription factor binding data [0.03%]
基于等位基因特异性和非特异性转录因子结合数据的DNA结合亲和力模型的基准测试与构建
Xiaoting Li,Lucas A N Melo,Harmen J Bussemaker
Xiaoting Li
Background: Transcription factors (TFs) bind to DNA in a highly sequence-specific manner. This specificity manifests itself in vivo as differences in TF occupancy between the two alleles at heterozygous loci. Genome-scale...
Winsorization greatly reduces false positives by popular differential expression methods when analyzing human population samples [0.03%]
winsor化可大幅减少人口群体样本差异表达分析中的假阳性结果
Lu Yang,Xianyang Zhang,Jun Chen
Lu Yang
A recent study found severely inflated type I error rates for DESeq2 and edgeR, two dominant tools used for differential expression analysis of RNA-seq data. Here, we show that by properly addressing the outliers in the RNA-Seq data using w...
Neglecting the impact of normalization in semi-synthetic RNA-seq data simulations generates artificial false positives [0.03%]
忽略标准化对半合成RNA序列数据模拟的影响会产生虚假阳性结果
Boris P Hejblum,Kalidou Ba,Rodolphe Thiébaut et al.
Boris P Hejblum et al.
A recent study reported exaggerated false positives by popular differential expression methods when analyzing large population samples. We reproduce the differential expression analysis simulation results and identify a caveat in the data g...
Response to "Neglecting normalization impact in semi-synthetic RNA-seq data simulation generates artificial false positives" and "Winsorization greatly reduces false positives by popular differential expression methods when analyzing human population samples" [0.03%]
关于“忽略标准化影响对半合成RNA序列数据模拟产生虚假阳性”的回应以及“分析人类群体样本时 winningsion大幅减少流行差异表达方法的虚假阳性”
Xinzhou Ge,Yumei Li,Wei Li et al.
Xinzhou Ge et al.
Two correspondences raised concerns or comments about our analyses regarding exaggerated false positives found by differential expression (DE) methods. Here, we discuss the points they raise and explain why we agree or disagree with these p...
pan-Draft: automated reconstruction of species-representative metabolic models from multiple genomes [0.03%]
全基因组草图：从多个基因组自动重建物种代表性代谢模型
Nicola De Bernardini,Guido Zampieri,Stefano Campanaro et al.
Nicola De Bernardini et al.
The accurate reconstruction of genome-scale metabolic models (GEMs) for unculturable species poses challenges due to the incomplete and fragmented genetic information typical of metagenome-assembled genomes (MAGs). While existing tools leve...
Plant conservation in the age of genome editing: opportunities and challenges [0.03%]
基因编辑时代的植物保护：机遇与挑战
Kangquan Yin,Mi Yoon Chung,Bo Lan et al.
Kangquan Yin et al.
Numerous plant taxa are threatened by habitat destruction or overexploitation. To overcome these threats, new methods are urgently needed for rescuing threatened and endangered plant species. Here, we review the genetic consequences of thre...
STASCAN deciphers fine-resolution cell distribution maps in spatial transcriptomics by deep learning [0.03%]
基于深度学习的STASCAN解码空间转录组学中细胞分布精细图谱
Ying Wu,Jia-Yi Zhou,Bofei Yao et al.
Ying Wu et al.
Spatial transcriptomics technologies have been widely applied to decode cellular distribution by resolving gene expression profiles in tissue. However, sequencing techniques still limit the ability to create a fine-resolved spatial cell-typ...
Marius Lange,Zoe Piran,Michal Klein et al.
Marius Lange et al.
Simultaneous profiling of single-cell gene expression and lineage history holds enormous potential for studying cellular decision-making. Recent computational approaches combine both modalities into cellular trajectories; however, they cann...