Conserved regulation of RNA processing in somatic cell reprogramming

Name: Conserved regulation of RNA processing in somatic cell reprogramming
Creator: Zenodo
Published: 2020-07-17 21:15:27
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Data set 1. Transcript expression across human RNA-Seq samples: estimated read counts. The file contains estimated read counts, generated by kallisto (https://pachterlab.github.io/kallisto/), for human transcripts and RNA-Seq samples used in this study (see Additional file 2 of the accompanying publication). The format is a compressed (GZIP) tab-separated transcript-by-sample matrix. Ensembl transcript identifiers and a combined Sequence Read Archive study/sample name identifier serve as row and column names, respectively. Data set 2. Transcript expression across murine RNA-Seq samples: estimated read counts. As in Data set 1, but for mouse transcripts. Data set 3. Transcript expression across simian RNA-Seq samples: estimated read counts. As in Data set 1, but for chimpanzee transcripts. Data set 4. Transcript expression across across human RNA-Seq samples: estimated transcript abundances. As in Data set 1, but instead of read counts, transcript abundances in transcripts per million (TPM), as estimated by kallisto (https://pachterlab.github.io/kallisto/), are listed. Format, column and row names as in Data set 1. Data set 5. Transcript expression across murine RNA-Seq samples: estimated transcript abundances. As in Data set 4, but for mouse transcripts. Data set 6. Transcript expression across simian RNA-Seq samples: estimated transcript abundances. As in Data set 4, but for chimpanzee transcripts. Data set 7. Differential expression analyses across human RNA-Seq sample groups: log fold changes. The file contains log fold changes, inferred by edgeR (http://bioconductor.org/packages/release/bioc/html/edgeR.html), for human genes and the RNA-Seq sample group contrasts listed in Additional file 3 of the accompanying publication in a compressed (GZIP) TSV gene-by-comparison matrix. Ensembl gene identifiers and a descriptive contrast identifier serve as row and column names, respectively. Data set 8. Differential expression analyses across murine RNA-Seq sample groups: log fold changes. As in Data set 7, but for mouse genes. Data set 9. Differential expression analyses across simian RNA-Seq sample groups: log fold changes. As in Data set 7, but for chimpanzee genes. Data set 10. Differential expression analyses across human RNA-Seq sample groups: false discovery rates. The file contains false discovery rates (FDR) for the differential expression analyses summarized in Data set 7. Format, column and row names as in Data set 7. Data set 11. Differential expression analyses across murine RNA-Seq sample groups: false discovery rates. As in Data set 10, but for mouse genes. Data set 12. Differential expression analyses across simian RNA-Seq sample groups: false discovery rates. As in Data set 10, but for chimpanzee genes. Data set 13. Quantification of alternative splicing events across human RNA-Seq samples. The file contains ‘percent spliced in’ (PSI) values computed by SUPPA (https://github.com/comprna/SUPPA) for annotated alternative splicing events (inferred from the transcript annotation of the human genome, Ensembl release 84; http://www.ensembl.org/). The format is a compressed (GZIP) tab-separated transcript-by-sample matrix. SUPPA-provided event identifiers and a combined Sequence Read Archive study/sample name identifier serve as row and column names, respectively. Data set 14. Quantification of alternative splicing events across murine RNA-Seq samples. As in Data set 13, but for mouse alternative splicing events. Data set 15. Differential splicing analyses across human RNA-Seq sample groups: differences in ‘percent spliced in’ (ΔPSI). The file contains ΔPSI values for human alternative splicing events (as in Data set 13). The RNA-Seq sample group contrasts are listed in Additional file 3 of the accompanying publication. Values were inferred by SUPPA’s diffSplice functionality (https://github.com/comprna/SUPPA). The format is a compressed (GZIP) tab-separated gene-by-comparison matrix. SUPPA event identifiers and a descriptive contrast identifier serve as row and column names, respectively. Data set 16. Differential splicing analyses across murine RNA-Seq sample groups: differences in ‘percent spliced in’ (ΔPSI). As in Data set 15, but for mouse alternative splicing events. Data set 17. Differential splicing analyses across human RNA-Seq sample groups: P values. The file contains P values for the differential splicing analysis of human alternative splicing events summarized in Data set 15. Format, column and row names as in Data set 15. Data set 18. Differential splicing analyses across murine RNA-Seq sample groups: P values. The file contains P values for the differential splicing analysis of mouse alternative splicing events summarized in Data set 16. Format, column and row names as in Data set 15. Data set 19. Transcript expression across murine RNA-Seq time course data: estimated read counts. As in Data set 2, but for the time course data generated for the accompanying publication. Data set 20. Transcript expression across murine RNA-Seq time course data: estimated transcript abundances. As in Data set 5, but for the time course data generated for the accompanying publication. Data set 21. Quantification of alternative splicing events across murine RNA-Seq time course data. As in Data set 14, but for the time course data generated for the accompanying publication.

数据集1：人类RNA测序（RNA-Seq）样本转录本表达：估算读取计数 本文件包含本研究使用的人类转录本与RNA-Seq样本的估算读取计数，由kallisto（https://pachterlab.github.io/kallisto/）生成（详见配套发表论文的补充材料2）。文件格式为经GZIP压缩的制表符分隔转录本-样本矩阵。行名与列名分别为Ensembl转录本标识符，以及组合式序列读取存档（Sequence Read Archive, SRA）研究/样本名称标识符。 数据集2：小鼠RNA测序（RNA-Seq）样本转录本表达：估算读取计数 与数据集1一致，但针对小鼠转录本。 数据集3：灵长类RNA测序（RNA-Seq）样本转录本表达：估算读取计数 与数据集1一致，但针对黑猩猩转录本。 数据集4：人类RNA测序（RNA-Seq）样本转录本表达：估算转录本丰度 与数据集1一致，但此处列出的是由kallisto估算的、以每百万转录本（transcripts per million, TPM）为单位的转录本丰度，而非读取计数。文件格式、行名与列名均与数据集1相同。 数据集5：小鼠RNA测序（RNA-Seq）样本转录本表达：估算转录本丰度 与数据集4一致，但针对小鼠转录本。 数据集6：灵长类RNA测序（RNA-Seq）样本转录本表达：估算转录本丰度 与数据集4一致，但针对黑猩猩转录本。 数据集7：人类RNA测序样本组的差异表达分析：对数折叠变化 本文件包含由edgeR（http://bioconductor.org/packages/release/bioc/html/edgeR.html）推导得到的人类基因对数折叠变化，对应配套发表论文补充材料3中列出的RNA-Seq样本组对比，格式为经GZIP压缩的制表符分隔基因-对比矩阵。行名与列名分别为Ensembl基因标识符，以及描述性对比标识符。 数据集8：小鼠RNA测序样本组的差异表达分析：对数折叠变化 与数据集7一致，但针对小鼠基因。 数据集9：灵长类RNA测序样本组的差异表达分析：对数折叠变化 与数据集7一致，但针对黑猩猩基因。 数据集10：人类RNA测序样本组的差异表达分析：错误发现率（false discovery rate, FDR） 本文件包含数据集7中汇总的人类差异表达分析的错误发现率（FDR）。文件格式、行名与列名均与数据集7相同。 数据集11：小鼠RNA测序样本组的差异表达分析：错误发现率 与数据集10一致，但针对小鼠基因。 数据集12：灵长类RNA测序样本组的差异表达分析：错误发现率 与数据集10一致，但针对黑猩猩基因。 数据集13：人类RNA测序样本可变剪接事件定量 本文件包含由SUPPA（https://github.com/comprna/SUPPA）计算得到的、针对注释可变剪接事件的剪接百分比（percent spliced in, PSI）值（可变剪接事件由人类基因组转录本注释推导而来，对应Ensembl发布84版；http://www.ensembl.org/）。文件格式为经GZIP压缩的制表符分隔转录本-样本矩阵。行名与列名分别为SUPPA提供的事件标识符，以及组合式序列读取存档（SRA）研究/样本名称标识符。 数据集14：小鼠RNA测序样本可变剪接事件定量 与数据集13一致，但针对小鼠可变剪接事件。 数据集15：人类RNA测序样本组的差异剪接分析：剪接百分比差值（ΔPSI） 本文件包含人类可变剪接事件的ΔPSI值（同数据集13），对应RNA-Seq样本组对比详见配套发表论文补充材料3。该数值由SUPPA的diffSplice功能（https://github.com/comprna/SUPPA）推导得到。文件格式为经GZIP压缩的制表符分隔基因-对比矩阵。行名与列名分别为SUPPA事件标识符，以及描述性对比标识符。 数据集16：小鼠RNA测序样本组的差异剪接分析：剪接百分比差值（ΔPSI） 与数据集15一致，但针对小鼠可变剪接事件。 数据集17：人类RNA测序样本组的差异剪接分析：P值 本文件包含数据集15中汇总的人类可变剪接事件差异剪接分析的P值。文件格式、行名与列名均与数据集15相同。 数据集18：小鼠RNA测序样本组的差异剪接分析：P值 本文件包含数据集16中汇总的小鼠可变剪接事件差异剪接分析的P值。文件格式、行名与列名均与数据集15相同。 数据集19：小鼠RNA测序时间序列数据的转录本表达：估算读取计数 与数据集2一致，但针对本配套发表论文生成的时间序列数据。 数据集20：小鼠RNA测序时间序列数据的转录本表达：估算转录本丰度 与数据集5一致，但针对本配套发表论文生成的时间序列数据。 数据集21：小鼠RNA测序时间序列数据的可变剪接事件定量 与数据集14一致，但针对本配套发表论文生成的时间序列数据。

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Zenodo

创建时间：

2019-01-15