Updated content for version `1.7.0' (Anyone can add more request)

[Starlitnightly]

If you have any feature requests, you can reply within this issue or create a new issue.

• Added CellVote to annotate the cell type automatically
• Added dynamo to calculate the velocity and visualization
• Added the argument chunk_size of AUCell, automatic chunking when single-cell data is too large to prevent memory overflow. geneset_aucell_tmp,pathway_aucell_tmp,pathway_aucell_enrichment_tmp
• Added OmicVerse Agentic to help people analysis the data in local computer.
• Added GASTON to learn a topographic map of a tissue slice

[zuiluo1116]

1. Statistical evaluation of clustering. Like scSHC.
2. Comprehensive DEG among groups in one same cluster. Like Memento.
3. High dimensional distance-based disturbance analysis. Like scDist .
4. Tutorial convert Anndata object into seurat object. Including reductions, metadata and raw matrix.

[GhostInTheShellwjc]

1. A function can be added to convert counts to formats such as TPM according to species, with automatic determination of gene formats, similar to the "count2tpm" function in the IOBR package in R.

2. A TCGA downloader can be added, similar to the TGGAbiolinks package in R, which downloads data based on the name of the cancer, such as "TCGA-BRCA" (preferably using R function formatting to facilitate easy use for those accustomed to R).

3. After obtaining TCGA data using method 2, can functions be provided to facilitate one-click data integration, automatic recognition and conversion of gene names, and sample grouping (0X and 1X, i.e., normal and cancer groups, where in TCGA data, samples with values of 0X are tumors and 1X are normal)?

4. It seems that there is currently no function for sample grouping (0X and 1X, i.e., normal and cancer groups) in the TCGA module. Can groups be automatically added when using the TCGA module?

5. Can some new content be added to the TCGA tutorial? For example, tutorials on performing WGCNA, GSVA, GSEA, and differential analysis on TCGA data based on groupings (0X and 1X).

6. For beginners in single-cell analysis, the full process of each section is very much needed. Can the full process of each section be added for learning purposes?

7. GSEApy provides a GSVA function, but there is no GSVA method in omicverse. It is hoped that the GSVA method can be added to omicverse using the function from GSEApy.

8. In the next version of GSEApy (or the current nightly version), the GSEA module of GSEApy will allow GSEA data to be saved as a folder for analysis by GSEA software (Added tutorial of space crop and reference getting #289 in GSEApy). Can omicverse achieve the function of saving GSEA data as a folder through GSEApy?

9. Up- and down-regulation columns can be added to the differential analysis results.

10. It is hoped that a function for multifactorial differential analysis (like edgeR in R) can be provided.

11. It is hoped that the functions of pertpy, such as cellular composition analysis and cellular perturbation analysis, can be added to omicverse as soon as possible.

1.可以添加一个根据物种转换counts为tpm等格式的函数，基因格式可自动判定，类似于R中IOBR包的“count2tpm”

2.可以添加一个TCGA的下载器，类似R中TGGAbiolinks包，根据癌症的名称，如“TCGA-BRCA”，下载数据（最好可以用R中的函数格式，便于习惯用R的人简单上手）

3.在用2的方法获得TCGA数据后，可以提供函数便于提供一键整合数据、自动识别转换基因名、样本分组（0X和1X，也就是正常组和癌症组，TCGA的数据中sample的值如果是0X就是肿瘤，1X是正常）吗？

4.现在的TCGA module中似乎没有样本分组（0X和1X，也就是正常组和癌症组，TCGA的数据中sample的值如果是0X就是肿瘤，1X是正常）的函数，可以在使用TCGA模块时自动添加分组吗

5.可以在TCGA教程中添加一些新内容吗？例如对TCGA数据，根据分组（0X和1X），进行WGCNA、GSVA、GSEA和差异分析的教程

6.对于单细胞分析初学者来说，每一个板块的全流程是非常需要的，可以添加每一个板块的全流程以便学习

7.GSEApy提供了GSVA的函数，但是omicverse中没有GSVA方法，希望GSVA方法能用GSEApy中的函数加入omicverse

8.在下一个GSEApy版本中（或者是现在的nightly版本），GSEApy的GSEA模块将允许GSEA的数据保存为文件夹以便GSEA软件分析（2 in #289 in GSEApy），omicverse是否可以通过GSEApy来实现保存GSEA数据为文件夹的功能？

9.可以在差异分析结果中添加上下调列

10.希望有一个多因素差异分析的函数（就像R中的edgeR）

11.希望细胞组成分析和细胞扰动分析等pertpy的功能可以尽快加入omicverse

[GhostInTheShellwjc]

1.An Api doc for many of main func is required.
2.In ov.pp.qc,can we identify the mitochondrion genes automatically? Sometimes,we may forget to change the MT_startwith when we process statistic from Mus musculus.
3.Sometimes，it is hard for starters to find where the file is when we use the downloader,especially in Windows.Can we have an option in downloader to download files in a specific location?
4. #245
5.It is too difficult to ID mapping because we need two functions to complete it.Can the annotation files be downloaded when we install the package?

1.对于大部分主要的函数，需要一个API文档
2.在ov.pp.qc中，需要一个自动检测器自动确定线粒体基因的开头，防止做小鼠数据的时候忘了改MT的开头而未过滤基因
3.对新人来说，有时很难找到下载器下载文件的位置，特别是在Windows中，对此需要在downloader中加一个参数指定下载的位置
4.看 #245
5.现在的基因名转换需要两步，有点麻烦。最好可以把ID映射文件内置入包，以便安装包时就下载完成

[GhostInTheShellwjc]

1.scVI enables model hyperparameter tuning by scVI.autotune.I think it is awesome if we can have the feature in functions which use scVI,or it can be added into deep learning methods which is available to hyperparameter tunning in omicverse.
2.cellassign is a dl method to annotate cells by database like cellmarker，which can be added.
（https://www.nature.com/articles/s41592-019-0529-1）
3.add denoising param in ov.pp.qc.
4.add MrVI in scVI to analyzing multi-sample single-cell RNA-seq data.
5.add function which can score TF activity by database when we input genes.
6.scATAC-seq analysis tools
7.scBs-seq analysis tools
8.multimodal analysis tools,such as CITE-seq analysis