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README.md

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@@ -17,7 +17,15 @@ APEC requires Linux system (CentOS 7.3+ or Ubuntu 16.04+), as well as Python3 (3
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Bedtools: http://bedtools.readthedocs.io/en/latest/content/installation.html
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Meme 4.11.2: http://meme-suite.org/doc/download.html?man_type=web
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The files in **reference** folder are required for APEC. **But we didn't upload reference files to GitHub since they are too big. Users can download all reference files from http://galaxy.ustc.edu.cn:30803/APEC/reference/ or https://apec.oss-us-east-1.aliyuncs.com/APEC/reference/reference.zip**. The **reference** folder should contains the following files:
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The files in **reference** folder are required for APEC. But we didn't upload reference files to GitHub since they are too big. Users can download all reference files from one of the following websites:
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-|website
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-|-
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1|http://galaxy.ustc.edu.cn:30803/APEC/reference/ <br> (Due to server upgrade, this site will be temporarily unavailable from 2019-11-26 to 2019-11-30)
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2|https://apec.oss-us-east-1.aliyuncs.com/APEC/reference/reference.zip
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3|https://drive.google.com/drive/folders/1psK7za4KNJfqpigUaLMY3bWlqBHp1J5k?usp=sharing
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The **reference** folder should contains the following files:
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hg19_RefSeq_genes.gtf, hg19_chr.fa, hg19_chr.fa.fai,
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mm10_RefSeq_genes.gtf, mm10_chr.fa, mm10_chr.fa.fai,
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pip install APEC==1.1.0.11
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We suggest that users build a sub environment for APEC with **miniconda** or **anaconda**, as bedtools and meme suite (4.11.2) can be installed in conda enviroment too.
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We suggest that users build a python 3.6.8 environment for APEC with **miniconda** or **anaconda**, since APEC is dependent on specific versions of python packages (see README.md in examples folder), and bedtools and meme suite (4.11.2) can be installed in conda enviroment too.
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In Ipython, Jupyter-notebook or a python script, users can import packages of APEC by:
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### 3. Functions of APEC (step by step)
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#### Users can directly run example projects and scripts in **examples** folder to generate figures listed in our APEC paper.
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#### 3.1 Clustering by APEC
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Use the following codes to cluster cells by APEC algorithm:
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#### 1.2 Installation
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Users can simply install this part by copying the **code_v1.1.0** folder and **reference** folder into a same path. Users **must** run ***APEC_prepare_steps.sh*** directly in code_v1.1.0/, since each program will invoke the reference files automatically. The **reference** folder is required, **but we didn't upload reference files to GitHub since they are too big. Users can download all reference files from http://galaxy.ustc.edu.cn:30803/APEC/**. The **reference** folder should contains the following files:
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Users can simply install this part by copying the **code_v1.1.0** folder and **reference** folder into a same path. Users **must** run ***APEC_prepare_steps.sh*** directly in code_v1.1.0/, since each program will invoke the reference files automatically. The **reference** folder is required, but we didn't upload reference files to GitHub since they are too big. Users can download all reference files from one of the following sites:
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-|website
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-|-
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1|http://galaxy.ustc.edu.cn:30803/APEC/ <br> (Due to server upgrade, this site will be temporarily unavailable from 2019-11-26 to 2019-11-30)
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2|https://apec.oss-us-east-1.aliyuncs.com/APEC/reference_full.zip.001 <br> https://apec.oss-us-east-1.aliyuncs.com/APEC/reference_full.zip.002 <br> https://apec.oss-us-east-1.aliyuncs.com/APEC/reference_full.zip.003
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The **reference** folder should contains the following files:
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hg19_refseq_genes_TSS.txt, hg19_RefSeq_genes.gtf, hg19_blacklist.JDB.bed,
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hg19_chr.fa, hg19_chr.fa.fai, hg19.chrom.sizes,

examples/README.md

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**(1)** **project01** contains single cell samples from hematopoietic stem cell differentiation project (including HSC, MPP, CMP, GMP, MEP, LMPP, CLP, pDC, and UNK cells), from "Buenrostro, J.D. et al. Integrated Single-Cell Analysis Maps the Continuous Regulatory Landscape of Human Hematopoietic Differentiation. Cell 173, 1535-1548 e1516 (2018)". Users can run "python script_for_project01.py" to obtain Fig. 1b, 1d, 3c, and 3d of the APEC paper, and this figures will be placed in $project01/figure/ folder.
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#### If users want to entirely reproduce the figures in APEC paper, please create a new python 3.6.8 environment in anaconda/miniconda, and install APEC in the environment. APEC will install following packages in specific versions:
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**NOTE**: In "script_for_project01.py", "project01/" should be the path to the project01 folder; "../reference/" should be the **reference** folder. The reference folder should be filled with the following files downloaded from http://galaxy.ustc.edu.cn:30803/APEC/reference/:
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numpy==1.16.2
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scipy==1.0.0
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pandas==0.24.2
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matplotlib==3.0.3
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seaborn==0.9.0
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numba==0.43.1
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networkx==2.2
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python-louvain==0.11
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scikit-learn==0.20.0
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MulticoreTsne==0.1
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umap-learn==0.3.8
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rpy2==2.8.5
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hg19_RefSeq_genes.gtf, hg19_chr.fa, hg19_chr.fa.fai,
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mm10_RefSeq_genes.gtf, mm10_chr.fa, mm10_chr.fa.fai,
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JASPAR2018_CORE_vertebrates_non-redundant_pfms_meme.txt, tier1_markov1.norc.txt
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**(1)** **project01** contains single cell samples from hematopoietic stem cell differentiation project (including HSC, MPP, CMP, GMP, MEP, LMPP, CLP, pDC, and UNK cells), from "Buenrostro, J.D. et al. Integrated Single-Cell Analysis Maps the Continuous Regulatory Landscape of Human Hematopoietic Differentiation. Cell 173, 1535-1548 e1516 (2018)". Users can run **script_for_project01.py** to obtain Fig. 1b, 1d, 3c, and 3d of the APEC paper, as follows:
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python script_for_project01.py -p $project01 -r $reference
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where $project01 is the **project01** folder, and $reference is the **reference** folder. The output figures will be placed in $project01/figure/ folder.
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**NOTE**: Monocle is very sensitive to the input matrix. For example, when we use different versions of scipy (such as 1.0.0 and 1.2.1), the PCA matrices generated by sklearn will be slightly different (difference < 1.0e-7), and even this small difference will produce completely different shapes of trajectories by monocle. Different versions of many other related libraries/packages in python and R environment will also result in different shapes of trajectories.
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**(2)** **project02** contains single cell samples from the forebrain of adult mice, from "Preissl, S. et al. Single-nucleus analysis of accessible chromatin in developing mouse forebrain reveals cell-type-specific transcriptional regulation. Nat Neurosci 21, 432-439 (2018)". Users can run "python script_for_project02.py" to obtain Fig. 2a, 2b, and 2e of the APEC paper, and this figures will be placed in $project02/figure/ folder.
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**(2)** **project02** contains single cell samples from the forebrain of adult mice, from "Preissl, S. et al. Single-nucleus analysis of accessible chromatin in developing mouse forebrain reveals cell-type-specific transcriptional regulation. Nat Neurosci 21, 432-439 (2018)". Users can run **script_for_project02.py** to obtain Fig. 2a, 2b, and 2e of the APEC paper, as follows:
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python script_for_project02.py -p $project02 -r $reference
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where $project02 is the **project02** folder, and $reference is the **reference** folder. The output figures will be placed in $project02/figure/ folder.
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If users want to re-plot Fig. 2c, 2d, 2f, and 2g of the APEC paper, they can run **script_python_for_Figure_2c_2d.py** and **script_python_for_Figure_2f_2g.py** **after** the running of "script_for_project02.py", as follows:
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python script_python_for_Figure_2c_2d.py -p $project02
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python script_python_for_Figure_2f_2g.py -p $project02
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If users want to re-plot Fig. 2c, 2d, 2f, and 2g of the APEC paper, they can run "script_python_for_Figure_2c_2d.py" and "script_python_for_Figure_2f_2g.py" after the running of "script_for_project02.py". The output png files "cluster_vs_gene.png" is Fig. 2c, "cluster_pearson_corr.png" is Fig. 2d, "clusters_vs_Excl_types.png" is Fig. 2f, "clusters_vs_Int_types.png" is Fig. 2g.
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The output png files "cluster_vs_gene.png" is Fig. 2c, "cluster_pearson_corr.png" is Fig. 2d, "clusters_vs_Excl_types.png" is Fig. 2f, "clusters_vs_Int_types.png" is Fig. 2g. These output figures will be placed in the same folder as the two scripts.
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**NOTE**: In all these scripts, "project02/" should be the path to the project02 folder; "../reference/" should be the **reference** folder.
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**(3)** **project03** contains single cell samples of the leukemic stem and blast cells of two different patients (SU070 and SU353), from "Schep, A.N., Wu, B., Buenrostro, J.D. & Greenleaf, W.J. chromVAR: inferring transcription-factor-associated accessibility from single-cell epigenomic data. Nat Methods 14, 975-978 (2017)". Users can run **script_for_project03.py** to obtain Fig. S3b of the APEC paper, as follows:
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**(3)** **project03** contains single cell samples of the leukemic stem and blast cells of two different patients (SU070 and SU353), from "Schep, A.N., Wu, B., Buenrostro, J.D. & Greenleaf, W.J. chromVAR: inferring transcription-factor-associated accessibility from single-cell epigenomic data. Nat Methods 14, 975-978 (2017)". Users can run "python script_for_project03.py" to obtain Fig. S3b of the APEC paper.
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python script_for_project03.py -p $project03
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**NOTE**: In "script_for_project03.py", "project03/" should be the path to the project03 folder.
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where $project03 is the **project03** folder. The output figures will be placed in $project03/figure/ folder.

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