# ChromHMM Tutorial
## 1. Prepare Histone Files for Cell Lines
>Where to find CHIP-Seq? (BED peaks file)
http://cistrome.org/db/#/
## 2. Creat cell-mark table
```script=1
#tab to separate
#cellmark15STATES.txt
GM12878 H3K27me3 45206_peaks.bed
GM12878 CTCF 45218_peaks.bed
CD4+T H3K4me1 8127_peaks.bed
CD4+T H3K4me1 36436_peaks.bed
```
## 3. BinarizeBed
```script=1
java -mx1600M -jar ChromHMM.jar BinarizeBed -center CHROMSIZES/hg38.txt data/bed cellmark15STATES.txt data/InputBinary
```
## 4. LearnModel
```script=1
java -mx1600M -jar ChromHMM.jar LearnModel data/InputBinary OUTPUTSAMPLE 15 hg38
```
## 5. Read segment.bed
Based on the states-model, this function can give each segment a state for a cell sequence.
```Rscript=1
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install(version = "3.13")
library("BiocManager")
BiocManager::install("rtracklayer")
library(rtracklayer)
seg<-import("./reco/runSTIAN0.0/proc/ChromHMM/OUTPUTSAMPLE/CD14+_15_segments.bed", format="bed")
seg
#write to a .csv file
write.csv(data.frame(seg),'OUTPATH/*.csv')
```
e.g. states for GM500_rep1:
## 6. States Heatmap
Input file: **`emission.txt`**
```Pythonscript=1
emission_matrix_15 = pd.read_csv("emissions_15.txt",sep='\t',index_col=0)
plt.subplots(figsize=(10, 10))
Emission_Matrix = sns.heatmap(emission_matrix_15, annot=True, vmax=1, square=True,cmap='YlOrRd')
Emission_Matrix.set_xticklabels(Emission_Matrix.get_xticklabels(),rotation=60)
Emission_Matrix.set_title("Chromatin State")
plt.show()
```
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