---
# System prepended metadata

title: LAB 01

---

# LAB 01
bi278 lab #1

Course Unix environment
1.1 Connect to the bi278 Unix environment

```
ssh colbyid@bi278
exit
```
1.2 Navigate and find your colbyhome
Here I first tried to 	‘print	working	directory’:

```
pwd #shows your current position
```
and also check what are the files in this directory:
```
ls # this lists everything in your current working directory
```
then I tried to use flags	-lh to	ask	for	
a	more	detailed	list	of	directory	contents:
```
ls -lh 
```

Then I learned how to back to home after I cd into personal/xsi25
```
cd ~
```
1.3 Organize your files
First I created two new directories
```
mkdir lab_01a lab_01b
```
And then I copy	over	the	entire	contents	of	this	first lab	folder (=directory) using	a command	that	says	to	copy	all	the	
files	(*)	in	this	week’s	lab	folder	to lab_01a: 
```
cp /courses/bi278/Course_Materials/lab_01a/* ./lab_01a
```
Then I cd into lab_01a and check the files in this directory:
```
cd lab_01a
ls
```
And I tried different files organization methods:
```
#remove this file from this directory
rm raw_preference_f1_control.txt

#print the content of this file in terminal
cat raw_preference_prelim_ca.txt 

#to view the content of this file one screen at a time
less raw_preference_prelim_ca.txt
```

I also tried to look up the options of one command:
```
man less #use q to exist
```

2. Collect genome statistics using a Unix script
2.1 Get basic information about genomes
First I cd into the lab material directory and check the files in this directory:
```
cd /courses/bi278/Course_Materials/lab_01b 
ls
```
And then I checked these files one by one. For example:
```
grep ">" /courses/bi278/Course_Materials/lab_01b/GCF_000756045.1_ASM75604v1_genomic.fna
```
The result is:
>NZ_CP008760.1 Paraburkholderia xenovorans LB400 chromosome 1, complete sequence
>NZ_CP008762.1 Paraburkholderia xenovorans LB400 chromosome 2, complete sequence
>NZ_CP008761.1 Paraburkholderia xenovorans LB400 chromosome 3, complete sequence

Then I tried these following methods:
```
grep ">" PATH/test.fa
#->test

grep -v ">" PATH/test.fa
#-> ACTGGCTCAGTTACTGGCACTGCGCCCGCATATCCGTAACGAAGTGCGTCGTGTACTGACGAGCGGCGACATAGCCCTCG
TCCTGCTCGACTGGACCCTCAACGGGACACTACCGGACGGCCGGGAGCACGAGGAGCGCGGTACCGCTACACAGGTCATG
GAAAGGGGCCGCGACGGTGGGTGGAAGCTGCGGATCTCCAATCCGTCCGGGCTGAACTGAATGGCATCGAAGGTGCGCCG
CCGTAAACGACCGGCAAGGATGTTCAAGCTGCTCCTGTCCGGCTCGAGCTTGATGCCGGCATCGCCGGGACATCGAACTG
CCCCGCGATGCGCGGCCACTGGCGCCAGGCAATTGCCTTCCCGGAAATCTGGTTGCGTGTGACTGCCCTGGCATATCTGA

grep -v ">" PATH/test.fa | tr -d -c GCgc
#->CGGCCGCGGCCGCGCCCGCCCGCGGGCGCGGCGCGGCGGCGCGCCCCGCCGCCGCGGCCCCCGGGCCCCGGCGGCCGGGGCCGGGGCGCGGCCGCCCGGCGGGGGGCCGCGCGGGGGGGGCGCGGCCCCCGCCGGGCGCGGGCCGGGGCGCCGCCGCGCCGGCGGGCGCGCCCGCCGGCCGGCGGCCGGCCGCCGGGCCGCGCCCCGCGGCGCGGCCCGGCGCCGGCGCCCCCGGCGGGCGGGCGCCCGGCCG

grep -v ">" PATH/test.fa | tr -d -c GCgc | wc -c
#->253

awk 'BEGIN {print (253/400)}'
#->0.6325
```
2.2. WRITE	AND	RUN	A	UNIX	SCRIPT	TO	AUTOMATE	YOUR	COLLECTION	OF	GENOME	STATISTICS
 First I type in nano and I got to an	editor	within	the	Unix	shell and use contorl + x to exist the editor
 
 In nano, I calculate the base pair.
 `#!/bin/bash
grep -v ">" /courses/bi278/Course_Materials/lab_01b/test.fa | tr -d -c GCgc | wc -c
grep -v ">" /courses/bi278/Course_Materials/lab_01b/test.fa | tr -d -c ATatGCgc | wc -c`


To check each oragnis one by one, I wrote codes in nano as:
```
grep -v ">" $1
grep -v ">" $1 | tr -d -c ATatGCgc | wc
grep -v ">" $1 | tr -d -c GCgc | wc
```

The form:

| oragnism      | strain       | contig count | cenome size | gc%  |
| ------------- | ------------ | ------------ | ----------- | ---- |
| P.agricolaris | baqs159      |        2      |     8721420        |  0.62(5375334)    |
| P.	bonniea    | bbqs859      |     2         |      4098182       |    0.59(2406657)  |
| P.	bonniea    | bbqs359      |      2        |    4009285         |  0.59(2357500)    |
| P.	bonniea    | bhqs433       |      2        |     4013203        |0.59(2359065)|
| P.	fungorum   | ATCC BAA-463 |      4        |      9058983       |   0.62(5593928)   |
| P.hayleyella  | bhqs11       |      2        |     4125700        |   0.59(2444079)   |
| P.	hayleyella | BHQS155      |      2        |     4118676        |  0.59(2439862)    |
| P.	hayleyella | BHQS171      |      35        |     4088457        |0.59(2421259)|
| P.	hayleyella | bhqs21       |       35       |     4088512        |   0.59(2421281)   |
| P.	hayleyella | bhqs22       |       45       |    4084312 |  0.59(2418627)  |
| P.	hayleyella | bhqs23       |       36      |      4090401       |   0.59(2422298)  |
| P.	hayleyella | bhqs530      |       2       |     4118722        |   0.59(2439957)   |
|    P.	hayleyella           |   bhqs69           |      2        |      4125852       |   0.59(2444184)   |
| P.	sprentiae  |      WSM5005        |   5           |     7829542        | 0.63(4948909)     |
| P.	terrae  |    DSM17804          |  4            |     10062489        | 0.62(6230535)     |
| P.	xenovorans    |    LB400          | 3         | 9702951        | 0.63(6077288) |


 
 