some Vi shortcuts

 Copy and paste one line

With the cursor at your desired line press yy. Press p wherever you like and the line will be pasted below the line you are on. The y stands for “yank”.

Cut and paste one line

With the cursor at your desired line press dd. Press p wherever you like and the line will be pasted below the line you are on. The d stands for “delete”.

Copy and paste multiple lines

With the cursor at your desired line press nyy, where n is the number of lines down you want to copy. So if you want to copy 2 lines, press 2yy. To paste press p and the number of lines copied will be pasted below the line you are on now.

Cut and paste multiple lines

With the cursor at your desired line press ndd, where n is the number of lines down you want to copy. So if you want to copy 2 lines, press 2dd. To paste press p and the number of lines copied will be pasted below the line you are on now.

Copy and paste one word in a line

Move the cursor to your desired word. It can be any part of the word and press yiw, which stands for yank inner word. Press p and your word will be pasted after the cursor.

Cut and paste one word in a line

Move the cursor to your desired word. It can be any part of the word and press diw, which stands for delete inner word. Press p and your word will be pasted after the cursor.

Copy and paste part of a word or line

Mover the cursor to your desired word. Press v, which will enter you into visual mode. Move your cursor around to highlight the words or parts of words you want to copy then press y. Press p and your selection will be pasted after the cursor.

Cut and paste part of a word or line

Mover the cursor to your desired word. Press v, which will enter you into visual mode. Move your cursor around to highlight the words or parts of words you want to cut then press d. Press p and your selection will be pasted after the cursor.

Some other commands

I think we get the pattern. Here are some other commands:

x   deletes/cuts the single character under the cursor
Nx  deletes/cuts N characters starting with the character under the cursor
dw  deletes/cuts the rest of the word the cursor is on starting with the character under the cursor
dNW deletes/cuts the N words starting with the character under the cursor
D   Delete the remainder of the line starting with the character under the cursor.

If you swicth d or x with y you get the same effect but with a copy instead of a cut. Note that Y copys the whole line not the remainder.

Ref: http://ahmed.amayem.com/copy-or-cut-and-paste-in-vi-linux-tutorial/

managing multiple SSH keys

 Let's say you have already generated an SSH key for GitHub, as instructed here:

https://docs.github.com/en/free-pro-team@latest/github/authenticating-to-github/generating-a-new-ssh-key-and-adding-it-to-the-ssh-agent

Now your .ssh folder will be like this:

PHS015945:.ssh xd010$ ll

-rw-r--r--  1 xd010  staff   165B Dec  9 23:21 config

-rw-------  1 xd010  staff   411B Dec  9 23:12 id_ed25519

-rw-r--r--  1 xd010  staff   100B Dec  9 23:12 id_ed25519.pub

where config file will be like:

Host *

  AddKeysToAgent yes

  UseKeychain yes

  IdentityFile ~/.ssh/id_ed25519

Now, you want to ssh to your HPC server without a password. You will follow instructions like this http://www.linuxproblem.org/art_9.html, e.g. 

a@A:~> ssh-keygen -t rsa
Generating public/private rsa key pair.
Enter file in which to save the key (/home/a/.ssh/id_rsa): 
Created directory '/home/a/.ssh'.
Enter passphrase (empty for no passphrase): 
Enter same passphrase again: 
Your identification has been saved in /home/a/.ssh/id_rsa.
Your public key has been saved in /home/a/.ssh/id_rsa.pub.
The key fingerprint is:
3e:4f:05:79:3a:9f:96:7c:3b:ad:e9:58:37:bc:37:e4 a@A

Now append a's new public key to b@B:.ssh/authorized_keys and enter b's password one last time:

a@A:~> cat .ssh/id_rsa.pub | ssh b@B 'cat >> .ssh/authorized_keys'
b@B's password: 

You will find that you are still asked to enter the password when you want to ssh to your HPC. Where's the problem?

Conda - A must-have for bioinformatician

As a bioinformatician, when you are given a new system (Mac, HPC, or any Linux environment), the first thing to do is probably to configure your work environment, install required tools, etc. 

Here is what I did for the new Mac:

1. This step is optional. Apple changed to default shell to zsh since the last OS. If you like bash, you can change the default zsh shell from bash:

chsh -s /bin/bash

2. Install Miniconda. Miniconda is a free minimal installer for conda, incl. only the basic ones (e.g. conda, python, zlib, etc). If you are under Linux, download the one for Linux. 

wget https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh

bash Miniconda3-latest-MacOSX-x86_64.sh

3. Install commonly used tools with bioconda:

# update bash (the one coming with MacOS is too old)

conda install -c conda-forge bash

# samtools etc.

conda install -c bioconda samtools plink plink2

# UCSC Kent Utilities etc.

conda install -c bioconda ucsc-bedgraphtobigwig ucsc-wigtobigwig ucsc-liftover ucsc-bigwigsummary

# GNU utils etc.

conda install -c conda-forge coreutils gawk wget gzip datamash parallel make readline sed

# R and R package etc.

conda install -c r r-base

conda install -c r r-essentials

conda install -c r r-tidyverse

# Google cloud gsutil

conda install -c conda-forge gsutil 

Life is much easier after conda!

Be careful of "sort -k1,1 -k2,2n -u"

When you attempted to sort and extract the unique genomic regions using "sort -k1,1 -k2,2n -u", you might make a mistake by missing the region with the same chr and start, but different end position.

The right way should be  "sort -k1,1 -k2,2n -k3,3n -u" or  "sort -k1,1 -k2,2n | sort -u"

Note on the case-insensitive file system in Mac OS

I recently noticed that when my script wrote a file (e.g. condition_pd_vs_hc.pdf) into the Linux server disk mounted in my Mac. It will override another existing file although with different file name (e.g. CONDITION_PD_vs_HC.pdf). It turned out that my Mac OS filesystem is HFS+ and the disk was formated as "Mac OS Extended" (by default). Unlike "Mac OS Extended (Case-sensitive, Journaled)", "Mac OS Extended" is not case-sensitive, but case-presertive. "This means that the file system will consider foo and FoO to be the same, but when you create a new file it will remember which letters where capitalized and which were not." (quoted from https://apple.stackexchange.com/a/22304).

I totally don't get the point to have a case-insensitive but case-preserving file system.  Bummer!

TERM_SWAP: job killed after reaching LSF swap usage limit.

When your job was killed due to this error, it means you've exceeded the swap usage set for the queue.

bsub -v option can set the limit:

   -v swap_limit

               Set the total process virtual memory limit to

               swap_limit for the whole job. The default is

               no limit. Exceeding the limit causes the job to

               terminate.

               By default, the limit is specified in KB. Use

               LSF_UNIT_FOR_LIMITS in lsf.conf to specify a

               larger unit for the limit (MB, GB, TB, PB, or EB).

Without administrator permission, one cannot change the lsf.conf. 

So as a user what you can do is to switch to use a different queue with larger swap limit. Here is the command to check the limit for a queue, e.g. 

$bqueues -l normal | grep -A 1 SWAP
CORELIMIT MEMLIMIT SWAPLIMIT
0 M 8 G 12 G


Here is what I got from our cluster:

$ for i in `bqueues | grep -v QUEUE_NAME | cut -f1 -d' '`; do echo $i; bqueues -l $i | grep -A 1 SWAP; done

interact

 MEMLIMIT SWAPLIMIT

     39 G      47 G 

interact-big

 MEMLIMIT SWAPLIMIT

    488 G     586 G 

gpu

 CORELIMIT MEMLIMIT SWAPLIMIT

      0 M      23 G      29 G 

elephant

 CORELIMIT MEMLIMIT SWAPLIMIT

      0 M       2 T       2 T 

big-multi

 CORELIMIT MEMLIMIT SWAPLIMIT

      0 M     498 G     500 G 

big

 CORELIMIT MEMLIMIT SWAPLIMIT

      0 M     498 G     500 G 

normal

 CORELIMIT MEMLIMIT SWAPLIMIT

      0 M       8 G      12 G 

medium

 CORELIMIT MEMLIMIT SWAPLIMIT

      0 M       9 G      12 G 

vshort

 CORELIMIT MEMLIMIT SWAPLIMIT

      0 M       8 G      10 G 

short

 CORELIMIT MEMLIMIT SWAPLIMIT

      0 M       8 G      10 G 

long

 CORELIMIT MEMLIMIT SWAPLIMIT

      0 M       9 G      12 G 

vlong

 CORELIMIT MEMLIMIT SWAPLIMIT

      0 M       8 G      12 G 

mpi-short

 CORELIMIT MEMLIMIT SWAPLIMIT

      0 M       8 G      10 G 

mpi-ib

 CORELIMIT MEMLIMIT SWAPLIMIT

      0 M     248 G     254 G 

aaa-chunk

 CORELIMIT MEMLIMIT SWAPLIMIT

      0 M     117 G     125 G 

pcpgmwgs

matlab

 CORELIMIT MEMLIMIT SWAPLIMIT

      0 M     250 G     250 G 

matlabdce

 CORELIMIT MEMLIMIT SWAPLIMIT

      0 M     250 G     250 G 

matlabdce-short

 CORELIMIT MEMLIMIT SWAPLIMIT

      0 M       4 G     250 G 

defaultlow

 CORELIMIT MEMLIMIT SWAPLIMIT

      0 M       8 G      12 G 

pcpgm

filemove

 CORELIMIT MEMLIMIT SWAPLIMIT

      0 M      12 G      12 G 

rerunnable

rerunnable-big

Download all KEGG pathway KGML files for SPIA analysis

Most people know the KEGG pathway, but not everyone knows that it costs at least $2000 to subscribe to its database. If you want to save the cost a bit, you can manually download the KEGG pathway KGML files and install them in SPIA. Here I have a workaround to download all KEGG pathway files using their REST API.
## Claim: this is my personal trick. I recommend people subscribe to their KEGG FTP download to support the authors.

# change folder to the folder where your SPIA installed, for example in my Mac
cd /Library/Frameworks/R.framework/Versions/4.0/Resources/library/SPIA
# download all XML and png files for all human pathway
curl -s http://rest.kegg.jp/list/pathway/hsa | awk '{split($1,a,":"); print "curl -s http://rest.kegg.jp/get/"a[2]"/kgml -o extdata/keggxml/hsa/"a[2]".xml"}' | bash

curl -s http://rest.kegg.jp/list/pathway/hsa | awk '{split($1,a,":"); print "curl -s http://rest.kegg.jp/get/"a[2]"/image -o extdata/keggxml/hsa/"a[2]".png"}' | bash

# then switch to R console
setwd("/Library/Frameworks/R.framework/Versions/3.4/Resources/library/SPIA")
library(SPIA)
makeSPIAdata(kgml.path=system.file("extdata/keggxml/hsa",package="SPIA"),organism="hsa",out.path="./extdata")

Done!

Brace expansion

Let's say I want to download the chromHMM result for all brain tissues from Roadmap project. The brain tissues are numbers from E067-E074, E081, and E082 according to Anshul's table: https://docs.google.com/spreadsheets/d/1yikGx4MsO9Ei36b64yOy9Vb6oPC5IBGlFbYEt-N6gOM/edit#gid=15

So, what's the wildcard to match all the ten brain tissues? E067-E074, E081, and E082

Here is the trick:

wget http://egg2.wustl.edu/roadmap/data/byFileType/chromhmmSegmentations/ChmmModels/coreMarks/jointModel/final/E0{{67..74},81,81}_15_coreMarks_segments.bed

There are two types of brace expansion in Bash:
1. String list: {string1,string2,...,stringN}
2. Range list: {<START>..<END>}

You can combine them or nest them, for example
{{67..74},81,81} ==> 67,68,69,70,71,72,73,74,81,82
{A..C}{0..2}  ==> A0, B0, C0, A1, B1, C1, A2, B2, C2
{{A..C},{0..2}}  ==> A, B, C, 0, 1, 2

In the new Bash 4.0, you can even do more, for example
- padding them, e.g. {0001..5} ==> 0001 0002 0003 0004 0005
- specify an increment using ranges, e.g. {1..10..2} ==> 1 3 5 7 9; {a..z..3} ==> a d g j m p s v y
- Using a prefix: 0{1..5} ==> 01 02 03 04 05
- or postfix: ---{A..E}---  ==> ---A--- ---B--- ---C--- ---D--- ---E---


Anyone understand the fun of code below:

function braceify {
    [[ $1 == +([[:digit:]]) ]] || return
    typeset -a a
    read -ra a < <(factor "$1")
    eval "echo $(printf '{$(printf ,%%.s {1..%s})}' "${a[@]:1}")"
}

printf 'eval printf "$arg"%s' "$(braceify 1000000)"

See explain here: http://wiki.bash-hackers.org/syntax/expansion/brace

remove and disable .DS_Store in mounted disk

Do you see this when you want to extend your path by typing the TAB key? What are those .DS_Store files?

They are generated by MacOS (see [1] for detail). Because I mount my remote disk via SMB, MacOS Finder will generate such a configure file whenever you open the mounted folder in Finder locally.

It's harmless to remove those files [2].

How to remove those already in your folder? [3]
cd FOLDER_YOU_WANT_TO_CLEAN_DS_STORE
find ./ -name ".DS_Store" -depth -exec rm {} \;

How to stop generating .DS_Store file on Network drive? [4]

defaults write com.apple.desktopservices DSDontWriteNetworkStores -boolean true

References:

1. https://en.wikipedia.org/wiki/.DS_Store
2. http://apple.stackexchange.com/questions/69467/consequences-of-deleting-ds-store
3. https://helpx.adobe.com/dreamweaver/kb/remove-ds-store-files-mac.html
4. https://software.com/mac/tweaks/disable-ds-store-files-on-network-drives

My 15 practical tips for a bioinformatician

Tips below are based on the lessons I learnt from making mistakes during my years of research. It's purely personal opinion. Order doesn't mean anything. If you think I should include something else, please comment below.

1. Always set a seed number when you run tools with random option, e.g. bedtools shuffle, random etc.; You (or your boss in a day) want your work reproducible. 
2. Set your own temporary folder (via --tmp, $TMPDIR etc., depending on your program). By default, many tools, e.g. sort, use the system /tmp as temporary folder, which may have limited quote that is not enough for your big NGS data. 
3. Always use a valid name for your variables, column and rows of data frame. Otherwise, it can bring up unexpected problem, e.g. a '-' in the name will be transferred to '.' in R unless you specify check.names=F.
4. Always make a README file for the folder of your data; For why and how, read this: http://stackoverflow.com/questions/2304863/how-to-write-a-good-readme
5. Always comment your code properly, for yourself and for others, as you very likely will read your ugly code again.
6. Always backup your code timely, using github, svn, Time Machine, or simply copy/paste whatever.
7. Always clean up the intermediate or unnecessary data, as you can easily shock your boss and yourself by generating so much data (and perhaps most of them are useless). 
8. Don't save into *.sam if you can use *.bam. Always zip your fastq (and other large plain files) as much as you. This applies to other file format if you can use the compressed one. As you cannot imagine how much data (aka "digital garbage") you will generate soon.
9. Using parallel as much as you can, e.g. using "LC_ALL=C sort --parallel=24 --buffer-size=5G" for sorting (https://www.biostars.org/p/66927/), as multi-core CPU/GPU is common nowaday.
10. When a project is completed, remember to clean up your project folder, incl. removing the unnecessary code/data/intermediate files, and burn a CD or host it somewhere in cloud for the project. You never know when you, your boss or your collaborators will need the data again;
11. Make your code sustainable as possible as you can. Remember the 3 major features of OOP: Inheritance, Encapsulation, Polymorphism. (URL)
12. When you learn some tips from others by Google search, remember to list the URL for future reference and also for acknowledging others' credit. This applies to this post, of course :)
13. Keep learning, otherwise you will be out soon. Just like the rapid development of NGS techniques, computing skills are also evolving quickly. Always catch up with the new skills/tools/techniques.
14. When you learn some tips from others, remember to share something you learned to the community as well, as that's how the community grows healthily. 
15. Last but not least, stand up and move around after sitting for 1-2 hours. This is especially important for us bioinformaticians who usually sit in front of computer for hours. Only good health can last your career long. More reading: https://www.washingtonpost.com/news/wonk/wp/2015/06/02/medical-researchers-have-figured-out-how-much-time-is-okay-to-spend-sitting-each-day/

Continuous tab in indentation could cause problem

When I tested the following code in terminal and got an error at the 2nd echo. It asked to list all files in the current folder, e.g. “Display all 148 possibilities? (y or n)”, rather than moving forwards. I cannot tell any error in the code.

for i in 1 2 3 4 5
do
    echo $i
    for j in eRNA promoter exon random
    do
        echo $j
    done
done

I figure it out when I display all the white characters, as shown below:

Do you see the difference?

The “working” code, which I copied from the Linux document (http://www.tldp.org/LDP/abs/html/nestedloops.html) has different characters for the nested indentation (-> .. means a tab and two spaces) than the two tabs in the “not working” part (which I typed in Rstudio). I realized that it’s because the tab-autocompletion feature in Linux. Pressing tab a second time will tell the shell to provide a list of matching files.

To avoid the problem, simply click on the “Insert spaces for tab” option in your editor. I used Rstudio, here is where you can find the option:

A parallel and fast way to download multiple files

We can write a short script to download multiple files easily in command, e..g

for i in X Y Z; do wget http://www.site.com/folder/$i.url; done

If we want them to run in background (so that in a pseudo-parallel way), we can use -b option for wget.

But this is still not fast enough, and the parallel with wget -b won't give me any notice once it's done.

Here is my solution: axel + parallel

parallel -a urls.file axel

Let's say I want to download all brain sample bigwig files of H3K4me1 marks from the Roadmap Epigenomics project. Here is the code:

mark=H3K4me1
> url.$mark # to generate an empty file
for i in E071 E074 E068 E069 E072 E067 E073 E070 E082 E081;
do 
  echo http://egg2.wustl.edu/roadmap/data/byFileType/signal/consolidated/macs2signal/pval/$i-$mark.pval.signal.bigwig >> url.$mark
done
parallel -a url.$mark axel -n 5 

Regarding what's axel and how fast it is comparing to wget, please refer to this link: http://www.cyberciti.biz/tips/download-accelerator-for-linux-command-line-tools.html

use getline to capture system command output in awk

I just learnt this today: awk also has its pipe (|) and getline, just like unix. If I want to call a system command in awk and capture its output (Note: system() won't work as it only return the exit status), I can use pipe the output to getline. 

For example,

$cat > test.txt

aa bb cc

11 22 33

44 55 cc

$awk 'BEGIN{cmd="grep cc test.txt | sort -k1,1 | head -n1 | cut -f2 -d\" \""; cmd | getline a; print a}'

55

or 

$awk 'BEGIN{cmd="grep cc test.txt | sort -k1,1 | head -n1 | cut -f2 -d\" \""; system(cmd);}'

55

Note that if only use cmd, it won't print out anything, because cmd itself won't switch to console (unlike system). 

$awk 'BEGIN{cmd="grep cc test.txt | sort -k1,1 | head -n1 | cut -f2 -d\" \""; cmd;}'

If you want to output the multiple lines and process them in awk, you can do

$awk 'BEGIN{cmd="grep cc test.txt | sort -k1,1 | cut -f2 -d\" \""; while( (cmd | getline a) >0) print a;}'

55

bb

Reference: http://stackoverflow.com/questions/1960895/awk-assigning-system-commands-output-to-variable

Be cautious of using grep --colour=always

I noticed that grep --colour=always can embed additional code (for coloring, for example, ^[[01;31m^[[K    ^[[m^[[K) in your text, which could lead downstream confusion. Here is one such example:
https://stackoverflow.com/questions/18315380/invisible-0131-number-in-bash

$ echo 1 2 3 | grep 2

1 2 3

$ echo 1 2 3 | grep 2 | cat -v

1 2 3

$ echo 1 2 3 | grep --colour=always 2 

1 2 3

$ echo 1 2 3 | grep --colour=always 2 | cat -v

1 ^[[01;31m^[[K2^[[m^[[K 3

See my answer for more detail.

The solution is to use --colour=autoor not use the --colour option at all.

$ echo 1 2 3 | grep --colour=auto 2 

1 2 3

$ echo 1 2 3 | grep --colour=auto 2 | cat -v

1 2 3

Check your .bashrc to see if you set alias grep='grep --colour=always' like I did.

Which version should I install? 32 bit or 64 bit? Ubuntu or CentOS?

I was posting two relevant articles on this topic:

Unix vs. Linux (http://onetipperday.blogspot.com/2014/07/unix-vs-linux.html)
Which version of tools I should install? i386 vs. x86_64, and 32bit vs. 64bit kernel (http://onetipperday.blogspot.com/2013/02/software-vs-hardware-i386-vs-x8664-and.html)

However, this can still be confusing sometimes... for example, when you visit the SRA toolkit download page: http://trace.ncbi.nlm.nih.gov/Traces/sra/sra.cgi?view=software

OK. Here is the short answer.

1. How to tell my CPU architecture is 32 bit or 64 bit?

$ uname -aIf the output is i386 or i586, it's 32 bit. If it's x86_64, it's 64 bit.

Ref: http://www.cyberciti.biz/faq/linux-how-to-find-if-processor-is-64-bit-or-not/

2. How to tell my OS (operation system) kernel is 32 bit or 64 bit?

Note that the OS kernel can be different from the above hardware architecture. Usually the OS changes version following the update of hardware, but the 32bit version can work in a 64bit machine (not the other way around), so it might not be consistent. The Macbook Pro I am using is running a 32-bit kernel on a 64-bit processor (see my previous post). 

3. How to tell which OS I am using? CentOS or Ubuntu?

In my case, I used:

$ ls -d /etc/[A-Za-z]*[_-][rv]e[lr]* | grep -v "lsb" | cut -d'/' -f3 | cut -d'-' -f1 | cut -d'_' -f1

it returns redhat, which is part of CentOS now.

## For more detail, please refer terdon's answer in http://askubuntu.com/a/459425

grep -wfF list.txt input.txt

If you are just greping the list from a file, and your list are store in a file, let's say, list.txt, then you can always do grep -wf list.txt input.txt

When list.txt is huge, "-F" will be much faster.

Extracted from https://www.biostars.org/p/134753/#134871

"search and highlight" in linux command line

Is there a way to display a text file in command line, but highlight the matches?

Actually there is a pretty neat tip from jacksonh:

grep --color -E "test|$" yourfile

What we're doing here is matching against the $ pattern and the test pattern, obviously $doesn't have anything to colourize so only the test pattern gets color. The -E just turns on extended regex matching.

external variables for GNU Parallel command

I was trying to use an externally defined variable within the parallel command, but it's failed. For example,

$ echo -e "intergenic\nintrons\nexons\n5utr\n3utr" | parallel 'echo {} $ANNOTATION/{}.bed'

3utr /3utr.bed

5utr /5utr.bed

intergenic /intergenic.bed

introns /introns.bed

exons /exons.bed

$ANNOTATION is not correctly read. One workout I found is to export the variable before the parallel, e.g. 

export ANNOTATION=/reference/annotation

transpose a tab-delimited file in command line

Very often we need to transpose a tab-delimited file, e.g. rows --> columns and columns --> rows. For example, I have a SNP file like below, each row is SNP and each column is a sample:

$ cat SNP.txt
id Sam_01 Sam_02 Sam_03 Sam_04 Sam_05
Snp_01 2 0 2 0 2
Snp_02 0 1 1 2 2
Snp_03 1 0 1 0 1
Snp_04 0 1 2 2 2
Snp_05 1 1 2 1 1
Snp_06 2 2 2 1 1
Snp_07 1 1 2 2 0
Snp_08 1 0 1 0 1
Snp_09 2 1 2 2 0

I want to convert it to the following format:

id Snp_01 Snp_02 Snp_03 Snp_04 Snp_05 Snp_06 Snp_07 Snp_08 Snp_09

Sam_01 2 0 1 0 1 2 1 1 2 

Sam_02 0 1 0 1 1 2 1 0 1 

Sam_03 2 1 1 2 2 2 2 1 2 

Sam_04 0 2 0 2 1 1 2 0 2 

Sam_05 2 2 1 2 1 1 0 1 0

We can easily do this in R (e.g.. t(df)), but actually there are also a couple available tools in linux. Here are two I used:

1. rowsToCols from Jim Kent's utility
wget http://hgdownload.soe.ucsc.edu/admin/exe/linux.x86_64/rowsToCols
cat SNP.txt | rowsToCols stdin stdout

2. datamash from GNU
cat SNP.txt | datamash transpose

btw, datamash is really a neat command with many functions, like your swiss-knife for small daily tasks for data scientist. Here is its example page on GNU:
http://www.gnu.org/software/datamash/examples/

Unix vs. Linux

I'd love to share a nice article about the difference between Linux and Unix (Believe me, not everyone knows the difference):
http://www.cyberciti.biz/faq/what-is-the-difference-between-linux-and-unix/

From there (also from Wiki), I learned that

• Linux is just a kernel while Unix is a complete operating system. 
• Unix was originally developed by Dennis Ritchie (also the creator of the C programming language) and Ken Thompson from Bell lab around 1970s, while the Linux kernel was written by a Finnish CS student Linus Torvalds in 1991. 
• A typical Linux distribution (or GNU/Linux as Free Software Foundation calls) comprises a Linux kernel, GNU tools and libraries, additional software, documentation, a window system, window manager, and a desktop environment. 
• There are 600+ Linux distributions (or GNU/Linux), with 300+ are in active development. 
• Some popular mainstream Linux distributions include Debian, Ubuntu, Linux Mint, Fedora, openSUSE, Arch Linux, and the commercial Red Hat Enterprise Linux and SUSE Linux Enterprise Server. Their full relationship/timeline can be referred here: http://upload.wikimedia.org/wikipedia/commons/1/1b/Linux_Distribution_Timeline.svg
  
• Android is also Linux-based, but does not include a command-line interface and programs made for typical Linux distributions.
• Mac OS is not linux-based. Its version 10, Max OS X is actually a Unix operating system. 
• Other popular Unix systems include: HP-UX, IBM AIX, Sun Solairs, IRIX. They are based on different kernels. See details here: http://upload.wikimedia.org/wikipedia/commons/1/1b/Linux_Distribution_Timeline.svg
• iOS is also based on Mac OS X, therefore it's also a Unix OS.