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2.1.2

2.1.1

Introduction

With the improvement of sequencing techniques, chromatinimmunoprecipitation followed by high throughput sequencing (ChIP-Seq)is getting popular to study genome-wide protein-DNA interactions. Toaddress the lack of powerful ChIP-Seq analysis method, we present anovel algorithm, named Model-based Analysis of ChIP-Seq (MACS), foridentifying transcript factor binding sites. MACS captures theinfluence of genome complexity to evaluate the significance ofenriched ChIP regions, and MACS improves the spatial resolution ofbinding sites through combining the information of both sequencing tagposition and orientation. MACS can be easily used for ChIP-Seq dataalone, or with control sample with the increase of specificity.

Install

Please check the file 'INSTALL' in the distribution.

Usage

Example for regular peak calling: macs2 callpeak -t ChIP.bam -c Control.bam -f BAM -g hs -n test -B -q 0.01

Example for broad peak calling: macs2 callpeak -t ChIP.bam -c Control.bam --broad -g hs --broad-cutoff 0.1

There are seven major functions available in MACS serving as sub-commands.

Subcommand	Description
callpeak	Main MACS2 Function to call peaksfrom alignment results.
bdgpeakcall	Call peaks from bedGraph output.
bdgbroadcall	Call broad peaks from bedGraph output.
bdgcmp	Comparing two signal tracks in bedGraph format.
bdgopt	Operate the score column of bedGraph file.
cmbreps	Combine BEDGraphs of scores from replicates.
bdgdiff	Differential peak detection based on paired four bedgraph files.
filterdup	Remove duplicate reads, then save in BED/BEDPE format.
predictd	Predict d or fragment size from alignment results.
pileup	Pileup aligned reads (single end) or fragments (paired-end)
randsample	Randomly choose a number/percentage of total reads.
refinepeak	Take raw reads alignment, refine peak summits.

We only cover 'callpeak' module in this document. Please use 'macs2COMMAND -h' to see the detail description for each option of eachmodule.

Call peaks

This is the main function in MACS2. It can be invoked by 'macs2callpeak' command. If you type this command without parameters, youwill see a full description of commandline options. Here we only listthe essential options.

Essential Options

-t/--treatment FILENAME

This is the only REQUIRED parameter for MACS. File can be in anysupported format specified by --format option. Check --format fordetail. If you have more than one alignment files, you can specifythem as -t A B C. MACS will pool up all these files together.

-c/--control

The control or mock data file. Please follow the same direction as for-t/--treatment.

-n/--name

The name string of the experiment. MACS will use this string NAME tocreate output files like NAME_peaks.xls, NAME_negative_peaks.xls,NAME_peaks.bed , NAME_summits.bed, NAME_model.r and so on. Soplease avoid any confliction between these filenames and yourexisting files.

--outdir

MACS2 will save all output files into speficied folder for thisoption.

-f/--format FORMAT

Format of tag file, can be 'ELAND', 'BED', 'ELANDMULTI','ELANDEXPORT', 'ELANDMULTIPET' (for pair-end tags), 'SAM', 'BAM','BOWTIE', 'BAMPE' or 'BEDPE'. Default is 'AUTO' which will allow MACSto decide the format automatically. 'AUTO' is also usefule when youcombine different formats of files. Note that MACS can't detect'BAMPE' or 'BEDPE' format with 'AUTO', and you have to implicitlyspecify the format for 'BAMPE' and 'BEDPE'.

Nowadays, the most common formats are BED or BAM/SAM.

BED

The BED format can be found at UCSC genome browser website.

The essential columns in BED format input are the 1st column'chromosome name', the 2nd 'start position', the 3rd 'end position',and the 6th, 'strand'.

BAM/SAM

If the format is BAM/SAM, please check the definition in(http://samtools.sourceforge.net/samtools.shtml). If the BAM file isgenerated for paired-end data, MACS will only keep the left mate(5'end) tag. However, when format BAMPE is specified, MACS will use thereal fragments inferred from alignment results for reads pileup.

BEDPE or BAMPE

A special mode will be triggered while format is specified as'BAMPE' or 'BEDPE'. In this way, MACS2 will process the BAM or BEDfiles as paired-end data. Instead of building bimodal distribution ofplus and minus strand reads to predict fragment size, MACS2 willuse actual insert sizes of pairs of reads to build fragmentpileup.

The BAMPE format is just BAM format containing paired-end alignmentinformation, such as those from BWA or BOWTIE.

The BEDPE format is a simplified and more flexible BED format, whichonly contains the first three columns defining the chromosome name,left and right position of the fragment from Paired-endsequencing. Please note, this is NOT the same format used by BEDTOOLS,and BEDTOOLS version of BEDPE is actually not in a standard BEDformat.

BOWTIE

If the format is BOWTIE, you need to provide the ASCII bowtie outputfile with the suffix '.map'. Please note that, you need to make surethat in the bowtie output, you only keep one location for oneread. Check the bowtie manual for detail if you want at(http://bowtie-bio.sourceforge.net/manual.shtml)

Here is the definition for Bowtie output in ASCII characters I copiedfrom the above webpage:

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1. Name of read that aligned
2. Orientation of read in the alignment, '-' for reverse complement, '+'otherwise
3. Name of reference sequence where alignment occurs, or ordinal IDif no name was provided
4. 0-based offset into the forward reference strand where leftmostcharacter of the alignment occurs
5. Read sequence (reverse-complemented if orientation is -)
6. ASCII-encoded read qualities (reversed if orientation is -). Theencoded quality values are on the Phred scale and the encoding isASCII-offset by 33 (ASCII char !).
7. Number of other instances where the same read aligns against thesame reference characters as were aligned against in thisalignment. This is not the number of other places the read alignswith the same number of mismatches. The number in this column isgenerally not a good proxy for that number (e.g., the number inthis column may be '0' while the number of other alignments withthe same number of mismatches might be large). This column waspreviously described as 'Reserved'.
8. Comma-separated list of mismatch descriptors. If there are nomismatches in the alignment, this field is empty. A singledescriptor has the format offset:reference-base>read-base. Theoffset is expressed as a 0-based offset from the high-quality (5')end of the read.

ELAND

If the format is ELAND, the file must be ELAND result output file,each line MUST represents only ONE tag, with fields of:

1. Sequence name (derived from file name and line number if format is not Fasta)
2. Sequence
3. Type of match:

• NM: no match found.
• QC: no matching done: QC failure (too many Ns basically).
• RM: no matching done: repeat masked (may be seen if repeatFile.txt was specified).
• U0: Best match found was a unique exact match.
• U1: Best match found was a unique 1-error match.
• U2: Best match found was a unique 2-error match.
• R0: Multiple exact matches found.
• R1: Multiple 1-error matches found, no exact matches.
• R2: Multiple 2-error matches found, no exact or 1-error matches.

4. Number of exact matches found.
5. Number of 1-error matches found.
6. Number of 2-error matches found.
   Rest of fields are only seen if a unique best match was found(i.e. the match code in field 3 begins with 'U').
7. Genome file in which match was found.
8. Position of match (bases in file are numbered starting at 1).
9. Direction of match (F=forward strand, R=reverse).
10. How N characters in read were interpreted: ('.'=not applicable,'D'=deletion, 'I'=insertion). Rest of fields are only seen inthe case of a unique inexact match (i.e. the match code was U1 orU2).
11. Position and type of first substitution error (e.g. 12A: base 12was A, not whatever is was in read).
12. Position and type of first substitution error, as above.

ELANDMULTI

If the format is ELANDMULTI, the file must be ELAND output file frommultiple-match mode, each line MUST represents only ONE tag, withfields of:

1. Sequence name
2. Sequence
3. Either NM, QC, RM (as described above) or the following:
4. x:y:z where x, y, and z are the number of exact, single-error, and 2-error matches found
5. Blank, if no matches found or if too many matches found, or the following:BAC_plus_vector.fa:163022R1,170128F2,E_coli.fa:3909847R1 This says there are two matches to BAC_plus_vector.fa: one in the reverse direction starting at position 160322 with one error, one in the forward direction starting at position 170128 with two errors. There is also a single-error match to E_coli.fa.

Notes

1. For BED format, the 6th column of strand information is required byMACS. And please pay attention that the coordinates in BED format iszero-based and half-open(http://genome.ucsc.edu/FAQ/FAQtracks#tracks1).

2. For plain ELAND format, only matches with match type U0, U1 or U2is accepted by MACS, i.e. only the unique match for a sequence withless than 3 errors is involed in calculation. If multiple hits of asingle tag are included in your raw ELAND file, please remove theredundancy to keep the best hit for that sequencing tag.

3. ELAND export format support sometimes may not work on yourdatasets, because people may mislabel the 11th and 12th column. MACSuses 11th column as the sequence name which should be the chromosomenames.

-g/--gsize

PLEASE assign this parameter to fit your needs!

It's the mappable genome size or effective genome size which isdefined as the genome size which can be sequenced. Because of therepetitive features on the chromsomes, the actual mappable genome sizewill be smaller than the original size, about 90% or 70% of the genomesize. The default hs -- 2.7e9 is recommended for UCSC human hg18assembly. Here are all precompiled parameters for effective genomesize:

• hs: 2.7e9
• mm: 1.87e9
• ce: 9e7
• dm: 1.2e8

-s/--tsize

The size of sequencing tags. If you don't specify it, MACS will try touse the first 10 sequences from your input treatment file to determinethe tag size. Specifying it will override the automatically determinedtag size.

-q/--qvalue

The qvalue (minimum FDR) cutoff to call significant regions. Defaultis 0.05. For broad marks, you can try 0.05 as cutoff. Q-values arecalculated from p-values using Benjamini-Hochberg procedure.

-p/--pvalue

The pvalue cutoff. If -p is specified, MACS2 will use pvalue insteadof qvalue.

--nolambda

With this flag on, MACS will use the background lambda as locallambda. This means MACS will not consider the local bias at peakcandidate regions.

--slocal, --llocal

These two parameters control which two levels of regions will bechecked around the peak regions to calculate the maximum lambda aslocal lambda. By default, MACS considers 1000bp for small localregion(--slocal), and 10000bps for large local region(--llocal) whichcaptures the bias from a long range effect like an open chromatindomain. You can tweak these according to your project. Remember thatif the region is set too small, a sharp spike in the input data maykill the significant peak.

--nomodel

While on, MACS will bypass building the shifting model.

--extsize

While '--nomodel' is set, MACS uses this parameter to extend reads in5'->3' direction to fix-sized fragments. For example, if the size ofbinding region for your transcription factor is 200 bp, and you wantto bypass the model building by MACS, this parameter can be setas 200. This option is only valid when --nomodel is set or when MACSfails to build model and --fix-bimodal is on.

--shift

Note, this is NOT the legacy --shiftsize option which is replaced by--extsize! You can set an arbitrary shift in bp here. Please Usediscretion while setting it other than default value (0). When--nomodel is set, MACS will use this value to move cutting ends (5')then apply --extsize from 5' to 3' direction to extend them tofragments. When this value is negative, ends will be moved toward3'->5' direction, otherwise 5'->3' direction. Recommended to keep itas default 0 for ChIP-Seq datasets, or -1 * half of EXTSIZE togetherwith --extsize option for detecting enriched cutting loci such ascertain DNAseI-Seq datasets. Note, you can't set values other than 0if format is BAMPE or BEDPE for paired-end data. Default is 0.

Here are some examples for combining --shift and --extsize:

1. To find enriched cutting sites such as some DNAse-Seq datasets. Inthis case, all 5' ends of sequenced reads should be extended in bothdirection to smooth the pileup signals. If the wanted smoothing windowis 200bps, then use '--nomodel --shift -100 --extsize 200'.

2. For certain nucleosome-seq data, we need to pileup the centers ofnucleosomes using a half-nucleosome size for wavelet analysis(e.g. NPS algorithm). Since the DNA wrapped on nucleosome is about147bps, this option can be used: --nomodel --shift 37 --extsize 73.

--keep-dup

It controls the MACS behavior towards duplicate tags at the exact samelocation -- the same coordination and the same strand. The default'auto' option makes MACS calculate the maximum tags at the exact samelocation based on binomal distribution using 1e-5 as pvalue cutoff;and the 'all' option keeps every tags. If an integer is given, atmost this number of tags will be kept at the same location. Thedefault is to keep one tag at the same location. Default: 1

--broad

When this flag is on, MACS will try to composite broad regions inBED12 ( a gene-model-like format ) by putting nearby highly enrichedregions into a broad region with loose cutoff. The broad region iscontrolled by another cutoff through --broad-cutoff. The maximumlength of broad region length is 4 times of d from MACS. DEFAULT:False

--broad-cutoff

Cutoff for broad region. This option is not available unless --broadis set. If -p is set, this is a pvalue cutoff, otherwise, it's aqvalue cutoff. DEFAULT: 0.1

--scale-to <large|small>

When set to 'large', linearly scale the smaller dataset to the samedepth as larger dataset. By default or being set as 'small', thelarger dataset will be scaled towards the smaller dataset. Beware, toscale up small data would cause more false positives.

-B/--bdg

If this flag is on, MACS will store the fragment pileup, controllambda, -log10pvalue and -log10qvalue scores in bedGraph files. ThebedGraph files will be stored in current directory namedNAME_treat_pileup.bdg for treatment data, NAME_control_lambda.bdgfor local lambda values from control, NAME_treat_pvalue.bdg forPoisson pvalue scores (in -log10(pvalue) form), andNAME_treat_qvalue.bdg for q-value scores fromBenjamini–Hochberg–Yekutieli procedure.

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--call-summits

MACS will now reanalyze the shape of signal profile (p or q-scoredepending on cutoff setting) to deconvolve subpeaks within each peakcalled from general procedure. It's highly recommended to detectadjacent binding events. While used, the output subpeaks of a bigpeak region will have the same peak boundaries, and different scoresand peak summit positions.

Output files

1. NAME_peaks.xls is a tabular file which contains information aboutcalled peaks. You can open it in excel and sort/filter using excelfunctions. Information include:

   • chromosome name
   • start position of peak
   • end position of peak
   • length of peak region
   • absolute peak summit position
   • pileup height at peak summit, -log10(pvalue) for the peak summit (e.g. pvalue =1e-10, then this value should be 10)
   • fold enrichment for this peak summit against random Poisson distribution with local lambda, -log10(qvalue) at peak summit

   Coordinates in XLS is 1-based which is different with BED format.

2. NAME_peaks.narrowPeak is BED6+4 format file which contains thepeak locations together with peak summit, pvalue and qvalue. Youcan load it to UCSC genome browser. Definition of some specificcolumns are:

   • 5th: integer score for display calculated as int(-10*log10qvalue). Please note that currently this value might be out of the [0-1000] range defined in UCSC Encode narrowPeak format
   • 7th: fold-change
   • 8th: -log10pvalue
   • 9th: -log10qvalue
   • 10th: relative summit position to peak start

   The file can be loaded directly to UCSC genome browser. Remove the beginning track line if you want toanalyze it by other tools.

3. NAME_summits.bed is in BED format, which contains the peak summitslocations for every peaks. The 5th column in this file is-log10pvalue the same as NAME_peaks.bed. If you want to find themotifs at the binding sites, this file is recommended. The filecan be loaded directly to UCSC genome browser. Remove thebeginning track line if you want to analyze it by other tools.

4. NAME_peaks.broadPeak is in BED6+3 format which is similar tonarrowPeak file, except for missing the 10th column for annotatingpeak summits.

5. NAME_peaks.gappedPeak is in BED12+3 format which contains both thebroad region and narrow peaks. The 5th column is 10*-log10qvalue,to be more compatible to show grey levels on UCSC browser. Tht 7this the start of the first narrow peak in the region, and the 8thcolumn is the end. The 9th column should be RGB color key, however,we keep 0 here to use the default color, so change it if youwant. The 10th column tells how many blocks including the starting1bp and ending 1bp of broad regions. The 11th column shows thelength of each blocks, and 12th for the starts of each blocks. 13th:fold-change, 14th: -log10pvalue, 15th: -log10qvalue. The file can beloaded directly to UCSC genome browser.

6. NAME_model.r is an R script which you can use to produce a PDFimage about the model based on your data. Load it to R by:

   $ Rscript NAME_model.r

   Then a pdf file NAME_model.pdf will be generated in your currentdirectory. Note, R is required to draw this figure.

7. The .bdg files are in bedGraph format which can be imported to UCSCgenome browser or be converted into even smaller bigWigfiles. There are two kinds of bdg files, one for treatment and theother one for control.

Other useful links

Tips of fine-tuning peak calling

Check the three scripts within MACSv2 package:

1. bdgcmp can be used on *_treat_pileup.bdg and*_control_lambda.bdg or bedGraph files from other resourcesto calculate score track.

2. bdgpeakcall can be used on *_treat_pvalue.bdg or the filegenerated from bdgcmp or bedGraph file from other resources tocall peaks with given cutoff, maximum-gap between nearby mergablepeaks and minimum length of peak. bdgbroadcall works similarly tobdgpeakcall, however it will output _broad_peaks.bed in BED12format.

3. Differential calling tool -- bdgdiff, can be used on 4 bedgraphfiles which are scores between treatment 1 and control 1,treatment 2 and control 2, treatment 1 and treatment 2, treatment2 and treatment 1. It will output the consistent and unique sitesaccording to parameter settings for minimum length, maximum gapand cutoff.

4. You can combine subcommands to do a step-by-step peakcalling. Read detail at MACS2 wikipage

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